diff --git a/docs/artifacts/hard_v2_deeper/chunk_150k/probe.txt b/docs/artifacts/hard_v2_deeper/chunk_150k/probe.txt new file mode 100644 index 0000000000000000000000000000000000000000..e24ed6b16b108252ee8cfa003eb9741336465a4c --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_150k/probe.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=3275000 +[probe] prompt='Bonjour' + RMS 0.004311 -> 0.029649 (norm 0.2759 -> 1.8976) atoms 3 -> 22 + gen_preview=" 'ns 'ns '�s '�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�sfr!p�" +[probe] prompt='Qui es-tu ?' + RMS 0.006657 -> 0.031680 (norm 0.4261 -> 2.0275) atoms 7 -> 26 + gen_preview="\n'�a\n'�s\n'�s\n'�s\n'�s\ne�s\n'�s\n'�s\ne�s\n'�s\n'�s\neys\n'ys\n'ysfr�p�.\n'ys\n'ys\n'esgr�p�.\n'ys\n'es\n'esgr�p�." +[probe] prompt='Il était une fois' + RMS 0.006141 -> 0.030857 (norm 0.3930 -> 1.9749) atoms 6 -> 25 + gen_preview=" a�s a�a a�a '�a '�a '�a '�a 8�a '�a '�a 8�a '�a U�a U�a U�a U�aaU�aaU�aaU�aaU�a" +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.004311 -> 0.029649 (norm 0.2759 -> 1.8976) atoms 3 -> 22 + gen_preview=" 'ns 'ns '�s '�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�sfr!p�" +[probe] mean off-diag cosine logits=0.914219 alpha=0.839724 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/hard_v2_deeper/chunk_150k/run_metrics.json b/docs/artifacts/hard_v2_deeper/chunk_150k/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..637162946a693aef1bfe136bb1053bdb2f2c2743 --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_150k/run_metrics.json @@ -0,0 +1,144 @@ +{ + "stream": true, + "data_path": null, + "data_glob": "data/dialogue_shards/part_*", + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt" + ], + "data_bytes": 7066157, + "data_characters": null, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": null, + "train_packet_count": null, + "validation_packet_count": 2048, + "mean_packet_bytes": null, + "max_packet_bytes": null, + "min_packet_bytes": null, + "bytes_seen": 524288, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 50000, + "start_step": 3225000, + "seed": 20260918, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "stream": true, + "chunk_bytes": 1048576, + "loop_shards": true, + "stream_buffer": 2048, + "stream_prefetch": true, + "enable_merge": true, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "slow_every": 1 + }, + "packets_seen": 97538, + "stream_epoch": 0, + "train": { + "steps": 50000, + "start_step": 3225000, + "total_steps": 3275000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 1381.466633162001, + "transitions_per_second": 36.19341850157928, + "first_loss": 11.078485488891602, + "final_loss": 6.2086687088012695, + "final_total_perplexity": 497.0391068427024, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0059940814971924, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9980056285858154, + "field_norm_max": 191.99998474121094, + "field_limited_steps": 48452, + "field_limited_fraction": 0.96904, + "final_dynamics": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.3081580400466919, + "energy_decay_before": 0.29993849992752075, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + }, + "final_atoms_before_validation": 8, + "stream": true, + "bytes_seen": 524288 + }, + "validation": { + "transitions": 256, + "loss": 7.102966853417456, + "total_perplexity": 1215.5681424282864, + "byte_loss": 4.10431616846472, + "byte_perplexity": 60.60128930231591, + "source": "stream_ring" + }, + "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt", + "reload": { + "n_atoms": 80, + "field_norm": 191.99984741210938, + "time": 500.1767883300781, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "21723f2721726c2d3f210a276561216521", + "text": "!r?'!rl-?!\n'ea!e!", + "reload_text": "!r?'!rl-?!\n'ea!e!", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "c271706d7975c371202d672c2d4a7971700a20a9", + "text": "\ufffdqpmyu\ufffdq -g,-Jyqp\n \ufffd", + "reload_text": "\ufffdqpmyu\ufffdq -g,-Jyqp\n \ufffd", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "4165616d217520a869a92155c361216565612175", + "text": "Aeam!u \ufffdi\ufffd!U\ufffda!eea!u", + "reload_text": "Aeam!u \ufffdi\ufffd!U\ufffda!eea!u", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/hard_v2_deeper/chunk_150k/train_excerpt.txt b/docs/artifacts/hard_v2_deeper/chunk_150k/train_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..7f0b149ca86da9cb6ea7a28fd9b834d1c0fb3894 --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_150k/train_excerpt.txt @@ -0,0 +1,29 @@ +train lock skipped (--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3225000, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95)) +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP) +field_obligatory_readout=ON (migrated=False) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LR param groups differ from checkpoint +step=3225001 (run 1/50000) loss=11.07849 byte_ppl=1135.752 atoms=1 merges=0 field=0.1176 rms=0.0021 scale=1.0000 fcos=0.678 ign=0.0000 mph=0.000 bytes=524288 pkts=97538 shard=0 +step=3225025 (run 25/50000) loss=7.47295 byte_ppl=57.852 atoms=25 merges=0 field=1.1280 rms=0.0177 scale=1.0000 fcos=0.647 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225050 (run 50/50000) loss=5.37463 byte_ppl=124.084 atoms=50 merges=0 field=2.1560 rms=0.0337 scale=1.0000 fcos=0.624 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225075 (run 75/50000) loss=6.48096 byte_ppl=32.551 atoms=75 merges=0 field=3.1031 rms=0.0485 scale=1.0000 fcos=0.618 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225100 (run 100/50000) loss=6.93733 byte_ppl=84.216 atoms=100 merges=0 field=4.0551 rms=0.0634 scale=1.0000 fcos=0.613 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225125 (run 125/50000) loss=9.17130 byte_ppl=80.493 atoms=125 merges=0 field=4.8758 rms=0.0762 scale=1.0000 fcos=0.607 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225150 (run 150/50000) loss=5.43816 byte_ppl=39.604 atoms=150 merges=0 field=5.8057 rms=0.0907 scale=1.0000 fcos=0.604 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225175 (run 175/50000) loss=5.48505 byte_ppl=60.693 atoms=175 merges=0 field=6.6279 rms=0.1036 scale=1.0000 fcos=0.599 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225200 (run 200/50000) loss=10.14227 byte_ppl=222.128 atoms=200 merges=0 field=7.5621 rms=0.1182 scale=1.0000 fcos=0.594 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225225 (run 225/50000) loss=4.57154 byte_ppl=19.913 atoms=225 merges=0 field=8.3569 rms=0.1306 scale=1.0000 fcos=0.587 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225250 (run 250/50000) loss=7.15508 byte_ppl=48.066 atoms=250 merges=0 field=9.3910 rms=0.1467 scale=1.0000 fcos=0.584 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3225275 (run 275/50000) loss=5.39268 byte_ppl=55.482 atoms=19 merges=0 field=10.2292 rms=0.1598 scale=1.0000 fcos=0.578 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +... +step=3235000 (run 10000/50000) loss=7.28107 byte_ppl=188.979 atoms=16 merges=0 field=191.9999 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3250000 (run 25000/50000) loss=8.16118 byte_ppl=117.372 atoms=168 merges=0 field=191.9999 rms=3.0000 scale=0.9982 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275000 (run 50000/50000) loss=6.20867 byte_ppl=70.255 atoms=80 merges=0 field=191.9998 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 + "reload_text": "Aeam!u \ufffdi\ufffd!U\ufffda!eea!u", + "reload_match": true + } + } +} diff --git a/docs/artifacts/hard_v2_deeper/chunk_50k/chat.txt b/docs/artifacts/hard_v2_deeper/chunk_50k/chat.txt new file mode 100644 index 0000000000000000000000000000000000000000..3fe9da4e54ffdcefc338863eb3a5ee3ab80f8a8e --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_50k/chat.txt @@ -0,0 +1,59 @@ +### Bonjour +Prompt: Bonjour +Response: uaasu.� + +ߧ' +'�rg'�"�e +j�s�.y +C�s s-a +xts�'�ps� + +'�s +'��or�0�. +O'�yxysgryp 'vs�.�"�.A'v -r�p O�s '� +'y aqmp +ets +sys��dd�]p'��p�vM +shMg�Wp + +### Qui es-tu ? +Prompt: Qui es-tu ? +Response: e a +8'ag� +e�� +syao.� +sva + �a C' �?'v + +s� + +sfa���'s. eya +j� +efa +'ea +'va�CyM +?xha���0s.�� +s s + +### Il était une fois +Prompt: Il était une fois +Response: !el !'�m!feM '� +e�a�nea +ߔa�'�aj'ts ee �'e + +8e + +8Qs +'Qa +jea +'�e��es +'� + +s�eiuQd�e +O'�ir�p?'�eÉ�iL. sye +xee + + +### Bonjour det +Prompt: Bonjour +Response: u�asu'asu'lsu'lsuuliunli6nli6sli6sliustiuOtiuOtiuOtiuO�ijO�ijO�i6O�s6O�s6O�s6O�s6O�s6O�s6O�s6u�s diff --git a/docs/artifacts/hard_v2_deeper/chunk_50k/probe.txt b/docs/artifacts/hard_v2_deeper/chunk_50k/probe.txt new file mode 100644 index 0000000000000000000000000000000000000000..da83761e3af14c894da969cb60e0f96ca51fb83a --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_50k/probe.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=3175000 +[probe] prompt='Bonjour' + RMS 0.004304 -> 0.028417 (norm 0.2755 -> 1.8187) atoms 3 -> 22 + gen_preview=" 'ns 'ns '�s '�s '�s '�s '�s\n'ps\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s" +[probe] prompt='Qui es-tu ?' + RMS 0.006704 -> 0.032128 (norm 0.4291 -> 2.0562) atoms 7 -> 26 + gen_preview='\nߔa\nߔs\nߔs\ne�s\ne�s\ne�s\ne�s\ne�s\nC�s\nC�s\ne�s\nC�s\nC�sv.mps.\nC�s\nC�s\ne�s\nC�sv.mps.\nC�s\nC�s\nC�s' +[probe] prompt='Il était une fois' + RMS 0.006004 -> 0.028465 (norm 0.3842 -> 1.8217) atoms 6 -> 25 + gen_preview=" a�a a�a a�a '�a '�a '�a '�a '�aaU�aaU�aaU�aa'�aaU�aaU�aaU�aa'�aaU�a6U�a6U�a6U�a" +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.004304 -> 0.028417 (norm 0.2755 -> 1.8187) atoms 3 -> 22 + gen_preview=" 'ns 'ns '�s '�s '�s '�s '�s\n'ps\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s" +[probe] mean off-diag cosine logits=0.915435 alpha=0.845265 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md +[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md +[probe] updated /workspace/exports/atom-ai/docs/SCALE.md +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/hard_v2_deeper/chunk_50k/run_metrics.json b/docs/artifacts/hard_v2_deeper/chunk_50k/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..90927e873eddafde62d7b5ebd5b964e13d8d2b12 --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_50k/run_metrics.json @@ -0,0 +1,144 @@ +{ + "stream": true, + "data_path": null, + "data_glob": "data/dialogue_shards/part_*", + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt" + ], + "data_bytes": 7066157, + "data_characters": null, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": null, + "train_packet_count": null, + "validation_packet_count": 2048, + "mean_packet_bytes": null, + "max_packet_bytes": null, + "min_packet_bytes": null, + "bytes_seen": 524288, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 50000, + "start_step": 3125000, + "seed": 20260918, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "stream": true, + "chunk_bytes": 1048576, + "loop_shards": true, + "stream_buffer": 2048, + "stream_prefetch": true, + "enable_merge": true, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "slow_every": 1 + }, + "packets_seen": 97538, + "stream_epoch": 0, + "train": { + "steps": 50000, + "start_step": 3125000, + "total_steps": 3175000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 1460.8717423260005, + "transitions_per_second": 34.22613946956766, + "first_loss": 20.27935218811035, + "final_loss": 6.268411636352539, + "final_total_perplexity": 527.6386299168859, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0064809322357178, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9978440403938293, + "field_norm_max": 191.99996948242188, + "field_limited_steps": 48500, + "field_limited_fraction": 0.97, + "final_dynamics": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.28007209300994873, + "energy_decay_before": 0.2999384105205536, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + }, + "final_atoms_before_validation": 7, + "stream": true, + "bytes_seen": 524288 + }, + "validation": { + "transitions": 256, + "loss": 7.183161847293377, + "total_perplexity": 1317.0660433453525, + "byte_loss": 4.123776443302631, + "byte_perplexity": 61.79215676999581, + "source": "stream_ring" + }, + "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt", + "reload": { + "n_atoms": 80, + "field_norm": 191.99986267089844, + "time": 500.1767883300781, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "617261616c61726c782d6fa82c61726c61617270", + "text": "araalarlx-o\ufffd,arlaarp", + "reload_text": "araalarlx-o\ufffd,arlaarp", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "c2636d61797570612075722c2175706d6175c373", + "text": "\ufffdcmayupa ur,!upmau\ufffds", + "reload_text": "\ufffdcmayupa ur,!upmau\ufffds", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2075200a216594a86565212cc3f12075202d2138", + "text": " u \n!e\ufffd\ufffdee!,\ufffd\ufffd u -!8", + "reload_text": " u \n!e\ufffd\ufffdee!,\ufffd\ufffd u -!8", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/hard_v2_deeper/chunk_50k/train_excerpt.txt b/docs/artifacts/hard_v2_deeper/chunk_50k/train_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..cacc2804759f912cee7971d558008e48ac7a5d7e --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/chunk_50k/train_excerpt.txt @@ -0,0 +1,29 @@ +train lock skipped (--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3125000, legacy_surface_migrated=True) +dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95)) +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP) +field_obligatory_readout=ON (migrated=False) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LayerNorm migration changed bias scale +step=3125001 (run 1/50000) loss=20.27935 byte_ppl=1781.479 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.000 bytes=524288 pkts=97538 shard=0 +step=3125025 (run 25/50000) loss=11.63221 byte_ppl=115.688 atoms=25 merges=0 field=1.1821 rms=0.0185 scale=1.0000 fcos=0.143 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125050 (run 50/50000) loss=7.01860 byte_ppl=180.592 atoms=50 merges=0 field=2.2246 rms=0.0348 scale=1.0000 fcos=0.408 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125075 (run 75/50000) loss=5.78146 byte_ppl=28.657 atoms=75 merges=0 field=3.2307 rms=0.0505 scale=1.0000 fcos=0.373 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125100 (run 100/50000) loss=6.38058 byte_ppl=75.765 atoms=100 merges=0 field=4.2239 rms=0.0660 scale=1.0000 fcos=0.527 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125125 (run 125/50000) loss=8.49685 byte_ppl=76.502 atoms=125 merges=0 field=5.0844 rms=0.0794 scale=1.0000 fcos=0.532 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125150 (run 150/50000) loss=5.92573 byte_ppl=67.643 atoms=150 merges=0 field=6.0760 rms=0.0949 scale=1.0000 fcos=0.536 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125175 (run 175/50000) loss=5.78230 byte_ppl=72.286 atoms=175 merges=0 field=6.9639 rms=0.1088 scale=1.0000 fcos=0.542 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125200 (run 200/50000) loss=10.76589 byte_ppl=409.006 atoms=200 merges=0 field=7.9200 rms=0.1238 scale=1.0000 fcos=0.539 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125225 (run 225/50000) loss=4.54946 byte_ppl=17.638 atoms=225 merges=0 field=8.7302 rms=0.1364 scale=1.0000 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125250 (run 250/50000) loss=7.75172 byte_ppl=52.010 atoms=250 merges=0 field=9.7824 rms=0.1529 scale=1.0000 fcos=0.546 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3125275 (run 275/50000) loss=5.36541 byte_ppl=55.040 atoms=19 merges=0 field=10.6460 rms=0.1663 scale=1.0000 fcos=0.549 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +... +step=3135000 (run 10000/50000) loss=7.39594 byte_ppl=198.787 atoms=16 merges=0 field=191.9999 rms=3.0000 scale=0.9979 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3150000 (run 25000/50000) loss=8.09320 byte_ppl=118.844 atoms=168 merges=0 field=191.9999 rms=3.0000 scale=0.9980 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3175000 (run 50000/50000) loss=6.26841 byte_ppl=73.648 atoms=80 merges=0 field=191.9999 rms=3.0000 scale=0.9980 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0 + "reload_text": " u \n!e\ufffd\ufffdee!,\ufffd\ufffd u -!8", + "reload_match": true + } + } +} diff --git a/docs/artifacts/hard_v2_deeper/pytest.txt b/docs/artifacts/hard_v2_deeper/pytest.txt new file mode 100644 index 0000000000000000000000000000000000000000..9ead668aa5fd454abb5c004a82b079235896b59d --- /dev/null +++ b/docs/artifacts/hard_v2_deeper/pytest.txt @@ -0,0 +1,2 @@ +.............................s............... [100%] +44 passed, 1 skipped in 3.75s diff --git a/docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.json b/docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.json new file mode 100644 index 0000000000000000000000000000000000000000..e747ac4d8ffde43564cecfc94973d91ad2d5d52d --- /dev/null +++ b/docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \nsoirends \nAsssistant:::::::::::::::::::O \nuurrraais " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je \n \nAsssistant:::::::::::::::::::::::::::O toirriraaarte.tee " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \nsoirends \nAsssistant:::::::::::::::::::O \nuurrraais " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je \nAsssistant::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je \nAAsssistant::::::::::::::::::::::::::::::toirrriisaateur:::::::::::::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::" + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::" + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \n'ut--ourra.toi un \nAsssistant::::::::::::::::::ttiisiisateur:::::::" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je \n'ut--ourra.toi un \nAsssistant::::::::::::::::::ttiisiisateur:::::::" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \n'ut--ourra un \nAsssistant::::::::::::::::::Juurrrriraiisateur::" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je \nAAsssistant::::::::::::::::::::::::aiiliirs reuttilisateur" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je \nAAsssistant:::::::::::::::::::::O un \n\n" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je \nAAsssistant::::::::::::::::::::::::aiiliirs reuuiss " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.txt b/docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.txt new file mode 100644 index 0000000000000000000000000000000000000000..e58c62bd3796ae0e40a026033805b5453b5f323a --- /dev/null +++ b/docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je \nsoirends \nAsssistant:::::::::::::::::::O \nuurrraais ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Je \n \nAsssistant:::::::::::::::::::::::::::O toirriraaarte.tee ' +[T=0.8 seed=1] 'Il était une fois' -> 'Je \nsoirends \nAsssistant:::::::::::::::::::O \nuurrraais ' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> "Je \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::" +[T=0.8 seed=2] 'Qui es-tu ?' -> "Je \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::" +[T=0.8 seed=2] 'Il était une fois' -> 'Je \nAsssistant::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je \nAAsssistant::::::::::::::::::::::::::::::toirrriisaateur:::::::::::::::' +[T=0.8 seed=3] 'Il était une fois' -> 'Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine ' +[T=0.6 seed=1] 'Il était une fois' -> 'Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::' +[T=0.6 seed=3] 'Il était une fois' -> 'Je \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> "Je \n'ut--ourra.toi un \nAsssistant::::::::::::::::::ttiisiisateur:::::::" +[T=1.0 seed=1] 'Qui es-tu ?' -> "Je \n'ut--ourra.toi un \nAsssistant::::::::::::::::::ttiisiisateur:::::::" +[T=1.0 seed=1] 'Il était une fois' -> "Je \n'ut--ourra un \nAsssistant::::::::::::::::::Juurrrriraiisateur::" +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::' +[T=1.0 seed=2] 'Il était une fois' -> 'Je uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Je \nAAsssistant::::::::::::::::::::::::aiiliirs reuttilisateur' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Je \nAAsssistant:::::::::::::::::::::O un \n\n' +[T=1.0 seed=3] 'Il était une fois' -> 'Je \nAAsssistant::::::::::::::::::::::::aiiliirs reuuiss ' diff --git a/docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.json b/docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.json new file mode 100644 index 0000000000000000000000000000000000000000..b05448e8009117a137ee7530c42ba0cb77827a2c --- /dev/null +++ b/docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure \nsoireco" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuu''''' un \nAsssistant:::::::::::::::Onnnnnnnnnnnnner, parle " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je \n'ut-- on \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je \n'ut-- on \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- \nAAsssistant:::::::::::::::::aissssistant::::::::::::, toirrierrrqu'''''" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui,, \nsoirra.\nUtilisateur:::::::::::::::::J'aiilisateur:::::::::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je \nAAssistant::::::::::::::::::aaiilisateur:::::::::::aiililisateur:::::::" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::aaiilisateur:::::::::::::::riiliisateur::::::::::::::aiiliisa" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je \nAsssistant:::::::::::::::::::tuurrrirraaimee \nerrra.." + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \nAsssistant:::::::::::::::::::D'aiilisateur:::::::::::::::::risiilisateu" + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuu'''''''''''' \n'uuttilisateur:::::::::::::::aaiilisateur:::::::::::::::::::" + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je \n'ut-- on \n'uttilisateur::::::::::::::::J prrrra..\nUtilisateur::::::::" + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je \n'ut-- on \nAsssistant::::::::::::::::D'aiilisateur:::::::::::::::::J q" + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- \nAsssistant:::::::::::::::::::::O \nuurrrra..\nUtilisateur::::::::::::::" + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je \nAAssistant:::::::::::::::::::::O \nuurrrra..\nUtilisateur::::::::::::::" + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je \nAAssistant:::::::::::::::::::::O \nuurrrra..\nUtilisateur::::::::::::::" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure \nsoireco" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuu''''' \n D''ut-- \n'uttilisateur::::::::::::aiilisatteurr:" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je ,\nAsssistant:::::::::::::Tiisaaccord \nAsssistant::::::::::::::aaiili" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je ,nds \n rd \nsoirra..\nUtilisateur::::::::::::aiilisaateur:::::::::" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- \nAAsssistant:::::::::::::::::aiiliisateur:::::::::::aiilisatt " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui,, T'ut-- Teuut-- ourra.\n\n" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je \n'uttilisateur:::::::::::::::::Pourrllisaarte..\n\n" + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.txt b/docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.txt new file mode 100644 index 0000000000000000000000000000000000000000..04a323e44d5b7207d4bac3984054e47a9d4cba2e --- /dev/null +++ b/docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure \nsoireco' +[T=0.8 seed=1] 'Qui es-tu ?' -> "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" +[T=0.8 seed=1] 'Il était une fois' -> "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> "Peuu''''' un \nAsssistant:::::::::::::::Onnnnnnnnnnnnner, parle " +[T=0.8 seed=2] 'Qui es-tu ?' -> "Je \n'ut-- on \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::" +[T=0.8 seed=2] 'Il était une fois' -> "Je \n'ut-- on \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::" +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> "Peut-- \nAAsssistant:::::::::::::::::aissssistant::::::::::::, toirrierrrqu'''''" +[T=0.8 seed=3] 'Qui es-tu ?' -> "Oui,, \nsoirra.\nUtilisateur:::::::::::::::::J'aiilisateur:::::::::::" +[T=0.8 seed=3] 'Il était une fois' -> 'Je \nAAssistant::::::::::::::::::aaiilisateur:::::::::::aiililisateur:::::::' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::aaiilisateur:::::::::::::::riiliisateur::::::::::::::aiiliisa' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je \nAsssistant:::::::::::::::::::tuurrrirraaimee \nerrra..' +[T=0.6 seed=1] 'Il était une fois' -> "Je \nAsssistant:::::::::::::::::::D'aiilisateur:::::::::::::::::risiilisateu" +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> "Peuu'''''''''''' \n'uuttilisateur:::::::::::::::aaiilisateur:::::::::::::::::::" +[T=0.6 seed=2] 'Qui es-tu ?' -> "Je \n'ut-- on \n'uttilisateur::::::::::::::::J prrrra..\nUtilisateur::::::::" +[T=0.6 seed=2] 'Il était une fois' -> "Je \n'ut-- on \nAsssistant::::::::::::::::D'aiilisateur:::::::::::::::::J q" +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Peut-- \nAsssistant:::::::::::::::::::::O \nuurrrra..\nUtilisateur::::::::::::::' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je \nAAssistant:::::::::::::::::::::O \nuurrrra..\nUtilisateur::::::::::::::' +[T=0.6 seed=3] 'Il était une fois' -> 'Je \nAAssistant:::::::::::::::::::::O \nuurrrra..\nUtilisateur::::::::::::::' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure \nsoireco' +[T=1.0 seed=1] 'Qui es-tu ?' -> "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" +[T=1.0 seed=1] 'Il était une fois' -> "Je \n'ut-- on \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa" +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> "Peuu''''' \n D''ut-- \n'uttilisateur::::::::::::aiilisatteurr:" +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je ,\nAsssistant:::::::::::::Tiisaaccord \nAsssistant::::::::::::::aaiili' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ,nds \n rd \nsoirra..\nUtilisateur::::::::::::aiilisaateur:::::::::' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Peut-- \nAAsssistant:::::::::::::::::aiiliisateur:::::::::::aiilisatt ' +[T=1.0 seed=3] 'Qui es-tu ?' -> "Oui,, T'ut-- Teuut-- ourra.\n\n" +[T=1.0 seed=3] 'Il était une fois' -> "Je \n'uttilisateur:::::::::::::::::Pourrllisaarte..\n\n" diff --git a/docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.json b/docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.json new file mode 100644 index 0000000000000000000000000000000000000000..878300500a0bace863c70fb56513468da6e7134c --- /dev/null +++ b/docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuut-- \nAAssistant::::::::::::::::toirre \n\n" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui,, \nAAssistant::::::::::::::::toirre \n\n" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \nourrra.iis \nAsssistant::::::::::::::::::Jarliilisateur::::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- un \nAAssistant::::::::::::::::toirrrilisateur::::::::::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je \n'uurrecommence \nAAssistant:::::::::::::::On nnnnnnnnnnne \naitti" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je \n'uurrecommence \nAAssistant:::::::::::::::On nnnnnnnnnnne \naitti" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuues \neuuttilisateur::::::::::::::::J'aiilisateur:::::::::::::::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui,, \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui,, \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuut-- \nAAssistant::::::::::::::::toirrirrraaartout " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui,, \nAAssistant::::::::::::::::toirrrraiisateur::::::::::::::::::" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \n'uut-- \nAAssistant::::::::::::::::::J \naiilisateur:::" + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- \naittilisateur:::::::::::::::::::aaiilisateur::::::::::::::::" + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne \nerra.. " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne \nerra.. " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuu'''''''''''' \neuuirra..\nUtilisateur:::::::::::::::::::J toirraaime " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui,, \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n" + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui,, \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peuut-- \nAssaaistant:::::::::::::::toirre \n\n" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui,, \nAssaaistant:::::::::::::::toirre \n\n" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je \n'ut-- recommence ??itilis--ilisateur::::::::::::::::Jriisaait �uee " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--être un \nAAssistant:::::::::::::::On rirrilisateur::::::::::::" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je ,ndre un \nAAssistant:::::::::::::::Onnnnnne \narle " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je ,ndi,,, \nsourrais \n \nAAssistant::" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, rd rdirra.. un \na" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui,, T'ut--ourra..\n\n" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, rirrases T'ut-- \nourrapposes " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.txt b/docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.txt new file mode 100644 index 0000000000000000000000000000000000000000..b52b63f2575d0b5825c021d022f0ba156da58e43 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Peuut-- \nAAssistant::::::::::::::::toirre \n\n' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Oui,, \nAAssistant::::::::::::::::toirre \n\n' +[T=0.8 seed=1] 'Il était une fois' -> 'Je \nourrra.iis \nAsssistant::::::::::::::::::Jarliilisateur::::::' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Peut-- un \nAAssistant::::::::::::::::toirrrilisateur::::::::::::' +[T=0.8 seed=2] 'Qui es-tu ?' -> "Je \n'uurrecommence \nAAssistant:::::::::::::::On nnnnnnnnnnne \naitti" +[T=0.8 seed=2] 'Il était une fois' -> "Je \n'uurrecommence \nAAssistant:::::::::::::::On nnnnnnnnnnne \naitti" +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> "Peuues \neuuttilisateur::::::::::::::::J'aiilisateur:::::::::::::::::" +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Oui,, \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::' +[T=0.8 seed=3] 'Il était une fois' -> 'Oui,, \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Peuut-- \nAAssistant::::::::::::::::toirrirrraaartout ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Oui,, \nAAssistant::::::::::::::::toirrrraiisateur::::::::::::::::::' +[T=0.6 seed=1] 'Il était une fois' -> "Je \n'uut-- \nAAssistant::::::::::::::::::J \naiilisateur:::" +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Peut-- \naittilisateur:::::::::::::::::::aaiilisateur::::::::::::::::' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne \nerra.. ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne \nerra.. ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> "Peuu'''''''''''' \neuuirra..\nUtilisateur:::::::::::::::::::J toirraaime " +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Oui,, \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n' +[T=0.6 seed=3] 'Il était une fois' -> 'Oui,, \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Peuut-- \nAssaaistant:::::::::::::::toirre \n\n' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Oui,, \nAssaaistant:::::::::::::::toirre \n\n' +[T=1.0 seed=1] 'Il était une fois' -> "Je \n'ut-- recommence ??itilis--ilisateur::::::::::::::::Jriisaait �uee " +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Peut--être un \nAAssistant:::::::::::::::On rirrilisateur::::::::::::' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je ,ndre un \nAAssistant:::::::::::::::Onnnnnne \narle ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ,ndi,,, \nsourrais \n \nAAssistant::' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,, rd rdirra.. un \na' +[T=1.0 seed=3] 'Qui es-tu ?' -> "Oui,, T'ut--ourra..\n\n" +[T=1.0 seed=3] 'Il était une fois' -> "Oui, rirrases T'ut-- \nourrapposes " diff --git a/docs/artifacts/last_atom_dropout/gen_coherent_4868000_b4828.txt b/docs/artifacts/last_atom_dropout/gen_coherent_4868000_b4828.txt new file mode 100644 index 0000000000000000000000000000000000000000..1c8083dbaea4cfc866538d22d8b2cd301628f67f --- /dev/null +++ b/docs/artifacts/last_atom_dropout/gen_coherent_4868000_b4828.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Oui,, +PROMPT: Qui es-tu ? +RESP: Oui,, +PROMPT: Il était une fois +RESP: Oui,, diff --git a/docs/artifacts/last_atom_dropout/gen_coherent_4876000_b4828.txt b/docs/artifacts/last_atom_dropout/gen_coherent_4876000_b4828.txt new file mode 100644 index 0000000000000000000000000000000000000000..d9f4fbe8242a7e7dec86a4820ede43412b09ce97 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/gen_coherent_4876000_b4828.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Bonne +PROMPT: Qui es-tu ? +RESP: Oui,, +PROMPT: Il était une fois +RESP: Oui,, diff --git a/docs/artifacts/last_atom_dropout/gen_coherent_4876000_ladrop.txt b/docs/artifacts/last_atom_dropout/gen_coherent_4876000_ladrop.txt new file mode 100644 index 0000000000000000000000000000000000000000..5c9b4b1dec03302442acae469028f28f03200434 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/gen_coherent_4876000_ladrop.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Bonne +PROMPT: Qui es-tu ? +RESP: Bonne +PROMPT: Il était une fois +RESP: Bonne diff --git a/docs/artifacts/last_atom_dropout/measure.sh b/docs/artifacts/last_atom_dropout/measure.sh new file mode 100644 index 0000000000000000000000000000000000000000..9aace7e7620b835c1b7e2eaf672cf9db34dc8f5a --- /dev/null +++ b/docs/artifacts/last_atom_dropout/measure.sh @@ -0,0 +1,26 @@ +#!/usr/bin/env bash +set -u +cd /workspace/exports/atom-ai +export PYTHONPATH=. OMP_NUM_THREADS=1 MKL_NUM_THREADS=1 +PY=.venv/bin/python +A=docs/artifacts/last_atom_dropout +LA=checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt +LIVE=checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt +START=checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt +# 1) exact coherence-probe CLI (unseeded, as in train_until_coherent.sh) +G=$A/gen_coherent_4876000_ladrop.txt; : > $G +for p in "Bonjour, comment ça va ?" "Qui es-tu ?" "Il était une fois"; do + RESP=$($PY tools/chat_atom_native.py --checkpoint "$LA" --prompt "$p" --no-role-prime \ + --max-packets 96 --max-length 100 --temperature 0.8 --top-k 12 2>/dev/null | sed -n 's/^Response: //p' | head -1) + echo "PROMPT: $p" >> $G; echo "RESP: $RESP" >> $G +done +# 2) seeded chats, 3 ckpts x 3 seeds x 3 temps +for tag in ladrop_4876000:$LA live_4876000:$LIVE start_4868000:$START; do + name=${tag%%:*}; ck=${tag#*:} + $PY tools/chat_seeds_probe.py --checkpoint "$ck" --seeds 1 2 3 --temps 0.8 0.6 1.0 \ + --out $A/chat_seeds_${name}.json > $A/chat_seeds_${name}.txt 2>&1 +done +# 3) val normal vs last_atom-zeroed on both rings +$PY -u tools/eval_last_atom_ablation.py --end-steps 4868000 4876000 \ + --checkpoints "$START" "$LIVE" "$LA" --out $A/val_ablation.json > $A/val_ablation.txt 2>&1 +echo DONE > $A/.measure_done diff --git a/docs/artifacts/last_atom_dropout/probe_start_time.txt b/docs/artifacts/last_atom_dropout/probe_start_time.txt new file mode 100644 index 0000000000000000000000000000000000000000..2d4c508577693be843a17e0b5eba5272ab29214c --- /dev/null +++ b/docs/artifacts/last_atom_dropout/probe_start_time.txt @@ -0,0 +1 @@ +2026-09-28T10:45:12-07:00 diff --git a/docs/artifacts/last_atom_dropout/pytest_full.txt b/docs/artifacts/last_atom_dropout/pytest_full.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a803266b08134195debc4e9554f323c22775c26 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/pytest_full.txt @@ -0,0 +1,87 @@ +..................F.......................................s............. [ 68%] +....................F.F.......... [100%] +=================================== FAILURES =================================== +_ ChatMergeOffIngestTests.test_payload_copy_sees_distinct_atoms_when_merge_off _ + +self = + + def test_payload_copy_sees_distinct_atoms_when_merge_off(self) -> None: + """Distinct living payloads under merge-off boost target byte mass vs MERGE collapse.""" + torch.manual_seed(5) + model = self._tiny() + model.eval() + prompt = "AAA BBB CCC DDD EEE FFF " + packets = model.atomizer.encode(prompt, reset=True) + self.assertGreaterEqual(len(packets), 2) + + model.reset_state(reset_atomizer=True) + last_off = None + for p in packets: + last_off = model.forward_packet(p, merge_enabled=False) + assert last_off is not None + n_off = len(model.core.atoms) + logits_off = last_off["surface"]["byte_logits"] + # Bytes present in prompt payloads. + target = sorted({b for p in packets for b in (p.payload or b"")}) + mass_off = float(logits_off.softmax(dim=-1)[:, target].sum().item()) + + model.reset_state(reset_atomizer=True) + packets2 = model.atomizer.encode(prompt, reset=True) + last_on = None + for p in packets2: + last_on = model.forward_packet(p) + assert last_on is not None + n_on = len(model.core.atoms) + logits_on = last_on["surface"]["byte_logits"] + mass_on = float(logits_on.softmax(dim=-1)[:, target].sum().item()) + + self.assertGreaterEqual(n_off, 2) + self.assertEqual(n_on, 1) + # Soft check: merge-off should not be worse on prompt-byte mass. +> self.assertGreaterEqual( + mass_off + 1e-6, + mass_on * 0.9, + msg=f"mass_off={mass_off:.4f} mass_on={mass_on:.4f} n_off={n_off} n_on={n_on}", + ) +E AssertionError: 3.050107763839722 not greater than or equal to 3.1522358894348144 : mass_off=3.0501 mass_on=3.5025 n_off=3 n_on=1 + +test/test_chat_merge_off.py:123: AssertionError +____________________ SpeechLockUnitTests.test_dialogue_wrap ____________________ + +self = + + def test_dialogue_wrap(self) -> None: +> self.assertEqual( + format_dialogue_prompt("Bonjour"), + "Utilisateur: Bonjour\nAssistant:", + ) +E AssertionError: 'Utilisateur: Bonjour\nAssistant: ' != 'Utilisateur: Bonjour\nAssistant:' +E Utilisateur: Bonjour +E - Assistant: +E ? - +E + Assistant: + +test/test_speech_lock.py:17: AssertionError +__________ SpeechLockUnitTests.test_speech_ok_rejects_attractor_soup ___________ + +self = + + def test_speech_ok_rejects_attractor_soup(self) -> None: + self.assertFalse(speech_ok(b"")) +> self.assertFalse(speech_ok(b"auiseateu : aernun e")) +E AssertionError: True is not false + +test/test_speech_lock.py:25: AssertionError +=============================== warnings summary =============================== +test/test_field_hard_couple.py::FieldHardCoupleTests::test_load_keeps_tip_field_feat_norm + /workspace/exports/atom-ai/test/test_field_hard_couple.py:125: UserWarning: Converting a tensor with requires_grad=True to a scalar may lead to unexpected behavior. + Consider using tensor.detach() first. (Triggered internally at /__w/pytorch/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:820.) + float(model2.surface.field_hard_couple_byte.weight.abs().mean()), 0.0 + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +=========================== short test summary info ============================ +FAILED test/test_chat_merge_off.py::ChatMergeOffIngestTests::test_payload_copy_sees_distinct_atoms_when_merge_off +FAILED test/test_speech_lock.py::SpeechLockUnitTests::test_dialogue_wrap - As... +FAILED test/test_speech_lock.py::SpeechLockUnitTests::test_speech_ok_rejects_attractor_soup +3 failed, 101 passed, 1 skipped, 1 warning in 77.00s (0:01:16) +HEAD 6bc06a9 (pre-change, git archive): same 3 failures (test_chat_merge_off::test_payload_copy_sees_distinct_atoms_when_merge_off, test_speech_lock::test_dialogue_wrap, test_speech_lock::test_speech_ok_rejects_attractor_soup) -> pre-existing diff --git a/docs/artifacts/last_atom_dropout/run_metrics_4868000_d32_ms1M_lrd_b4828.json b/docs/artifacts/last_atom_dropout/run_metrics_4868000_d32_ms1M_lrd_b4828.json new file mode 100644 index 0000000000000000000000000000000000000000..d8e66bb7f3e73bcec8ccbeb9184f1e1b89c80bcc --- /dev/null +++ b/docs/artifacts/last_atom_dropout/run_metrics_4868000_d32_ms1M_lrd_b4828.json @@ -0,0 +1,163 @@ +{ + "stream": true, + "data_path": null, + "data_glob": "data/corpus_fr_medium*.txt", + "shard_paths": [ + "/workspace/exports/atom-ai/data/corpus_fr_medium.txt", + "/workspace/exports/atom-ai/data/corpus_fr_medium_s21.txt" + ], + "data_bytes": 1000453, + "data_characters": null, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": null, + "train_packet_count": null, + "validation_packet_count": 2048, + "mean_packet_bytes": null, + "max_packet_bytes": null, + "min_packet_bytes": null, + "bytes_seen": 4395028, + "config": { + "d_model": 32, + "n_modes": 32, + "n_atoms_max": 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"reload_text": "Je ", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3a3a3a3a3a3a3a3a", + "text": "::::::::", + "reload_text": "::::::::", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/last_atom_dropout/train_ladrop.log b/docs/artifacts/last_atom_dropout/train_ladrop.log new file mode 100644 index 0000000000000000000000000000000000000000..64f956c0c14900d23a45c7fb0e99af9d8404fef5 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/train_ladrop.log @@ -0,0 +1,504 @@ +train lock skipped (--allow-parallel-train) +stream skip: advancing 4372000 packet transitions... +stream skip done: packets_seen=4395028 +resumed weights from checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt (recorded step=4868000, legacy_surface_migrated=False, span_head_migrated=False) +atomizer pack_mode=linguistic max_span_bytes=1 +dynamics on load: energy_decay=0.3000006675720215 -> 0.3000006675720215 (repaired=False, bounds=(0.3, 0.95)) +MERGE gates: enable=False coherence_thr=0.450 energy_floor=0.080 +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*(α_MLP+payload_prod)) +payload_copy=False (train-time copy-bias branch) +last_atom_readout=True (byte-tick 2-gram + dentate) +last_atom_dropout=0.5 (train-only per-position zeroing of la_byte; 0=off/current) +field_hard_couple_scale=0 (OFF — hard path unchanged) +last_atom_scale=1.0 (1.0=off/current; hard-path la_byte *= S) +efference_every=10 (0=off) +free_run_aux_every=0 horizon=4 weight=1.0 (0=off) +optimizer groups: field/other lr=1.5e-05 (13 tensors), surface lr=3.6e-05 (27 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 2 shard(s), chunk_bytes=65536, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LR param groups differ from checkpoint +step=4868001 (run 1/8000) loss=5.61222 byte_ppl=273.356 atoms=1 merges=0 field=0.0371 rms=0.0015 scale=1.0000 fcos=nan ign=0.0000 prn=nan nxp=0.000 mph=0.000 bytes=4395028 pkts=4395028 shard=0 +step=4868025 (run 25/8000) loss=0.00137 byte_ppl=1.001 atoms=27 merges=0 field=0.4856 rms=0.0152 scale=1.0000 fcos=nan ign=0.0000 prn=nan nxp=0.000 mph=0.000 bytes=4395028 pkts=4395028 shard=0 +step=4868050 (run 50/8000) loss=0.00089 byte_ppl=1.000 atoms=55 merges=0 field=0.9154 rms=0.0286 scale=1.0000 fcos=nan ign=0.0000 prn=nan nxp=0.000 mph=0.000 bytes=4395028 pkts=4395028 shard=0 +step=4868075 (run 75/8000) loss=0.00549 byte_ppl=1.005 atoms=12 merges=0 field=1.3038 rms=0.0408 scale=1.0000 fcos=nan ign=0.0000 prn=nan nxp=0.000 mph=0.000 bytes=4395028 pkts=4395028 shard=0 +step=4868100 (run 100/8000) loss=2.26823 byte_ppl=9.651 atoms=40 merges=0 field=1.5776 rms=0.0493 scale=1.0000 fcos=nan ign=0.0000 prn=nan nxp=0.000 mph=0.000 bytes=4395028 pkts=4395028 shard=0 +step=4868125 (run 125/8000) loss=4.96310 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20, + "bytes_hex": "3a3a3a3a3a3a3a3a", + "text": "::::::::", + "reload_text": "::::::::", + "reload_match": true + } + } +} diff --git a/docs/artifacts/last_atom_dropout/train_live_4868000_4876000.log b/docs/artifacts/last_atom_dropout/train_live_4868000_4876000.log new file mode 100644 index 0000000000000000000000000000000000000000..415a69e95f63afd131ddfdd5e452498d06b585fe --- /dev/null +++ b/docs/artifacts/last_atom_dropout/train_live_4868000_4876000.log @@ -0,0 +1,504 @@ +train lock skipped (--allow-parallel-train) +stream skip: advancing 4372000 packet transitions... +stream skip done: packets_seen=4395028 +resumed weights from checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt (recorded step=4868000, legacy_surface_migrated=False, span_head_migrated=False) +atomizer pack_mode=linguistic max_span_bytes=1 +dynamics on load: energy_decay=0.3000006675720215 -> 0.3000006675720215 (repaired=False, bounds=(0.3, 0.95)) +MERGE gates: enable=False coherence_thr=0.450 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3.3987816316075623, + "n": 256 + } + } + } + } + } +} \ No newline at end of file diff --git a/docs/artifacts/last_atom_dropout/val_ablation.txt b/docs/artifacts/last_atom_dropout/val_ablation.txt new file mode 100644 index 0000000000000000000000000000000000000000..464943d08299902d990cf9bbc694b11965d818f9 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/val_ablation.txt @@ -0,0 +1,19 @@ +val rings built for [4868000, 4876000] in 473.1s +[ring@4868000] checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt + normal loss=0.4010 byte_ce=0.3990 + la_zero loss=6.1219 byte_ce=6.1199 +[ring@4868000] checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt + normal loss=0.4024 byte_ce=0.4003 + la_zero loss=6.1970 byte_ce=6.1949 +[ring@4868000] checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt + normal loss=0.5363 byte_ce=0.5309 + la_zero loss=3.4042 byte_ce=3.3988 +[ring@4876000] checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt + normal loss=0.4010 byte_ce=0.3990 + la_zero loss=6.1219 byte_ce=6.1199 +[ring@4876000] checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt + normal loss=0.4024 byte_ce=0.4003 + la_zero loss=6.1970 byte_ce=6.1949 +[ring@4876000] checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt + normal loss=0.5363 byte_ce=0.5309 + la_zero loss=3.4042 byte_ce=3.3988 diff --git a/docs/artifacts/last_atom_dropout/val_window_baselines.json b/docs/artifacts/last_atom_dropout/val_window_baselines.json new file mode 100644 index 0000000000000000000000000000000000000000..67f6d186222b25bd73003b48c0e273cbbc566535 --- /dev/null +++ b/docs/artifacts/last_atom_dropout/val_window_baselines.json @@ -0,0 +1,7 @@ +{ + "val_window_text": ": Je vais bien, merci. Et toi ?\nUtilisateur: Dis-m'en plus.\nAssistant: Oui, tout à fait.\nUtilisateur: Dis-m'en plus.\nAssistant: Bonne question, je vais réfléchir.\n\nUtilisateur: Merci bien\nAssistant: Avec grand plaisir.\nUtilisateur: Dis-m'en plus.\nAssista", + "n_targets": 256, + "unigram_ce_corpus": 3.2359449769619477, + "bigram_ce_corpus_add0.01": 1.7686215704800623, + "uniform_ce": 5.545177444479562 +} \ No newline at end of file diff --git a/docs/artifacts/last_atom_dropout/yield_to_live.py b/docs/artifacts/last_atom_dropout/yield_to_live.py new file mode 100644 index 0000000000000000000000000000000000000000..b3f32528f230cc898f6360e7647dfd7fee9a32af --- /dev/null +++ b/docs/artifacts/last_atom_dropout/yield_to_live.py @@ -0,0 +1,72 @@ +"""Pause (SIGSTOP) MY probe PIDs while the live b4828 loop is in a multi-threaded phase. + +Live torch uses 8 spinning OMP threads; any other busy process on a core cuts live +throughput ~38x (measured 77 -> 2 steps/s). The live stream-skip phase is +single-threaded, so my single-threaded probe runs only then. Only signals the PIDs +listed in the pid file (my own processes). Never touches the live loop. +""" +import glob, os, signal, sys, time, subprocess +PIDFILE = sys.argv[1] +LOG = "/workspace/exports/atom-ai/logs/ladrop_yield.log" +ROOT = "/workspace/exports/atom-ai/logs" + +def my_pids(): + try: + return [int(x) for x in open(PIDFILE).read().split() if x.strip()] + except FileNotFoundError: + return [] + +def alive(pg): + # pg is a process-group id (setsid leader); alive if any member exists + try: + os.killpg(pg, 0) + return True + except Exception: + return False + +def live_busy(): + mine = set(my_pids()) + out = subprocess.run(["ps", "-eo", "pid,args"], capture_output=True, text=True).stdout + for line in out.splitlines()[1:]: + pid_s, _, args = line.strip().partition(" ") + pid = int(pid_s) + try: + if os.getpgid(pid) in mine: + continue + except Exception: + continue + if "ladrop" in args: + continue + if "chat_atom_native.py" in args and "lrd_b4828.pt" in args: + return True + if "run_atom_native.py" in args and "lrd_b4828.pt" in args: + logs = [l for l in glob.glob(f"{ROOT}/train_d32_*_ms1M_lrd_b4828.log")] + if not logs: + return True + cur = max(logs, key=os.path.getmtime) + txt = open(cur, errors="replace").read() + if "stream skip done" in txt: + return True # training / val / generation phase + return False # still skipping (single-threaded) + return False + +state = None +while True: + pids = [p for p in my_pids() if alive(p)] + if not pids: + break + busy = live_busy() + want = "STOP" if busy else "CONT" + for p in pids: + try: + os.killpg(p, signal.SIGSTOP if busy else signal.SIGCONT) + except ProcessLookupError: + pass + if want != state: + with open(LOG, "a") as f: + f.write(f"{time.strftime('%H:%M:%S')} {want} pids={pids}\n") + state = want + time.sleep(0.5) +for p in my_pids(): + try: os.killpg(p, signal.SIGCONT) + except Exception: pass diff --git a/docs/artifacts/lign_ablate_2k5/lign_probe_after.txt b/docs/artifacts/lign_ablate_2k5/lign_probe_after.txt new file mode 100644 index 0000000000000000000000000000000000000000..4e31717a6a0294c1e16396ced0ef2373275cb13a --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/lign_probe_after.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_ablate/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2105000 +[probe] prompt='Bonjour' + RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006797 -> 0.034313 (norm 0.4350 -> 2.1960) atoms 7 -> 26 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006037 -> 0.033744 (norm 0.3864 -> 2.1596) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.991780 alpha=0.698509 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_ablate_2k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_ablate_2k5/lign_probe_before.txt b/docs/artifacts/lign_ablate_2k5/lign_probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..ab54fa3e0172c8769abacbb69bfcb28e7f6bef9c --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/lign_probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006797 -> 0.034313 (norm 0.4350 -> 2.1960) atoms 7 -> 26 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006037 -> 0.033744 (norm 0.3864 -> 2.1596) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.991780 alpha=0.698509 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_ablate_2k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_ablate_2k5/probe_after_report.json b/docs/artifacts/lign_ablate_2k5/probe_after_report.json new file mode 100644 index 0000000000000000000000000000000000000000..c30cb10fdaeffb0c777319467ecc349c0a1ee831 --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/probe_after_report.json @@ -0,0 +1,447 @@ +{ + "timestamp_local": "2026-09-17 19:11:52 PDT", + "timestamp_utc": "2026-09-18T02:11:52.830435+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 16, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "enable_merge": true, + "slow_every": 4, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_contrast_margin": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": true, + "field_ignorance_prompt_bank": false, + "merge_count_total": 0 + }, + "training_meta": { + "step": 2105000, + "run_steps": 2500, + "seed": 20260917, + "episode_reset": false, + "atom_flush_every": 256, + "dynamics_on_load": { + "coupling_scale": 1.9906045198440552, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9987071752548218, + "energy_decay_before": 0.44999998807907104, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_ablate/atom_native.pt", + "checkpoint_bytes": 20532464 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0038661202415823936, + "field_norm": 0.247431680560112, + "field_mean_abs": 0.0029331459663808346, + "field_max_abs": 0.024348242208361626, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.032615795731544495, + "field_norm": 2.0874109268188477, + "field_mean_abs": 0.0234804917126894, + "field_max_abs": 0.14776422083377838, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 264.658935546875 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 7, + "packet_payloads": [ + "Utilisateur:", + " Qui ", + "es-", + "tu ", + "?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.006796767003834248, + "field_norm": 0.43499308824539185, + "field_mean_abs": 0.005092245060950518, + "field_max_abs": 0.0342055968940258, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 7, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.06999999284744263 + }, + "stats_after_gen": { + "field_rms": 0.03431277722120285, + "field_norm": 2.1960175037384033, + "field_mean_abs": 0.025360628962516785, + "field_max_abs": 0.15245617926120758, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 26, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2600000202655792 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 217.61972045898438 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 6, + "packet_payloads": [ + "Utilisateur:", + " Il ", + "\u00e9tait ", + "une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.006037322338670492, + "field_norm": 0.3863886296749115, + "field_mean_abs": 0.004503290634602308, + "field_max_abs": 0.03781157359480858, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 6, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.059999994933605194 + }, + "stats_after_gen": { + "field_rms": 0.033743564039468765, + "field_norm": 2.159588098526001, + "field_mean_abs": 0.024512071162462234, + "field_max_abs": 0.15108709037303925, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 25, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2500000298023224 + }, + "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 235.82313537597656 + }, + { + "prompt": "Utilisateur: Bonjour\nAssistant:", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0038661202415823936, + "field_norm": 0.247431680560112, + "field_mean_abs": 0.0029331459663808346, + "field_max_abs": 0.024348242208361626, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.032615795731544495, + "field_norm": 2.0874109268188477, + "field_mean_abs": 0.0234804917126894, + "field_max_abs": 0.14776422083377838, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 264.658935546875 + } + ], + "prompt_sensitivity": { + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "cosine_alpha": [ + [ + 0.9999999591503186, + 0.4765916552705683, + 0.8353639415455211, + 0.9999999591503186 + ], + [ + 0.4765916552705683, + 1.0000001375930643, + 0.5671435013560066, + 0.4765916552705683 + ], + [ + 0.8353639415455211, + 0.5671435013560066, + 1.0000001418181077, + 0.8353639415455211 + ], + [ + 0.9999999591503186, + 0.4765916552705683, + 0.8353639415455211, + 0.9999999591503186 + ] + ], + "cosine_output_state": [ + [ + 0.9999999505621286, + 0.9704693246384373, + 0.9899996836884695, + 0.9999999505621286 + ], + [ + 0.9704693246384373, + 0.9999999381350225, + 0.9767315391244513, + 0.9704693246384373 + ], + [ + 0.9899996836884695, + 0.9767315391244513, + 1.000000080813615, + 0.9899996836884695 + ], + [ + 0.9999999505621286, + 0.9704693246384373, + 0.9899996836884695, + 0.9999999505621286 + ] + ], + "cosine_surface_logits": [ + [ + 1.000000089773527, + 0.9856087639128152, + 0.9952362798386291, + 1.000000089773527 + ], + [ + 0.9856087639128152, + 1.0000001131637146, + 0.98899230137612, + 0.9856087639128152 + ], + [ + 0.9952362798386291, + 0.98899230137612, + 0.9999999569902737, + 0.9952362798386291 + ], + [ + 1.000000089773527, + 0.9856087639128152, + 0.9952362798386291, + 1.000000089773527 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.384511798620224, + 0.22536420822143555, + 0.0 + ], + [ + 0.384511798620224, + 0.0, + 0.3845365643501282, + 0.384511798620224 + ], + [ + 0.22536420822143555, + 0.3845365643501282, + 0.0, + 0.22536420822143555 + ], + [ + 0.0, + 0.384511798620224, + 0.22536420822143555, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.6985091090230839, + "mean_offdiag_cosine_output_state": 0.9829449177233989, + "mean_offdiag_cosine_surface_logits": 0.991780413108756, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.384511798620224, + 0.22536420822143555, + 0.0, + 0.3845365643501282, + 0.384511798620224, + 0.22536420822143555 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.2673814296722412, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 7.184626671374872e-09, + "baseline_mean_mse": 0.0012413040967658162, + "mse_improvement_vs_mean": 0.0012412969121391448, + "pred_target_cosine_per_prompt": [ + 1.0000000605084391, + 0.9999992448845294, + 0.9999996897767539, + 1.0000000605084391 + ], + "mean_pred_target_cosine": 0.9999997639195404, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000186264528, + "per_prompt": [ + 0.9999999999999988, + 1.000000074505813, + 1.0000000000000009, + 0.9999999999999988 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "mean_offdiag_cosine_surface_logits": 0.991780413108756, + "mean_offdiag_cosine_alpha": 0.6985091090230839, + "mean_field_rms_after_prompt": 0.005141582456417382, + "mean_field_rms_after_20_gen": 0.03332198318094015, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/lign_ablate_2k5/probe_before.txt b/docs/artifacts/lign_ablate_2k5/probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..ab54fa3e0172c8769abacbb69bfcb28e7f6bef9c --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdfrN\ufffdf su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/lign_ablate_2k5/series_row.json b/docs/artifacts/lign_ablate_2k5/series_row.json new file mode 100644 index 0000000000000000000000000000000000000000..225e1d101b1d07d840000d6e5ef37ec2de114b9d --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/series_row.json @@ -0,0 +1,12 @@ +{ + "name": "ablate", + "before_logits_cos": 0.992294, + "after_logits_cos": 0.991780, + "before_alpha_cos": 0.720524, + "after_alpha_cos": 0.698509, + "final_ign": 0.1500, + "final_mph": 0.500, + "merges_nonzero_log_lines": 0, + "checkpoint": "checkpoints/atom_native_lign_ablate/atom_native.pt", + "flags": ["--field-ignorance-ablate-shared", "--no-field-ignorance-prompt-bank"] +} diff --git a/docs/artifacts/lign_ablate_2k5/train_log.txt b/docs/artifacts/lign_ablate_2k5/train_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f8349c12a52bd0240c654cf2b95614f1dbfb2965 --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/train_log.txt @@ -0,0 +1,146 @@ +===== TRAIN ablate ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3147288) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500 +step=2102900 (run 400/2500) loss=2.37023 byte_ppl=2.444 atoms=144 merges=0 field=21.5615 rms=0.3369 scale=1.0000 fcos=0.076 ign=0.1462 mph=0.500 +step=2103100 (run 600/2500) loss=0.84953 byte_ppl=1.217 atoms=88 merges=0 field=38.1373 rms=0.5959 scale=1.0000 fcos=0.215 ign=0.1497 mph=0.500 +step=2103300 (run 800/2500) loss=4.14532 byte_ppl=5.120 atoms=32 merges=0 field=64.3113 rms=1.0049 scale=1.0000 fcos=0.234 ign=0.1498 mph=0.500 +step=2103500 (run 1000/2500) loss=10.31853 byte_ppl=92.074 atoms=232 merges=0 field=106.9234 rms=1.6707 scale=1.0000 fcos=0.254 ign=0.1499 mph=0.500 +step=2103700 (run 1200/2500) loss=6.81425 byte_ppl=76.736 atoms=176 merges=0 field=174.8289 rms=2.7317 scale=1.0000 fcos=0.151 ign=0.1499 mph=0.500 +step=2103900 (run 1400/2500) loss=4.61975 byte_ppl=18.999 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.183 ign=0.1499 mph=0.500 +step=2104100 (run 1600/2500) loss=6.30454 byte_ppl=51.807 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.187 ign=0.1500 mph=0.500 +step=2104300 (run 1800/2500) loss=5.01119 byte_ppl=18.008 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.290 ign=0.1500 mph=0.500 +step=2104500 (run 2000/2500) loss=6.39907 byte_ppl=19.718 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.277 ign=0.1500 mph=0.500 +step=2104700 (run 2200/2500) loss=6.85184 byte_ppl=13.419 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.235 ign=0.1500 mph=0.500 +step=2104900 (run 2400/2500) loss=8.30257 byte_ppl=124.561 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.275 ign=0.1500 mph=0.500 +step=2105000 (run 2500/2500) loss=6.33053 byte_ppl=20.570 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.300 ign=0.1500 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 2500, + "start_step": 2102500, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_ablate_shared": true, + "field_ignorance_prompt_bank": false, + "slow_every": 4 + }, + "train": { + "steps": 2500, + "start_step": 2102500, + "total_steps": 2105000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 44.848359566996805, + "transitions_per_second": 55.74339895900474, + "first_loss": 6.400629043579102, + "final_loss": 6.3305253982543945, + "final_total_perplexity": 561.4515020131753, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0074563026428223, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.997520387172699, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 1262, + "field_limited_fraction": 0.5048, + "final_dynamics": { + "coupling_scale": 1.9906045198440552, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9987071752548218, + "energy_decay_before": 0.4499995708465576, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 7, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 17.185137315401956, + "total_perplexity": 29067675.73906257, + "byte_loss": 6.6650525984309965, + "byte_perplexity": 784.5047276135747, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_lign_ablate/atom_native.pt", + "reload": { + "n_atoms": 196, + "field_norm": 191.9998779296875, + "time": 25.000476837158203, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c652c7121742d5671696e4eaa6a3c6576", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_ablate_2k5/train_log_excerpt.txt b/docs/artifacts/lign_ablate_2k5/train_log_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..38b1fcceed0d348554a4f624ee95e6ad59e69b50 --- /dev/null +++ b/docs/artifacts/lign_ablate_2k5/train_log_excerpt.txt @@ -0,0 +1,57 @@ +# train log excerpt — ablate + +===== TRAIN ablate ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3147288) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500 +... +3:resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +7:step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +8:step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500 +9:step=2102900 (run 400/2500) loss=2.37023 byte_ppl=2.444 atoms=144 merges=0 field=21.5615 rms=0.3369 scale=1.0000 fcos=0.076 ign=0.1462 mph=0.500 +10:step=2103100 (run 600/2500) loss=0.84953 byte_ppl=1.217 atoms=88 merges=0 field=38.1373 rms=0.5959 scale=1.0000 fcos=0.215 ign=0.1497 mph=0.500 +11:step=2103300 (run 800/2500) loss=4.14532 byte_ppl=5.120 atoms=32 merges=0 field=64.3113 rms=1.0049 scale=1.0000 fcos=0.234 ign=0.1498 mph=0.500 +12:step=2103500 (run 1000/2500) loss=10.31853 byte_ppl=92.074 atoms=232 merges=0 field=106.9234 rms=1.6707 scale=1.0000 fcos=0.254 ign=0.1499 mph=0.500 +13:step=2103700 (run 1200/2500) loss=6.81425 byte_ppl=76.736 atoms=176 merges=0 field=174.8289 rms=2.7317 scale=1.0000 fcos=0.151 ign=0.1499 mph=0.500 +14:step=2103900 (run 1400/2500) loss=4.61975 byte_ppl=18.999 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.183 ign=0.1499 mph=0.500 +15:step=2104100 (run 1600/2500) loss=6.30454 byte_ppl=51.807 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.187 ign=0.1500 mph=0.500 +16:step=2104300 (run 1800/2500) loss=5.01119 byte_ppl=18.008 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.290 ign=0.1500 mph=0.500 +17:step=2104500 (run 2000/2500) loss=6.39907 byte_ppl=19.718 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.277 ign=0.1500 mph=0.500 +18:step=2104700 (run 2200/2500) loss=6.85184 byte_ppl=13.419 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.235 ign=0.1500 mph=0.500 +19:step=2104900 (run 2400/2500) loss=8.30257 byte_ppl=124.561 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.275 ign=0.1500 mph=0.500 +20:step=2105000 (run 2500/2500) loss=6.33053 byte_ppl=20.570 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.300 ign=0.1500 mph=0.500 +... + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c652c7121742d5671696e4eaa6a3c6576", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_both_2k5/lign_probe_after.txt b/docs/artifacts/lign_both_2k5/lign_probe_after.txt new file mode 100644 index 0000000000000000000000000000000000000000..1e2c62091dafc20009fcbf54b9c077a6b2b4e3d4 --- /dev/null +++ b/docs/artifacts/lign_both_2k5/lign_probe_after.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_both/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2105000 +[probe] prompt='Bonjour' + RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006798 -> 0.034249 (norm 0.4351 -> 2.1919) atoms 7 -> 26 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006038 -> 0.033752 (norm 0.3864 -> 2.1602) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.992358 alpha=0.698481 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_both_2k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_both_2k5/lign_probe_before.txt b/docs/artifacts/lign_both_2k5/lign_probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..b210178e55485a6f8af8b8779841cad35003d25c --- /dev/null +++ b/docs/artifacts/lign_both_2k5/lign_probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006798 -> 0.034249 (norm 0.4351 -> 2.1919) atoms 7 -> 26 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006038 -> 0.033752 (norm 0.3864 -> 2.1602) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.992358 alpha=0.698481 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_both_2k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_both_2k5/probe_after_report.json b/docs/artifacts/lign_both_2k5/probe_after_report.json new file mode 100644 index 0000000000000000000000000000000000000000..672bb6068246e001c248b7e2ac52d9535bedfd23 --- /dev/null +++ b/docs/artifacts/lign_both_2k5/probe_after_report.json @@ -0,0 +1,447 @@ +{ + "timestamp_local": "2026-09-17 19:13:57 PDT", + "timestamp_utc": "2026-09-18T02:13:57.778386+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 16, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "enable_merge": true, + "slow_every": 4, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_contrast_margin": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": true, + "field_ignorance_prompt_bank": true, + "merge_count_total": 0 + }, + "training_meta": { + "step": 2105000, + "run_steps": 2500, + "seed": 20260917, + "episode_reset": false, + "atom_flush_every": 256, + "dynamics_on_load": { + "coupling_scale": 1.9910084009170532, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9985595941543579, + "energy_decay_before": 0.44999998807907104, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_both/atom_native.pt", + "checkpoint_bytes": 20532464 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0038667896296828985, + "field_norm": 0.2474745512008667, + "field_mean_abs": 0.002933506853878498, + "field_max_abs": 0.02435270883142948, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.032398514449596405, + "field_norm": 2.07350492477417, + "field_mean_abs": 0.023319242522120476, + "field_max_abs": 0.14671093225479126, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 277.39556884765625 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 7, + "packet_payloads": [ + "Utilisateur:", + " Qui ", + "es-", + "tu ", + "?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.006798470858484507, + "field_norm": 0.43510210514068604, + "field_mean_abs": 0.005093753337860107, + "field_max_abs": 0.03420306369662285, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 7, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.06999999284744263 + }, + "stats_after_gen": { + "field_rms": 0.03424892947077751, + "field_norm": 2.1919312477111816, + "field_mean_abs": 0.02527393214404583, + "field_max_abs": 0.1521221101284027, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 26, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2600000202655792 + }, + "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 224.024658203125 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 6, + "packet_payloads": [ + "Utilisateur:", + " Il ", + "\u00e9tait ", + "une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.006037530023604631, + "field_norm": 0.3864019513130188, + "field_mean_abs": 0.004503221251070499, + "field_max_abs": 0.03779352456331253, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 6, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.059999994933605194 + }, + "stats_after_gen": { + "field_rms": 0.033752478659152985, + "field_norm": 2.160158634185791, + "field_mean_abs": 0.024521082639694214, + "field_max_abs": 0.15114596486091614, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 25, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2500000298023224 + }, + "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 247.80909729003906 + }, + { + "prompt": "Utilisateur: Bonjour\nAssistant:", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0038667896296828985, + "field_norm": 0.2474745512008667, + "field_mean_abs": 0.002933506853878498, + "field_max_abs": 0.02435270883142948, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.032398514449596405, + "field_norm": 2.07350492477417, + "field_mean_abs": 0.023319242522120476, + "field_max_abs": 0.14671093225479126, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 277.39556884765625 + } + ], + "prompt_sensitivity": { + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "cosine_alpha": [ + [ + 0.9999999968217755, + 0.4764792049119334, + 0.8354733430631697, + 0.9999999968217755 + ], + [ + 0.4764792049119334, + 1.000000167715084, + 0.5669796813780352, + 0.4764792049119334 + ], + [ + 0.8354733430631697, + 0.5669796813780352, + 0.9999997550955949, + 0.8354733430631697 + ], + [ + 0.9999999968217755, + 0.4764792049119334, + 0.8354733430631697, + 0.9999999968217755 + ] + ], + "cosine_output_state": [ + [ + 1.0000001201656668, + 0.970649331773234, + 0.9900165471385234, + 1.0000001201656668 + ], + [ + 0.970649331773234, + 0.999999947744685, + 0.9767877563333452, + 0.970649331773234 + ], + [ + 0.9900165471385234, + 0.9767877563333452, + 0.9999999134828831, + 0.9900165471385234 + ], + [ + 1.0000001201656668, + 0.970649331773234, + 0.9900165471385234, + 1.0000001201656668 + ] + ], + "cosine_surface_logits": [ + [ + 1.0000002645084607, + 0.9868905506754033, + 0.9955139524229406, + 1.0000002645084607 + ], + [ + 0.9868905506754033, + 1.0000000457084584, + 0.9893375376062745, + 0.9868905506754033 + ], + [ + 0.9955139524229406, + 0.9893375376062745, + 0.9999999218617306, + 0.9955139524229406 + ], + [ + 1.0000002645084607, + 0.9868905506754033, + 0.9955139524229406, + 1.0000002645084607 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.38463765382766724, + 0.22531399130821228, + 0.0 + ], + [ + 0.38463765382766724, + 0.0, + 0.38467419147491455, + 0.38463765382766724 + ], + [ + 0.22531399130821228, + 0.38467419147491455, + 0.0, + 0.22531399130821228 + ], + [ + 0.0, + 0.38463765382766724, + 0.22531399130821228, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.6984807956916694, + "mean_offdiag_cosine_output_state": 0.9830199390537544, + "mean_offdiag_cosine_surface_logits": 0.9923578013852371, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.38463765382766724, + 0.22531399130821228, + 0.0, + 0.38467419147491455, + 0.38463765382766724, + 0.22531399130821228 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.26742958029111225, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 7.22156645593941e-09, + "baseline_mean_mse": 0.0012413040967658162, + "mse_improvement_vs_mean": 0.0012412968751993603, + "pred_target_cosine_per_prompt": [ + 0.999999935346222, + 0.9999992268162038, + 0.9999996283491076, + 0.999999935346222 + ], + "mean_pred_target_cosine": 0.9999996814644388, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 0.9999999838570781, + "per_prompt": [ + 0.9999999602635737, + 0.9999999701976776, + 1.0000000447034871, + 0.9999999602635737 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "mean_offdiag_cosine_surface_logits": 0.9923578013852371, + "mean_offdiag_cosine_alpha": 0.6984807956916694, + "mean_field_rms_after_prompt": 0.005142395035363734, + "mean_field_rms_after_20_gen": 0.03319960925728083, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/lign_both_2k5/probe_before.txt b/docs/artifacts/lign_both_2k5/probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..b210178e55485a6f8af8b8779841cad35003d25c --- /dev/null +++ b/docs/artifacts/lign_both_2k5/probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdfrN\ufffdf su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/lign_both_2k5/series_row.json b/docs/artifacts/lign_both_2k5/series_row.json new file mode 100644 index 0000000000000000000000000000000000000000..da585cdf70cdc9037a1095a38aa417295dec723f --- /dev/null +++ b/docs/artifacts/lign_both_2k5/series_row.json @@ -0,0 +1,12 @@ +{ + "name": "both", + "before_logits_cos": 0.992294, + "after_logits_cos": 0.992358, + "before_alpha_cos": 0.720524, + "after_alpha_cos": 0.698481, + "final_ign": 0.0000, + "final_mph": 0.500, + "merges_nonzero_log_lines": 0, + "checkpoint": "checkpoints/atom_native_lign_both/atom_native.pt", + "flags": ["--field-ignorance-ablate-shared", "--field-ignorance-prompt-bank"] +} diff --git a/docs/artifacts/lign_both_2k5/train_log.txt b/docs/artifacts/lign_both_2k5/train_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..3ecd7cdb382076e3c572a036cf54119d3a17d1a5 --- /dev/null +++ b/docs/artifacts/lign_both_2k5/train_log.txt @@ -0,0 +1,146 @@ +===== TRAIN both ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3168090) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500 +step=2102900 (run 400/2500) loss=2.36884 byte_ppl=2.444 atoms=144 merges=0 field=21.5616 rms=0.3369 scale=1.0000 fcos=0.119 ign=0.1265 mph=0.500 +step=2103100 (run 600/2500) loss=0.84731 byte_ppl=1.223 atoms=88 merges=0 field=38.1377 rms=0.5959 scale=1.0000 fcos=0.325 ign=0.0591 mph=0.500 +step=2103300 (run 800/2500) loss=4.13253 byte_ppl=5.113 atoms=32 merges=0 field=64.3126 rms=1.0049 scale=1.0000 fcos=0.368 ign=0.0000 mph=0.500 +step=2103500 (run 1000/2500) loss=10.28781 byte_ppl=90.063 atoms=232 merges=0 field=106.9277 rms=1.6707 scale=1.0000 fcos=0.390 ign=0.0000 mph=0.500 +step=2103700 (run 1200/2500) loss=6.81054 byte_ppl=77.353 atoms=176 merges=0 field=174.8396 rms=2.7319 scale=1.0000 fcos=0.295 ign=0.0000 mph=0.500 +step=2103900 (run 1400/2500) loss=4.60311 byte_ppl=18.904 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.334 ign=0.0000 mph=0.500 +step=2104100 (run 1600/2500) loss=6.28093 byte_ppl=51.199 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.305 ign=0.0000 mph=0.500 +step=2104300 (run 1800/2500) loss=5.00042 byte_ppl=18.019 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.268 ign=0.0022 mph=0.500 +step=2104500 (run 2000/2500) loss=6.38675 byte_ppl=19.710 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.267 ign=0.0000 mph=0.500 +step=2104700 (run 2200/2500) loss=6.83892 byte_ppl=13.414 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.297 ign=0.0000 mph=0.500 +step=2104900 (run 2400/2500) loss=8.30884 byte_ppl=126.876 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.319 ign=0.0000 mph=0.500 +step=2105000 (run 2500/2500) loss=6.31794 byte_ppl=20.556 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.243 ign=0.0000 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 2500, + "start_step": 2102500, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_ablate_shared": true, + "field_ignorance_prompt_bank": true, + "slow_every": 4 + }, + "train": { + "steps": 2500, + "start_step": 2102500, + "total_steps": 2105000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 44.728401276050135, + "transitions_per_second": 55.89289866567682, + "first_loss": 6.400629043579102, + "final_loss": 6.317938327789307, + "final_total_perplexity": 554.4287629702109, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0074567794799805, + "field_rms_after_max": 2.999999761581421, + "field_scale_min": 0.9975202679634094, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 1262, + "field_limited_fraction": 0.5048, + "final_dynamics": { + "coupling_scale": 1.9910084009170532, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9985595941543579, + "energy_decay_before": 0.4499995708465576, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 7, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 17.255518042852007, + "total_perplexity": 31187191.600063678, + "byte_loss": 6.73190822203954, + "byte_perplexity": 838.7462539442383, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_lign_both/atom_native.pt", + "reload": { + "n_atoms": 196, + "field_norm": 191.99989318847656, + "time": 25.000476837158203, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69762c662c7121742d5671696e4e6966726969", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_both_2k5/train_log_excerpt.txt b/docs/artifacts/lign_both_2k5/train_log_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..67d8bb54ffcbebbbd29f4f2476a51d2756db1c98 --- /dev/null +++ b/docs/artifacts/lign_both_2k5/train_log_excerpt.txt @@ -0,0 +1,57 @@ +# train log excerpt — both + +===== TRAIN both ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3168090) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500 +... +3:resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +7:step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +8:step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500 +9:step=2102900 (run 400/2500) loss=2.36884 byte_ppl=2.444 atoms=144 merges=0 field=21.5616 rms=0.3369 scale=1.0000 fcos=0.119 ign=0.1265 mph=0.500 +10:step=2103100 (run 600/2500) loss=0.84731 byte_ppl=1.223 atoms=88 merges=0 field=38.1377 rms=0.5959 scale=1.0000 fcos=0.325 ign=0.0591 mph=0.500 +11:step=2103300 (run 800/2500) loss=4.13253 byte_ppl=5.113 atoms=32 merges=0 field=64.3126 rms=1.0049 scale=1.0000 fcos=0.368 ign=0.0000 mph=0.500 +12:step=2103500 (run 1000/2500) loss=10.28781 byte_ppl=90.063 atoms=232 merges=0 field=106.9277 rms=1.6707 scale=1.0000 fcos=0.390 ign=0.0000 mph=0.500 +13:step=2103700 (run 1200/2500) loss=6.81054 byte_ppl=77.353 atoms=176 merges=0 field=174.8396 rms=2.7319 scale=1.0000 fcos=0.295 ign=0.0000 mph=0.500 +14:step=2103900 (run 1400/2500) loss=4.60311 byte_ppl=18.904 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.334 ign=0.0000 mph=0.500 +15:step=2104100 (run 1600/2500) loss=6.28093 byte_ppl=51.199 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.305 ign=0.0000 mph=0.500 +16:step=2104300 (run 1800/2500) loss=5.00042 byte_ppl=18.019 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.268 ign=0.0022 mph=0.500 +17:step=2104500 (run 2000/2500) loss=6.38675 byte_ppl=19.710 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.267 ign=0.0000 mph=0.500 +18:step=2104700 (run 2200/2500) loss=6.83892 byte_ppl=13.414 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.297 ign=0.0000 mph=0.500 +19:step=2104900 (run 2400/2500) loss=8.30884 byte_ppl=126.876 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.319 ign=0.0000 mph=0.500 +20:step=2105000 (run 2500/2500) loss=6.31794 byte_ppl=20.556 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.243 ign=0.0000 mph=0.500 +... + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69762c662c7121742d5671696e4e6966726969", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_prompt_bank_2k5/lign_probe_after.txt b/docs/artifacts/lign_prompt_bank_2k5/lign_probe_after.txt new file mode 100644 index 0000000000000000000000000000000000000000..c5e2bd38caa7e5283f1a61c6d8eb6fa48a1fd619 --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/lign_probe_after.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_prompt_bank/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2105000 +[probe] prompt='Bonjour' + RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006797 -> 0.034235 (norm 0.4350 -> 2.1911) atoms 7 -> 26 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006036 -> 0.033740 (norm 0.3863 -> 2.1594) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.991156 alpha=0.698703 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_prompt_bank_2k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_prompt_bank_2k5/lign_probe_before.txt b/docs/artifacts/lign_prompt_bank_2k5/lign_probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..cb3feb6fb2c1d0903bc5412a1bcd598a4b26bfc3 --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/lign_probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006797 -> 0.034235 (norm 0.4350 -> 2.1911) atoms 7 -> 26 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006036 -> 0.033740 (norm 0.3863 -> 2.1594) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.991156 alpha=0.698703 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_prompt_bank_2k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_prompt_bank_2k5/probe_after_report.json b/docs/artifacts/lign_prompt_bank_2k5/probe_after_report.json new file mode 100644 index 0000000000000000000000000000000000000000..cb976391d6c10ab2a9e85148172c4e4b9ae2809a --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/probe_after_report.json @@ -0,0 +1,447 @@ +{ + "timestamp_local": "2026-09-17 19:12:56 PDT", + "timestamp_utc": "2026-09-18T02:12:56.419178+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 16, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "enable_merge": true, + "slow_every": 4, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_contrast_margin": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": true, + "merge_count_total": 0 + }, + "training_meta": { + "step": 2105000, + "run_steps": 2500, + "seed": 20260917, + "episode_reset": false, + "atom_flush_every": 256, + "dynamics_on_load": { + "coupling_scale": 1.9906097650527954, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9987052083015442, + "energy_decay_before": 0.44999998807907104, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_prompt_bank/atom_native.pt", + "checkpoint_bytes": 20532464 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.003865806618705392, + "field_norm": 0.24741162359714508, + "field_mean_abs": 0.0029328055679798126, + "field_max_abs": 0.024350089952349663, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.032612450420856476, + "field_norm": 2.0871970653533936, + "field_mean_abs": 0.023477904498577118, + "field_max_abs": 0.14776554703712463, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 221.82965087890625 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 7, + "packet_payloads": [ + "Utilisateur:", + " Qui ", + "es-", + "tu ", + "?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0067970287054777145, + "field_norm": 0.43500980734825134, + "field_mean_abs": 0.005090977996587753, + "field_max_abs": 0.03416934609413147, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 7, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.06999999284744263 + }, + "stats_after_gen": { + "field_rms": 0.03423523157835007, + "field_norm": 2.1910552978515625, + "field_mean_abs": 0.02526124194264412, + "field_max_abs": 0.15207387506961823, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 26, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2600000202655792 + }, + "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 189.15171813964844 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 6, + "packet_payloads": [ + "Utilisateur:", + " Il ", + "\u00e9tait ", + "une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.00603602034971118, + "field_norm": 0.3863053023815155, + "field_mean_abs": 0.004502155352383852, + "field_max_abs": 0.037809669971466064, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 6, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.059999994933605194 + }, + "stats_after_gen": { + "field_rms": 0.033740267157554626, + "field_norm": 2.159377336502075, + "field_mean_abs": 0.024509785696864128, + "field_max_abs": 0.151095449924469, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 25, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2500000298023224 + }, + "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 197.5469207763672 + }, + { + "prompt": "Utilisateur: Bonjour\nAssistant:", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.003865806618705392, + "field_norm": 0.24741162359714508, + "field_mean_abs": 0.0029328055679798126, + "field_max_abs": 0.024350089952349663, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.032612450420856476, + "field_norm": 2.0871970653533936, + "field_mean_abs": 0.023477904498577118, + "field_max_abs": 0.14776554703712463, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>", + "generated_bytes": 80, + "surface_byte_logits_norm": 221.82965087890625 + } + ], + "prompt_sensitivity": { + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "cosine_alpha": [ + [ + 0.9999999126692176, + 0.4770204767289738, + 0.8353735615402859, + 0.9999999126692176 + ], + [ + 0.4770204767289738, + 0.9999999688127341, + 0.5674274534930072, + 0.4770204767289738 + ], + [ + 0.8353735615402859, + 0.5674274534930072, + 0.9999999326352736, + 0.8353735615402859 + ], + [ + 0.9999999126692176, + 0.4770204767289738, + 0.8353735615402859, + 0.9999999126692176 + ] + ], + "cosine_output_state": [ + [ + 1.0000000114730727, + 0.9704771401012563, + 0.9900029352492485, + 1.0000000114730727 + ], + [ + 0.9704771401012563, + 0.9999998538000267, + 0.9767207011712129, + 0.9704771401012563 + ], + [ + 0.9900029352492485, + 0.9767207011712129, + 0.9999999042680695, + 0.9900029352492485 + ], + [ + 1.0000000114730727, + 0.9704771401012563, + 0.9900029352492485, + 1.0000000114730727 + ] + ], + "cosine_surface_logits": [ + [ + 0.999999956310069, + 0.9842647262611598, + 0.9955123977058938, + 0.999999956310069 + ], + [ + 0.9842647262611598, + 1.0000000727444798, + 0.9873824478682708, + 0.9842647262611598 + ], + [ + 0.9955123977058938, + 0.9873824478682708, + 0.9999999914541752, + 0.9955123977058938 + ], + [ + 0.999999956310069, + 0.9842647262611598, + 0.9955123977058938, + 0.999999956310069 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.38440337777137756, + 0.22530032694339752, + 0.0 + ], + [ + 0.38440337777137756, + 0.0, + 0.38439151644706726, + 0.38440337777137756 + ], + [ + 0.22530032694339752, + 0.38439151644706726, + 0.0, + 0.22530032694339752 + ], + [ + 0.0, + 0.38440337777137756, + 0.22530032694339752, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.6987025737834575, + "mean_offdiag_cosine_output_state": 0.9829468105575492, + "mean_offdiag_cosine_surface_logits": 0.9911561086854078, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.38440337777137756, + 0.22530032694339752, + 0.0, + 0.38439151644706726, + 0.38440337777137756, + 0.22530032694339752 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.2672998209794362, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 7.179306926730078e-09, + "baseline_mean_mse": 0.0012413040967658162, + "mse_improvement_vs_mean": 0.0012412969174588895, + "pred_target_cosine_per_prompt": [ + 1.0000000765155859, + 0.9999991857830204, + 0.9999996927917011, + 1.0000000765155859 + ], + "mean_pred_target_cosine": 0.9999997579014733, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 1.000000014901162, + "per_prompt": [ + 0.9999999999999988, + 1.0000000447034871, + 1.0000000149011639, + 0.9999999999999988 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "mean_offdiag_cosine_surface_logits": 0.9911561086854078, + "mean_offdiag_cosine_alpha": 0.6987025737834575, + "mean_field_rms_after_prompt": 0.0051411655731499195, + "mean_field_rms_after_20_gen": 0.03330009989440441, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/lign_prompt_bank_2k5/probe_before.txt b/docs/artifacts/lign_prompt_bank_2k5/probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..cb3feb6fb2c1d0903bc5412a1bcd598a4b26bfc3 --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdfrN\ufffdf su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf =k> =k", + "reload_text": " =k> =k", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c6871666f2c2c72659174d8d720646b3e203d6b", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c712c652070753e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/lign_prompt_bank_2k5/series_row.json b/docs/artifacts/lign_prompt_bank_2k5/series_row.json new file mode 100644 index 0000000000000000000000000000000000000000..1856b5595e29f2a73181ea8ebec8a389c7469a87 --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/series_row.json @@ -0,0 +1,12 @@ +{ + "name": "prompt_bank", + "before_logits_cos": 0.992294, + "after_logits_cos": 0.991156, + "before_alpha_cos": 0.720524, + "after_alpha_cos": 0.698703, + "final_ign": 0.0000, + "final_mph": 0.500, + "merges_nonzero_log_lines": 0, + "checkpoint": "checkpoints/atom_native_lign_prompt_bank/atom_native.pt", + "flags": ["--no-field-ignorance-ablate-shared", "--field-ignorance-prompt-bank"] +} diff --git a/docs/artifacts/lign_prompt_bank_2k5/train_log.txt b/docs/artifacts/lign_prompt_bank_2k5/train_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..62f7b85812ba3af8b8af6f99a38a5565201fec15 --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/train_log.txt @@ -0,0 +1,146 @@ +===== TRAIN prompt_bank ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3157768) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.41256 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.1491 mph=0.000 +step=2102700 (run 200/2500) loss=12.29048 byte_ppl=40.383 atoms=200 merges=0 field=9.9247 rms=0.1551 scale=1.0000 fcos=0.206 ign=0.0000 mph=0.500 +step=2102900 (run 400/2500) loss=2.36072 byte_ppl=2.449 atoms=144 merges=0 field=21.5607 rms=0.3369 scale=1.0000 fcos=0.108 ign=0.0000 mph=0.500 +step=2103100 (run 600/2500) loss=0.83619 byte_ppl=1.214 atoms=88 merges=0 field=38.1396 rms=0.5959 scale=1.0000 fcos=0.161 ign=0.0000 mph=0.500 +step=2103300 (run 800/2500) loss=4.13730 byte_ppl=5.129 atoms=32 merges=0 field=64.3142 rms=1.0049 scale=1.0000 fcos=0.197 ign=0.0000 mph=0.500 +step=2103500 (run 1000/2500) loss=10.30387 byte_ppl=91.805 atoms=232 merges=0 field=106.9238 rms=1.6707 scale=1.0000 fcos=0.228 ign=0.0000 mph=0.500 +step=2103700 (run 1200/2500) loss=6.80633 byte_ppl=77.045 atoms=176 merges=0 field=174.8268 rms=2.7317 scale=1.0000 fcos=0.165 ign=0.0000 mph=0.500 +step=2103900 (run 1400/2500) loss=4.60745 byte_ppl=18.994 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.167 ign=0.0000 mph=0.500 +step=2104100 (run 1600/2500) loss=6.29213 byte_ppl=51.809 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.289 ign=0.0000 mph=0.500 +step=2104300 (run 1800/2500) loss=5.00036 byte_ppl=18.018 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.182 ign=0.0000 mph=0.500 +step=2104500 (run 2000/2500) loss=6.38649 byte_ppl=19.705 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.301 ign=0.0000 mph=0.500 +step=2104700 (run 2200/2500) loss=6.84005 byte_ppl=13.421 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.249 ign=0.0000 mph=0.500 +step=2104900 (run 2400/2500) loss=8.31378 byte_ppl=127.482 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.276 ign=0.0000 mph=0.500 +step=2105000 (run 2500/2500) loss=6.31765 byte_ppl=20.555 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.177 ign=0.0000 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 2500, + "start_step": 2102500, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": true, + "slow_every": 4 + }, + "train": { + "steps": 2500, + "start_step": 2102500, + "total_steps": 2105000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 46.47950343892444, + "transitions_per_second": 53.787149496661044, + "first_loss": 6.412557601928711, + "final_loss": 6.317653656005859, + "final_total_perplexity": 554.2709552082359, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0074565410614014, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9975203275680542, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 1262, + "field_limited_fraction": 0.5048, + "final_dynamics": { + "coupling_scale": 1.9906097650527954, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9987052083015442, + "energy_decay_before": 0.4499995708465576, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 7, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 17.186749573737856, + "total_perplexity": 29114578.140812457, + "byte_loss": 6.68167227412027, + "byte_perplexity": 797.6518899328228, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_lign_prompt_bank/atom_native.pt", + "reload": { + "n_atoms": 196, + "field_norm": 191.99989318847656, + "time": 25.000476837158203, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c652c712165203dc33e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c6871666f2c2c72659174d8d720646b3e203d6b", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c712c652070753e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_prompt_bank_2k5/train_log_excerpt.txt b/docs/artifacts/lign_prompt_bank_2k5/train_log_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..3db621c85baa47f23438ad2fb58117ee543010ff --- /dev/null +++ b/docs/artifacts/lign_prompt_bank_2k5/train_log_excerpt.txt @@ -0,0 +1,57 @@ +# train log excerpt — prompt_bank + +===== TRAIN prompt_bank ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3157768) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.41256 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.1491 mph=0.000 +step=2102700 (run 200/2500) loss=12.29048 byte_ppl=40.383 atoms=200 merges=0 field=9.9247 rms=0.1551 scale=1.0000 fcos=0.206 ign=0.0000 mph=0.500 +... +3:resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +7:step=2102501 (run 1/2500) loss=6.41256 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.1491 mph=0.000 +8:step=2102700 (run 200/2500) loss=12.29048 byte_ppl=40.383 atoms=200 merges=0 field=9.9247 rms=0.1551 scale=1.0000 fcos=0.206 ign=0.0000 mph=0.500 +9:step=2102900 (run 400/2500) loss=2.36072 byte_ppl=2.449 atoms=144 merges=0 field=21.5607 rms=0.3369 scale=1.0000 fcos=0.108 ign=0.0000 mph=0.500 +10:step=2103100 (run 600/2500) loss=0.83619 byte_ppl=1.214 atoms=88 merges=0 field=38.1396 rms=0.5959 scale=1.0000 fcos=0.161 ign=0.0000 mph=0.500 +11:step=2103300 (run 800/2500) loss=4.13730 byte_ppl=5.129 atoms=32 merges=0 field=64.3142 rms=1.0049 scale=1.0000 fcos=0.197 ign=0.0000 mph=0.500 +12:step=2103500 (run 1000/2500) loss=10.30387 byte_ppl=91.805 atoms=232 merges=0 field=106.9238 rms=1.6707 scale=1.0000 fcos=0.228 ign=0.0000 mph=0.500 +13:step=2103700 (run 1200/2500) loss=6.80633 byte_ppl=77.045 atoms=176 merges=0 field=174.8268 rms=2.7317 scale=1.0000 fcos=0.165 ign=0.0000 mph=0.500 +14:step=2103900 (run 1400/2500) loss=4.60745 byte_ppl=18.994 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.167 ign=0.0000 mph=0.500 +15:step=2104100 (run 1600/2500) loss=6.29213 byte_ppl=51.809 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.289 ign=0.0000 mph=0.500 +16:step=2104300 (run 1800/2500) loss=5.00036 byte_ppl=18.018 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.182 ign=0.0000 mph=0.500 +17:step=2104500 (run 2000/2500) loss=6.38649 byte_ppl=19.705 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.301 ign=0.0000 mph=0.500 +18:step=2104700 (run 2200/2500) loss=6.84005 byte_ppl=13.421 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.249 ign=0.0000 mph=0.500 +19:step=2104900 (run 2400/2500) loss=8.31378 byte_ppl=127.482 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.276 ign=0.0000 mph=0.500 +20:step=2105000 (run 2500/2500) loss=6.31765 byte_ppl=20.555 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.177 ign=0.0000 mph=0.500 +... + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c652c712165203dc33e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c6871666f2c2c72659174d8d720646b3e203d6b", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c712c652070753e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_readout_series/SUMMARY.md b/docs/artifacts/lign_readout_series/SUMMARY.md new file mode 100644 index 0000000000000000000000000000000000000000..82db7989ceca845c0502fd384faaa68ea15c0393 --- /dev/null +++ b/docs/artifacts/lign_readout_series/SUMMARY.md @@ -0,0 +1,34 @@ +# L_ign readout series — SUMMARY + +_Generated 2026-09-17 19:22 PDT. Same src @ step 2102500. Each arm +2500 steps. No fluency claim._ + +## Question + +Does fixing **how** ℓ(α) vs ℓ(α_bar) is formed drop inter-prompt **logits** cosine +below ~0.991 without killing **α** cosine (~0.70)? + +## Table + +| run | logits before | logits after | α before | α after | ign | mph | merges | +|-----|---------------|--------------|----------|---------|-----|-----|--------| +| baseline smoke | 0.992294 | **0.991285** | 0.720524 | 0.698694 | 0.150 | 0.500 | 0 | +| ablate-shared | 0.992294 | **0.991780** | 0.720524 | 0.698509 | 0.150 | 0.500 | 0 | +| prompt-bank | 0.992294 | **0.991156** | 0.720524 | 0.698703 | 0.000 | 0.500 | 0 | +| both | 0.992294 | **0.992358** | 0.720524 | 0.698481 | 0.000 | 0.500 | 0 | + +## Answer + +**No.** None of the three mechanism arms produced a meaningful logits drop vs ~0.991. +α stayed ~0.70 in all cases. + +Side finding: **prompt-bank** (and **both**) drive train `ign→0` — α_bar from distinct +prompts is far enough that the cosine hinge is inactive (no L_ign gradient). Ablate-only +still saturates at ign=0.150 (cos_ign≈1). + +## Artifacts + +- `docs/artifacts/lign_ablate_2k5/` +- `docs/artifacts/lign_prompt_bank_2k5/` +- `docs/artifacts/lign_both_2k5/` +- `docs/artifacts/lign_readout_series/series_log.txt` +- Docs: `LIGN_ABLATION.md`, `LIGN_PROMPT_BANK.md`, `LIGN_ABLATION_PLUS_BANK.md` diff --git a/docs/artifacts/lign_readout_series/series_log.txt b/docs/artifacts/lign_readout_series/series_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..facf1a514780a275bc096fd7333df54645b86252 --- /dev/null +++ b/docs/artifacts/lign_readout_series/series_log.txt @@ -0,0 +1,445 @@ +########## SERIES LOG — L_ign readout (ablate / prompt-bank / both) ########## + +########## EXPERIMENT 1 — ABLATE ONLY ########## +===== TRAIN ablate ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3147288) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500 +step=2102900 (run 400/2500) loss=2.37023 byte_ppl=2.444 atoms=144 merges=0 field=21.5615 rms=0.3369 scale=1.0000 fcos=0.076 ign=0.1462 mph=0.500 +step=2103100 (run 600/2500) loss=0.84953 byte_ppl=1.217 atoms=88 merges=0 field=38.1373 rms=0.5959 scale=1.0000 fcos=0.215 ign=0.1497 mph=0.500 +step=2103300 (run 800/2500) loss=4.14532 byte_ppl=5.120 atoms=32 merges=0 field=64.3113 rms=1.0049 scale=1.0000 fcos=0.234 ign=0.1498 mph=0.500 +step=2103500 (run 1000/2500) loss=10.31853 byte_ppl=92.074 atoms=232 merges=0 field=106.9234 rms=1.6707 scale=1.0000 fcos=0.254 ign=0.1499 mph=0.500 +step=2103700 (run 1200/2500) loss=6.81425 byte_ppl=76.736 atoms=176 merges=0 field=174.8289 rms=2.7317 scale=1.0000 fcos=0.151 ign=0.1499 mph=0.500 +step=2103900 (run 1400/2500) loss=4.61975 byte_ppl=18.999 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.183 ign=0.1499 mph=0.500 +step=2104100 (run 1600/2500) loss=6.30454 byte_ppl=51.807 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.187 ign=0.1500 mph=0.500 +step=2104300 (run 1800/2500) loss=5.01119 byte_ppl=18.008 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.290 ign=0.1500 mph=0.500 +step=2104500 (run 2000/2500) loss=6.39907 byte_ppl=19.718 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.277 ign=0.1500 mph=0.500 +step=2104700 (run 2200/2500) loss=6.85184 byte_ppl=13.419 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.235 ign=0.1500 mph=0.500 +step=2104900 (run 2400/2500) loss=8.30257 byte_ppl=124.561 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.275 ign=0.1500 mph=0.500 +step=2105000 (run 2500/2500) loss=6.33053 byte_ppl=20.570 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.300 ign=0.1500 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 2500, + "start_step": 2102500, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_ablate_shared": true, + "field_ignorance_prompt_bank": false, + "slow_every": 4 + }, + "train": { + "steps": 2500, + "start_step": 2102500, + "total_steps": 2105000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 44.848359566996805, + "transitions_per_second": 55.74339895900474, + "first_loss": 6.400629043579102, + "final_loss": 6.3305253982543945, + "final_total_perplexity": 561.4515020131753, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": 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+ "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c652c7121742d5671696e4eaa6a3c6576", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} + +########## EXPERIMENT 2 — DISTINCT PROMPT BANK ONLY ########## +===== TRAIN prompt_bank ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3157768) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); 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=k", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c6871666f2c2c72659174d8d720646b3e203d6b", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c712c652070753e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} + +########## EXPERIMENT 3 — BOTH COMBINED ########## +===== TRAIN both ===== +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3168090) +resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500 +step=2102900 (run 400/2500) loss=2.36884 byte_ppl=2.444 atoms=144 merges=0 field=21.5616 rms=0.3369 scale=1.0000 fcos=0.119 ign=0.1265 mph=0.500 +step=2103100 (run 600/2500) loss=0.84731 byte_ppl=1.223 atoms=88 merges=0 field=38.1377 rms=0.5959 scale=1.0000 fcos=0.325 ign=0.0591 mph=0.500 +step=2103300 (run 800/2500) loss=4.13253 byte_ppl=5.113 atoms=32 merges=0 field=64.3126 rms=1.0049 scale=1.0000 fcos=0.368 ign=0.0000 mph=0.500 +step=2103500 (run 1000/2500) loss=10.28781 byte_ppl=90.063 atoms=232 merges=0 field=106.9277 rms=1.6707 scale=1.0000 fcos=0.390 ign=0.0000 mph=0.500 +step=2103700 (run 1200/2500) loss=6.81054 byte_ppl=77.353 atoms=176 merges=0 field=174.8396 rms=2.7319 scale=1.0000 fcos=0.295 ign=0.0000 mph=0.500 +step=2103900 (run 1400/2500) loss=4.60311 byte_ppl=18.904 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.334 ign=0.0000 mph=0.500 +step=2104100 (run 1600/2500) loss=6.28093 byte_ppl=51.199 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.305 ign=0.0000 mph=0.500 +step=2104300 (run 1800/2500) loss=5.00042 byte_ppl=18.019 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.268 ign=0.0022 mph=0.500 +step=2104500 (run 2000/2500) loss=6.38675 byte_ppl=19.710 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.267 ign=0.0000 mph=0.500 +step=2104700 (run 2200/2500) loss=6.83892 byte_ppl=13.414 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.297 ign=0.0000 mph=0.500 +step=2104900 (run 2400/2500) loss=8.30884 byte_ppl=126.876 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.319 ign=0.0000 mph=0.500 +step=2105000 (run 2500/2500) loss=6.31794 byte_ppl=20.556 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.243 ign=0.0000 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 2500, + "start_step": 2102500, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.08, + "field_ignorance_ablate_shared": true, + "field_ignorance_prompt_bank": true, + "slow_every": 4 + }, + "train": { + "steps": 2500, + "start_step": 2102500, + "total_steps": 2105000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 44.728401276050135, + "transitions_per_second": 55.89289866567682, + "first_loss": 6.400629043579102, + "final_loss": 6.317938327789307, + "final_total_perplexity": 554.4287629702109, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0074567794799805, + "field_rms_after_max": 2.999999761581421, + "field_scale_min": 0.9975202679634094, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 1262, + "field_limited_fraction": 0.5048, + "final_dynamics": { + "coupling_scale": 1.9910084009170532, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9985595941543579, + "energy_decay_before": 0.4499995708465576, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 7, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 17.255518042852007, + "total_perplexity": 31187191.600063678, + "byte_loss": 6.73190822203954, + "byte_perplexity": 838.7462539442383, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_lign_both/atom_native.pt", + "reload": { + "n_atoms": 196, + "field_norm": 191.99989318847656, + "time": 25.000476837158203, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69762c662c7121742d5671696e4e6966726969", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_readout_series/src_probe_before.txt b/docs/artifacts/lign_readout_series/src_probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..d3ef22abaeb0489ae3e40c30c618758006e27b81 --- /dev/null +++ b/docs/artifacts/lign_readout_series/src_probe_before.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdfrN\ufffdf su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000 +step=2102700 (run 200/2500) loss=12.30308 byte_ppl=40.439 atoms=200 merges=0 field=9.9247 rms=0.1551 scale=1.0000 fcos=0.205 ign=0.1500 mph=0.500 +step=2102900 (run 400/2500) loss=2.37278 byte_ppl=2.449 atoms=144 merges=0 field=21.5610 rms=0.3369 scale=1.0000 fcos=0.090 ign=0.1500 mph=0.500 +step=2103100 (run 600/2500) loss=0.84817 byte_ppl=1.214 atoms=88 merges=0 field=38.1401 rms=0.5959 scale=1.0000 fcos=0.153 ign=0.1500 mph=0.500 +step=2103300 (run 800/2500) loss=4.14937 byte_ppl=5.129 atoms=32 merges=0 field=64.3150 rms=1.0049 scale=1.0000 fcos=0.177 ign=0.1500 mph=0.500 +step=2103500 (run 1000/2500) loss=10.32189 byte_ppl=92.373 atoms=232 merges=0 field=106.9250 rms=1.6707 scale=1.0000 fcos=0.210 ign=0.1500 mph=0.500 +step=2103700 (run 1200/2500) loss=6.81823 byte_ppl=77.035 atoms=176 merges=0 field=174.8288 rms=2.7317 scale=1.0000 fcos=0.146 ign=0.1500 mph=0.500 +step=2103900 (run 1400/2500) loss=4.61942 byte_ppl=18.994 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.149 ign=0.1500 mph=0.500 +step=2104100 (run 1600/2500) loss=6.30402 byte_ppl=51.803 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.279 ign=0.1500 mph=0.500 +step=2104300 (run 1800/2500) loss=5.01236 byte_ppl=18.018 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.162 ign=0.1500 mph=0.500 +step=2104500 (run 2000/2500) loss=6.39849 byte_ppl=19.706 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.284 ign=0.1500 mph=0.500 +step=2104700 (run 2200/2500) loss=6.85200 byte_ppl=13.420 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.230 ign=0.1500 mph=0.500 +step=2104900 (run 2400/2500) loss=8.32475 byte_ppl=127.348 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.259 ign=0.1500 mph=0.500 +step=2105000 (run 2500/2500) loss=6.32966 byte_ppl=20.555 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.160 ign=0.1500 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 2500, + "start_step": 2102500, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.08, + "slow_every": 4 + }, + "train": { + "steps": 2500, + "start_step": 2102500, + "total_steps": 2105000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 3796.7575237510027, + "transitions_per_second": 0.6584565868009732, + "first_loss": 6.400629043579102, + "final_loss": 6.32966423034668, + "final_total_perplexity": 560.9682061272248, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0074567794799805, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9975202679634094, + "field_norm_max": 191.99996948242188, + "field_limited_steps": 1262, + "field_limited_fraction": 0.5048, + "final_dynamics": { + "coupling_scale": 1.990602731704712, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.9987053871154785, + "energy_decay_before": 0.4499995708465576, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 7, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 17.19775122498709, + "total_perplexity": 29436655.015937008, + "byte_loss": 6.683856225202954, + "byte_perplexity": 799.3958262841246, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_lign_smoke/atom_native.pt", + "reload": { + "n_atoms": 196, + "field_norm": 191.9999237060547, + "time": 25.000476837158203, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c652c712165203dc33e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c687166662c2c72659174d8d720646b3e203d6b", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c712c652070753e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} diff --git a/docs/artifacts/lign_smoke_2k5/lign_smoke_probe_after.txt b/docs/artifacts/lign_smoke_2k5/lign_smoke_probe_after.txt new file mode 100644 index 0000000000000000000000000000000000000000..441e8e393a49627925f100db10909a60b5b98da4 --- /dev/null +++ b/docs/artifacts/lign_smoke_2k5/lign_smoke_probe_after.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2105000 +[probe] prompt='Bonjour' + RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Qui es-tu ?' + RMS 0.006797 -> 0.034235 (norm 0.4350 -> 2.1910) atoms 7 -> 26 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Il était une fois' + RMS 0.006036 -> 0.033740 (norm 0.3863 -> 2.1593) atoms 6 -> 25 + gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22 + gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>' +[probe] mean off-diag cosine logits=0.991285 alpha=0.698694 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md +[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md +[probe] updated /workspace/exports/atom-ai/docs/SCALE.md +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/lign_smoke_2k5/lign_smoke_probe_before.txt b/docs/artifacts/lign_smoke_2k5/lign_smoke_probe_before.txt new file mode 100644 index 0000000000000000000000000000000000000000..89f6609007aaa4240de301f251ded607fe706446 --- /dev/null +++ b/docs/artifacts/lign_smoke_2k5/lign_smoke_probe_before.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2102500 +[probe] prompt='Bonjour' + RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26 + gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25 + gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22 + gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f =k> =k", + "reload_text": " =k> =k", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c687166662c2c72659174d8d720646b3e203d6b", + "text": " =k", + "reload_text": " =k", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "3c69692c6f2c712c652070753e203d6b3e203d6b", + "text": " =k> =k", + "reload_text": " =k> =k", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/linguistic_spans/chunk_100k/chat.txt b/docs/artifacts/linguistic_spans/chunk_100k/chat.txt new file mode 100644 index 0000000000000000000000000000000000000000..767b17288bd5c5550b65a7cae210afcfc2af4241 --- /dev/null +++ b/docs/artifacts/linguistic_spans/chunk_100k/chat.txt @@ -0,0 +1,34 @@ +### Bonjour +Prompt: Bonjour +Response: !H Ma� iau:tc� +.|�L� +A d � + +H. +H�eqdea�� p�u�:ed ��nai� fd� + +sce�� k�tasvm��aba +�c gs al:a:td,�gC�v�����.0#«�A +A + + + +### Qui es-tu ? +Prompt: Qui es-tu ? +Response: + +### Il était une fois +Prompt: Il était une fois +Response: s� ardr�t�:ig�spt9J.p�d +Hsa + + + +### Bonjour (deterministic) +Prompt: Bonjour +Response: AAa.M +l,,� 0.022426 (norm 0.1613 -> 1.4353) atoms 2 -> 21 + gen_preview='AAa.M\nl,,� 0.022737 (norm 0.2946 -> 1.4551) atoms 3 -> 22 + gen_preview='\n\n\n\n\neOiie g�us�ed��:C�r�u�pte\neOiqe g�us:ed��gC�r�uìte\n\neOiqe glus:ede�gC�r�u �te\n\nsOiqe glus�ede�pC�rAup te\nsclqe glus�ede�gC,rAup te�\t�!9�\n\n\nsclqe glus�ede�' +[probe] prompt='Il était une fois' + RMS 0.003697 -> 0.023243 (norm 0.2366 -> 1.4876) atoms 3 -> 22 + gen_preview='\n\n\n\ns.iJe:g�us: de-)C�L�p�d�e\ns.iJe:g�us:edesgC�LAuì�e\n\ns�igeag�us:ede�gC�rAup��e�#�\n\n\nsOigeag�us:ede�gC�rfup��e\nscigeag�us:ede�gC�rfup �e�\t�\nscigh glus:ede�gC' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.002521 -> 0.022426 (norm 0.1613 -> 1.4353) atoms 2 -> 21 + gen_preview='AAa.M\nl,,� 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95)) +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LR param groups differ from checkpoint +step=3375001 (run 1/50000) loss=9.83900 byte_ppl=254.370 atoms=1 merges=0 field=0.1128 rms=0.0020 scale=1.0000 fcos=0.692 ign=0.0000 prn=nan mph=0.000 bytes=524288 pkts=27462 shard=0 +step=3375050 (run 50/50000) loss=4.15503 byte_ppl=3.868 atoms=50 merges=0 field=2.3375 rms=0.0365 scale=1.0000 fcos=0.615 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375100 (run 100/50000) loss=7.75727 byte_ppl=85.828 atoms=100 merges=0 field=4.2996 rms=0.0672 scale=1.0000 fcos=0.602 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375150 (run 150/50000) loss=3.36688 byte_ppl=2.845 atoms=150 merges=0 field=5.9228 rms=0.0925 scale=1.0000 fcos=0.590 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375200 (run 200/50000) loss=7.76101 byte_ppl=116.858 atoms=200 merges=0 field=7.5974 rms=0.1187 scale=1.0000 fcos=0.580 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375250 (run 250/50000) loss=3.60576 byte_ppl=3.277 atoms=250 merges=0 field=9.1384 rms=0.1428 scale=1.0000 fcos=0.573 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375300 (run 300/50000) loss=7.30132 byte_ppl=121.229 atoms=44 merges=0 field=10.9591 rms=0.1712 scale=1.0000 fcos=0.569 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375350 (run 350/50000) loss=7.20671 byte_ppl=121.377 atoms=94 merges=0 field=12.8018 rms=0.2000 scale=1.0000 fcos=0.565 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375400 (run 400/50000) loss=8.22015 byte_ppl=167.070 atoms=144 merges=0 field=14.7994 rms=0.2312 scale=1.0000 fcos=0.561 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375450 (run 450/50000) loss=7.20289 byte_ppl=53.864 atoms=194 merges=0 field=16.9471 rms=0.2648 scale=1.0000 fcos=0.559 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375500 (run 500/50000) loss=4.89892 byte_ppl=6.670 atoms=244 merges=0 field=19.2339 rms=0.3005 scale=1.0000 fcos=0.558 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3375550 (run 550/50000) loss=7.76190 byte_ppl=125.050 atoms=38 merges=0 field=21.6217 rms=0.3378 scale=1.0000 fcos=0.556 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +... + "bytes_hex": "2021277527766e712769a9cd656cc36f3a737774", + "text": " !'u'vnq'i\ufffd\ufffdel\ufffdo:swt", + "reload_text": " !'u'vnq'i\ufffd\ufffdel\ufffdo:swt", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "7361652072c3626f686c206c276173eb64a079ae", + "text": "sae r\ufffdbohl l'as\ufffdd\ufffdy\ufffd", + "reload_text": "sae r\ufffdbohl l'as\ufffdd\ufffdy\ufffd", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "0a746e0a6f546973782e555674732073ae0a0a", + "text": "\ntn\noTisx.UVts s\ufffd\n\n", + "reload_text": "\ntn\noTisx.UVts s\ufffd\n\n", + "reload_match": true + } + } +} diff --git a/docs/artifacts/linguistic_spans/chunk_50k/chat.txt b/docs/artifacts/linguistic_spans/chunk_50k/chat.txt new file mode 100644 index 0000000000000000000000000000000000000000..9f87a916a4bcc6c8d238b7c15669ca32dcec989e --- /dev/null +++ b/docs/artifacts/linguistic_spans/chunk_50k/chat.txt @@ -0,0 +1,35 @@ +### Bonjour +Prompt: Bonjour +Response: !d�aa��titg:tc� +p�l�lu�ph҇8��S� +Hc +ooeeo Me� pAAdcs ��pozu:�d��p��veä�o.~�CTm�fUfe + + + +### Qui es-tu ? +Prompt: Qui es-tu ? +Response: + +### Il était une fois +Prompt: Il était une fois +Response: r +s a + +dfMis�thu +:edÍa�UmŊ�� +r� g��glua�Dde�amǢfmvdU�d 2!E� + +s�q + +f' ge giu��vde�gb�>�p��U.0� + +eeag�as�za�Hd�����1ńf��. � +2ha + + + +### Bonjour (deterministic) +Prompt: Bonjour +Response: Apa� as ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e + diff --git a/docs/artifacts/linguistic_spans/chunk_50k/field_probe_report.json b/docs/artifacts/linguistic_spans/chunk_50k/field_probe_report.json new file mode 100644 index 0000000000000000000000000000000000000000..22eb8631d9d6f74819d28804418898ea9ba3adbf --- /dev/null +++ b/docs/artifacts/linguistic_spans/chunk_50k/field_probe_report.json @@ -0,0 +1,441 @@ +{ + "timestamp_local": "2026-09-18 16:39:57 PDT", + "timestamp_utc": "2026-09-18T23:39:57.123000+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 32, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "enable_merge": true, + "slow_every": 1, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_contrast_margin": 0.55, + "field_ignorance_weight": 0.0, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "printable_aux_weight": 0.0, + "merge_count_total": 0 + }, + "training_meta": { + "step": 3375000, + "run_steps": 50000, + "seed": 20260913, + "episode_reset": false, + "atom_flush_every": 256, + "dynamics_on_load": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.5484083294868469, + "energy_decay_before": 0.30000001192092896, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt", + "checkpoint_bytes": 47380837 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 2, + "packet_payloads": [ + "Utilisateur: Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.002575422404333949, + "field_norm": 0.16482703387737274, + "field_mean_abs": 0.0018891594372689724, + "field_max_abs": 0.021730387583374977, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 2, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.019999999552965164 + }, + "stats_after_gen": { + "field_rms": 0.030461745336651802, + "field_norm": 1.9495519399642944, + "field_mean_abs": 0.019823584705591202, + "field_max_abs": 0.17880390584468842, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 21, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.21000002324581146 + }, + "generated_preview": "Apa\ufffd as ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e", + "generated_bytes": 115, + "surface_byte_logits_norm": 125.34232330322266 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur: Qui es-tu ?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.00450554583221674, + "field_norm": 0.28835490345954895, + "field_mean_abs": 0.0031115259043872356, + "field_max_abs": 0.03162336349487305, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.02340536192059517, + "field_norm": 1.4979432821273804, + "field_mean_abs": 0.017407096922397614, + "field_max_abs": 0.13813002407550812, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "\n\n\n\n\nsOiqe g us:\ufffdd\ufffd\ufffd\ufffdC\ufffdj\ufffd!\ufffdp=r\nsOiqe g\ufffdus:\ufffdd\ufffd\ufffd\ufffdC\ufffdrAu\u05ectr\n\nsOiqe g us\ufffd&d\ufffd\ufffd\ufffdC\ufffd\ufffdAu\u05ec\ufffdr\ns\ufffdsge g us\ufffd&d\ufffd\ufffd\ufffdC\u06e2Au\ufffd\ufffd\ufffdr\n\ns\ufffd ge g us\ufffd&de\ufffdpC\ufffd\ufffdAu\ufffd\ufffd\ufffd\ufffd\n\ns\ufffd ge g us\ufffd&de\ufffdpC\ufffd\ufffdAu\ufffd", + "generated_bytes": 294, + "surface_byte_logits_norm": 124.97484588623047 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur: Il \u00e9tait une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0037958628963679075, + "field_norm": 0.24293522536754608, + "field_mean_abs": 0.0028677149675786495, + "field_max_abs": 0.028762931004166603, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.023401813581585884, + "field_norm": 1.4977160692214966, + "field_mean_abs": 0.0172744020819664, + "field_max_abs": 0.13804784417152405, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "\n\n\n\nsOiJe\ufffdg\ufffdus:\ufffdd,\ufffd)C\ufffdLAp\ufffdd\ufffde\ns\ufffdiJe g\ufffdus:\ufffdde\ufffd\ufffdC\ufffdLAp\ufffd\ufffd\ufffde\ns\ufffdige g\ufffdus:&de\ufffd\ufffdC\ufffdLAu\ufffd\ufffd\ufffd\ufffd\ufffd\t\ufffd\n\ns\ufffdige g\ufffdus:&de\ufffd\ufffdC\u06e2Au\ufffd\ufffd\ufffde\ufffd\t\ufffd\n\n\ns\ufffdige g\ufffdus:&de\ufffd\ufffdC\u06e2Au\ufffd\ufffd\ufffde\ufffd\t\ufffd\ns\ufffdige g\ufffdus:&de", + "generated_bytes": 322, + "surface_byte_logits_norm": 125.71207427978516 + }, + { + "prompt": "Utilisateur: Bonjour\nAssistant:", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 2, + "packet_payloads": [ + "Utilisateur: Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.002575422404333949, + "field_norm": 0.16482703387737274, + "field_mean_abs": 0.0018891594372689724, + "field_max_abs": 0.021730387583374977, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 2, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.019999999552965164 + }, + "stats_after_gen": { + "field_rms": 0.030461745336651802, + "field_norm": 1.9495519399642944, + "field_mean_abs": 0.019823584705591202, + "field_max_abs": 0.17880390584468842, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 21, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.21000002324581146 + }, + "generated_preview": "Apa\ufffd as ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e", + "generated_bytes": 115, + "surface_byte_logits_norm": 125.34232330322266 + } + ], + "prompt_sensitivity": { + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "cosine_alpha": [ + [ + 1.0000000217667446, + 0.6944012760637956, + 0.669534167858365, + 1.0000000217667446 + ], + [ + 0.6944012760637956, + 1.0000000435162137, + 0.6913045865620868, + 0.6944012760637956 + ], + [ + 0.669534167858365, + 0.6913045865620868, + 0.9999999436357431, + 0.669534167858365 + ], + [ + 1.0000000217667446, + 0.6944012760637956, + 0.669534167858365, + 1.0000000217667446 + ] + ], + "cosine_output_state": [ + [ + 0.9999999527697081, + 0.8044588382003146, + 0.9096363481835081, + 0.9999999527697081 + ], + [ + 0.8044588382003146, + 0.9999998405358232, + 0.8020669891981551, + 0.8044588382003146 + ], + [ + 0.9096363481835081, + 0.8020669891981551, + 0.9999999454284457, + 0.9096363481835081 + ], + [ + 0.9999999527697081, + 0.8044588382003146, + 0.9096363481835081, + 0.9999999527697081 + ] + ], + "cosine_surface_logits": [ + [ + 0.9999998643559591, + 0.8463830431275975, + 0.865974308542433, + 0.9999998643559591 + ], + [ + 0.8463830431275975, + 0.9999999475742297, + 0.8663951814851142, + 0.8463830431275975 + ], + [ + 0.865974308542433, + 0.8663951814851142, + 1.0000003595435258, + 0.865974308542433 + ], + [ + 0.9999998643559591, + 0.8463830431275975, + 0.865974308542433, + 0.9999998643559591 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.21049602329730988, + 0.1804608255624771, + 0.0 + ], + [ + 0.21049602329730988, + 0.0, + 0.21286651492118835, + 0.21049602329730988 + ], + [ + 0.1804608255624771, + 0.21286651492118835, + 0.0, + 0.1804608255624771 + ], + [ + 0.0, + 0.21049602329730988, + 0.1804608255624771, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.7365292493621921, + "mean_offdiag_cosine_output_state": 0.8717095524559181, + "mean_offdiag_cosine_surface_logits": 0.8818516248635224, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.21049602329730988, + 0.1804608255624771, + 0.0, + 0.21286651492118835, + 0.21049602329730988, + 0.1804608255624771 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.16579670210679373, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 5.0965936679858714e-05, + "baseline_mean_mse": 0.000621866318397224, + "mse_improvement_vs_mean": 0.0005709003817173652, + "pred_target_cosine_per_prompt": [ + 0.9994367539083037, + 0.9968598360703447, + 0.9969921213349268, + 0.9994367539083037 + ], + "mean_pred_target_cosine": 0.9981813663054697, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000099341104, + "per_prompt": [ + 1.0, + 0.9999999602635748, + 1.0000000794728667, + 1.0 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "mean_offdiag_cosine_surface_logits": 0.8818516248635224, + "mean_offdiag_cosine_alpha": 0.7365292493621921, + "mean_field_rms_after_prompt": 0.0033630633843131363, + "mean_field_rms_after_20_gen": 0.026932666543871164, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/linguistic_spans/chunk_50k/probe.txt b/docs/artifacts/linguistic_spans/chunk_50k/probe.txt new file mode 100644 index 0000000000000000000000000000000000000000..f7f6260d8f854cbb4a1fa9746436452f00e97e10 --- /dev/null +++ b/docs/artifacts/linguistic_spans/chunk_50k/probe.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=3375000 +[probe] prompt='Bonjour' + RMS 0.002575 -> 0.030462 (norm 0.1648 -> 1.9496) atoms 2 -> 21 + gen_preview='Apa� as ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e' +[probe] prompt='Qui es-tu ?' + RMS 0.004506 -> 0.023405 (norm 0.2884 -> 1.4979) atoms 3 -> 22 + gen_preview='\n\n\n\n\nsOiqe g us:�d���C�j�!�p=r\nsOiqe g�us:�d���C�rAu\u05ectr\n\nsOiqe g us�&d���C��Au\u05ec�r\ns�sge g us�&d���CۢAu���r\n\ns� ge g us�&de�pC��Au����\n\ns� ge g us�&de�pC��Au�' +[probe] prompt='Il était une fois' + RMS 0.003796 -> 0.023402 (norm 0.2429 -> 1.4977) atoms 3 -> 22 + gen_preview='\n\n\n\nsOiJe�g�us:�d,�)C�LAp�d�e\ns�iJe g�us:�de��C�LAp���e\ns�ige g�us:&de��C�LAu�����\t�\n\ns�ige g�us:&de��CۢAu���e�\t�\n\n\ns�ige g�us:&de��CۢAu���e�\t�\ns�ige g�us:&de' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.002575 -> 0.030462 (norm 0.1648 -> 1.9496) atoms 2 -> 21 + gen_preview='Apa� as ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e ae e' +[probe] mean off-diag cosine logits=0.881852 alpha=0.736529 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md +[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md +[probe] updated /workspace/exports/atom-ai/docs/SCALE.md +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/linguistic_spans/chunk_50k/run_metrics.json b/docs/artifacts/linguistic_spans/chunk_50k/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..59b7505cf2c2d3c4bd9b8278f95ca62b1616ac3c --- /dev/null +++ b/docs/artifacts/linguistic_spans/chunk_50k/run_metrics.json @@ -0,0 +1,145 @@ +{ + "stream": true, + "data_path": null, + "data_glob": "data/dialogue_shards/part_*", + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt" + ], + "data_bytes": 7066157, + "data_characters": null, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": null, + "train_packet_count": null, + "validation_packet_count": 2048, + "mean_packet_bytes": null, + "max_packet_bytes": null, + "min_packet_bytes": null, + "bytes_seen": 1048576, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 32, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 50000, + "start_step": 3325000, + "seed": 20260913, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "stream": true, + "chunk_bytes": 1048576, + "loop_shards": true, + "stream_buffer": 2048, + "stream_prefetch": true, + "enable_merge": true, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "printable_aux_weight": 0.0, + "slow_every": 1 + }, + "packets_seen": 54947, + "stream_epoch": 0, + "train": { + "steps": 50000, + "start_step": 3325000, + "total_steps": 3375000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 1427.0970382510004, + "transitions_per_second": 35.03615988249701, + "first_loss": 10.409775733947754, + "final_loss": 9.134225845336914, + "final_total_perplexity": 9267.100674920166, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.006105661392212, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9979686141014099, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 48478, + "field_limited_fraction": 0.96956, + "final_dynamics": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.5484083294868469, + "energy_decay_before": 0.2999170422554016, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + }, + "final_atoms_before_validation": 4, + "stream": true, + "bytes_seen": 1048576 + }, + "validation": { + "transitions": 256, + "loss": 7.1272735465317965, + "total_perplexity": 1245.4765995535452, + "byte_loss": 4.101913979044184, + "byte_perplexity": 60.45588823665378, + "source": "stream_ring" + }, + "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt", + "reload": { + "n_atoms": 80, + "field_norm": 191.99986267089844, + "time": 500.1767883300781, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2027610a206520385f716c927444a09573eb20e5", + "text": " 'a\n e 8_ql\ufffdtD\ufffd\ufffds\ufffd \ufffd", + "reload_text": " 'a\n e 8_ql\ufffdtD\ufffd\ufffds\ufffd \ufffd", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "4161656465652c2c69637392a9832c0ae369497d", + "text": "Aaedee,,ics\ufffd\ufffd\ufffd,\n\ufffdiI}", + "reload_text": "Aaedee,,ics\ufffd\ufffd\ufffd,\n\ufffdiI}", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "0a272061206c206e203a2bd574c68d73aa0a0a", + "text": "\n' a l n :+\ufffdt\u018ds\ufffd\n\n", + "reload_text": "\n' a l n :+\ufffdt\u018ds\ufffd\n\n", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/linguistic_spans/chunk_50k/train_excerpt.txt b/docs/artifacts/linguistic_spans/chunk_50k/train_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..e4eb98359ad2398445da2d219bfce48e28f3eada --- /dev/null +++ b/docs/artifacts/linguistic_spans/chunk_50k/train_excerpt.txt @@ -0,0 +1,56 @@ +train lock skipped (--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3325000, legacy_surface_migrated=True, span_head_migrated=True) +span-head pad-migrate: old_max=16 -> new_max=32 padded=10 tensors (field/core kept; new rows only) +atomizer pack_mode=linguistic max_span_bytes=32 +dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95)) +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LayerNorm migration changed bias scale +step=3325001 (run 1/50000) loss=10.40978 byte_ppl=358.524 atoms=1 merges=0 field=0.1158 rms=0.0021 scale=1.0000 fcos=0.695 ign=0.0000 prn=nan mph=0.000 bytes=524288 pkts=27462 shard=0 +step=3325050 (run 50/50000) loss=5.15741 byte_ppl=5.132 atoms=50 merges=0 field=2.4749 rms=0.0387 scale=1.0000 fcos=0.652 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325100 (run 100/50000) loss=7.93792 byte_ppl=71.663 atoms=100 merges=0 field=4.4329 rms=0.0693 scale=1.0000 fcos=0.643 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325150 (run 150/50000) loss=4.87981 byte_ppl=3.844 atoms=150 merges=0 field=6.2729 rms=0.0980 scale=1.0000 fcos=0.638 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325200 (run 200/50000) loss=9.67721 byte_ppl=201.796 atoms=200 merges=0 field=7.8901 rms=0.1233 scale=1.0000 fcos=0.631 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325250 (run 250/50000) loss=4.50899 byte_ppl=3.253 atoms=250 merges=0 field=9.8786 rms=0.1544 scale=1.0000 fcos=0.627 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325300 (run 300/50000) loss=9.92596 byte_ppl=207.108 atoms=44 merges=0 field=11.9672 rms=0.1870 scale=1.0000 fcos=0.624 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325350 (run 350/50000) loss=9.74259 byte_ppl=173.364 atoms=94 merges=0 field=14.1936 rms=0.2218 scale=1.0000 fcos=0.621 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325400 (run 400/50000) loss=8.17101 byte_ppl=209.395 atoms=144 merges=0 field=16.5543 rms=0.2587 scale=1.0000 fcos=0.618 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325450 (run 450/50000) loss=8.10495 byte_ppl=82.901 atoms=194 merges=0 field=19.2532 rms=0.3008 scale=1.0000 fcos=0.618 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325500 (run 500/50000) loss=4.70964 byte_ppl=4.614 atoms=244 merges=0 field=22.0822 rms=0.3450 scale=1.0000 fcos=0.616 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325550 (run 550/50000) loss=7.79491 byte_ppl=190.972 atoms=38 merges=0 field=25.1497 rms=0.3930 scale=1.0000 fcos=0.615 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325600 (run 600/50000) loss=4.77624 byte_ppl=5.303 atoms=88 merges=0 field=28.5828 rms=0.4466 scale=1.0000 fcos=0.614 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325650 (run 650/50000) loss=8.39410 byte_ppl=156.294 atoms=138 merges=0 field=32.2896 rms=0.5045 scale=1.0000 fcos=0.613 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325700 (run 700/50000) loss=7.00639 byte_ppl=140.715 atoms=188 merges=0 field=36.3047 rms=0.5673 scale=1.0000 fcos=0.613 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +step=3325750 (run 750/50000) loss=6.94402 byte_ppl=122.347 atoms=238 merges=0 field=40.6975 rms=0.6359 scale=1.0000 fcos=0.612 ign=0.0000 prn=nan mph=0.500 bytes=524288 pkts=27462 shard=0 +... + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2027610a206520385f716c927444a09573eb20e5", + "text": " 'a\n e 8_ql\ufffdtD\ufffd\ufffds\ufffd \ufffd", + "reload_text": " 'a\n e 8_ql\ufffdtD\ufffd\ufffds\ufffd \ufffd", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "4161656465652c2c69637392a9832c0ae369497d", + "text": "Aaedee,,ics\ufffd\ufffd\ufffd,\n\ufffdiI}", + "reload_text": "Aaedee,,ics\ufffd\ufffd\ufffd,\n\ufffdiI}", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "0a272061206c206e203a2bd574c68d73aa0a0a", + "text": "\n' a l n :+\ufffdt\u018ds\ufffd\n\n", + "reload_text": "\n' a l n :+\ufffdt\u018ds\ufffd\n\n", + "reload_match": true + } + } +} diff --git a/docs/artifacts/linguistic_spans/pytest.txt b/docs/artifacts/linguistic_spans/pytest.txt new file mode 100644 index 0000000000000000000000000000000000000000..8fdc6c83a505af010f3e36538245de2d1007db0e --- /dev/null +++ b/docs/artifacts/linguistic_spans/pytest.txt @@ -0,0 +1,2 @@ +..................................s............... [100%] +49 passed, 1 skipped in 3.80s diff --git a/docs/artifacts/merge_operational/chat.txt b/docs/artifacts/merge_operational/chat.txt new file mode 100644 index 0000000000000000000000000000000000000000..20125930d93943b27d169396b14fb23712989754 --- /dev/null +++ b/docs/artifacts/merge_operational/chat.txt @@ -0,0 +1,29 @@ +### Bonjour +Prompt: Bonjour +Response: fa Mae, �ua:vci +1|l��m�p,��83�ATb�Ͱ bultig�j�C,m�p� �m# �T�� +L��g� hu�:ts,C^edJhpI�t� + + + +### Qui es-tu ? +Prompt: Qui es-tu ? +Response: + +### Il était une fois +Prompt: Il était une fois +Response: s� + +s +ss �s tlur:ed� ��:w�u� +ecM +qdfM s�s�� +su os d' ɨr us:tersgnI�auv t� �+ +s� g��ricsies�sgb�va 0.020182 (norm 0.1603 -> 1.2917) atoms 1 -> 1 + gen_preview="AAa.Mtl,�� 0.023975 (norm 0.2969 -> 1.5344) atoms 1 -> 1 + gen_preview='\n\n\n\n\neOiie�g�us�edi��C�j-!�pce\n\neOiie g�us:ede�gC�r�uìte\n\neOiie gius�ede�gC�r�uìte\nsOiqe g�us:ede�gCkr�up tr�\t�\n\nsO ie glus:ede�gC�rfup �e�\t�\n\nsc ge glus�ede�' +[probe] prompt='Il était une fois' + RMS 0.003720 -> 0.024232 (norm 0.2381 -> 1.5509) atoms 1 -> 1 + gen_preview='\n\n\ns�ibs:t�us:vde-g�aJ�p�d�e��N\n\n\ns�iJ�:g�us:edesgCajfu�d�e�t�\ns� q�:g�us:edesgCajfup��e�t�\n\n\ns� J�ag�us:ede�gCajfu���e�t�\nsc g�ag�us:ede�gCavfup��e�\t�\n\nsc g�ag' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.002505 -> 0.020182 (norm 0.1603 -> 1.2917) atoms 1 -> 1 + gen_preview="AAa.Mtl,��.\n\nQui ? .\n\n" + (16 names with distinct first letters, G uniform in [8, 160], filler = random slices of the + mixed training corpus). The first name byte after "Qui ? " is only predictable from the + name seen G+~15 bytes earlier: chance = ln 16 = 2.77 nats / 6.25 % acc. Eval on 256 fixed + held-out episodes (other filler, other seed) bucketed by distance. +task mem2k : the 2 KB memorisation test (root_cause/memorize_2k.txt, greedy regen past a 32-byte prefix). +usage: longmem_bench.py NAME --task recall|mem2k --minutes M [--k K] [--slow-block F] [--slow-cap C] + [--slow-gain ema|none] [--lr 2e-3] [--leak .05] +""" +import argparse, json, math, random, sys, time +from pathlib import Path +import torch +HERE = Path(__file__).resolve().parent +ROOT = HERE.parents[2] +sys.path.insert(0, str(ROOT)); sys.path.insert(0, str(ROOT / "tools")); sys.path.insert(0, str(HERE.parent / "decfix_bptt")) +from src.atom_native import AtomNativeModel # noqa: E402 +from src.io.atomizer import Atomizer # noqa: E402 +import memorize_bptt as MB # noqa: E402 (flush, tf_ce, regen) + +NAMES = ["Alice", "Bruno", "Cyril", "Denis", "Emile", "Fanny", "Gaston", "Hugo", + "Irene", "Jules", "Karim", "Louise", "Marc", "Nadia", "Oscar", "Paul"] +OUTDIR = ROOT / "checkpoints/mix_long_memory_bench" + + +def filler_source(): + raw = b"".join(p.read_bytes() for p in sorted((ROOT / "data").glob("corpus_fr_mix_[0-9]*.txt"))) + return raw.decode("utf-8", "ignore").replace("\n", " ") + + +def episode(rng, src, gmin=8, gmax=160, gap=None): + name = rng.choice(NAMES); g = gap if gap is not None else rng.randint(gmin, gmax) + o = rng.randrange(0, len(src) - 400); fill = src[o:o + g] + head = f"Nom: {name}.\n"; q = "\nQui ? " + text = head + fill + q + name + ".\n\n" + ans = len((head + fill + q).encode()) # byte index of the first answer byte + dist = ans - len("Nom: ".encode()) # bytes between the name's first byte and the answer + return text.encode(), ans, dist, name + + +def build(a): + torch.manual_seed(a.seed) + m = AtomNativeModel(d_model=32, n_modes=32, n_atoms_max=64, max_payload_bytes=1, + atomizer=Atomizer(max_span_bytes=1), field_max_rms=3.0, enable_merge=False, + field_loss_weight=0.05, field_obligatory_hard=True, last_atom_readout=True, + field_leak=a.leak) + m.field_leak = float(a.leak) + m.set_field_leak_learnable(True, init=float(a.leak)) + if a.slow_block > 0: + m.set_field_leak_slow_block(a.slow_block, cap=a.slow_cap, gain=a.slow_gain, ref=a.leak) + m.set_field_bptt(int(a.k)) + m.surface.payload_enabled = False; m.surface.last_atom_dropout = a.ladrop; m.field_loss_weight = 0.05 + m._efference_every = 0 + return m + + +@torch.no_grad() +def eval_recall(m, eps): + m.eval(); m.reset_state(reset_atomizer=True) + buckets = {}; tick = 0 + for text, ans, dist, name in eps: + pk = m.atomizer.encode_bytes(text, reset=False) + for i in range(len(pk) - 1): + out = m.forward_packet(pk[i]); tick += 1 + if tick % 64 == 0: MB.flush(m) + if i + 1 == ans: + lp = torch.log_softmax(out["surface"]["byte_logits"][0], -1) + tgt = text[ans] + b = "d<32" if dist < 32 else "d32-63" if dist < 64 else "d64-127" if dist < 128 else "d128+" + r = buckets.setdefault(b, {"n": 0, "ce": 0.0, "acc": 0}) + r["n"] += 1; r["ce"] += float(-lp[tgt]); r["acc"] += int(int(lp.argmax()) == tgt) + m.forward_packet(pk[-1]); tick += 1 + m.train() + return {b: {"n": r["n"], "ce": round(r["ce"] / r["n"], 4), "acc": round(r["acc"] / r["n"], 4)} for b, r in sorted(buckets.items())} + + +def main(): + ap = argparse.ArgumentParser() + ap.add_argument("name"); ap.add_argument("--task", default="recall"); ap.add_argument("--minutes", type=float, default=45) + ap.add_argument("--k", type=int, default=128); ap.add_argument("--leak", type=float, default=0.05) + ap.add_argument("--slow-block", type=float, default=0.0); ap.add_argument("--slow-cap", type=float, default=0.02) + ap.add_argument("--slow-gain", default="ema"); ap.add_argument("--lr", type=float, default=2e-3) + ap.add_argument("--ladrop", type=float, default=0.5); ap.add_argument("--seed", type=int, default=20260913) + ap.add_argument("--eval-min", type=float, default=10.0) + a = ap.parse_args() + torch.set_num_threads(1) + m = build(a); m.train() + params = [p for p in m.parameters() if p.requires_grad] + opt = torch.optim.AdamW(params, lr=a.lr, weight_decay=0.01) + t0 = time.time(); step = 0; updates = 0; capped = 0; log = []; nan = False + if a.task == "recall": + src = filler_source(); half = len(src) // 2 + train_src, eval_src = src[:half], src[half:] + erng = random.Random(777) + eval_eps = [episode(erng, eval_src) for _ in range(256)] + rng = random.Random(a.seed) + stream = iter(lambda: episode(rng, train_src)[0], None) + r0 = {"min": 0, "recall": eval_recall(m, eval_eps)}; log.append(r0); print(json.dumps(r0), flush=True) + else: + data = MB.TEXT.read_bytes() + r0 = {"min": 0, "tf_ce": MB.tf_ce(m, data)}; log.append(r0); print(json.dumps(r0), flush=True) + next_eval = a.eval_min * 60; acc = None; n = 0 + m.reset_state(reset_atomizer=True) + + def tick(cur, tgt): + nonlocal step, updates, capped, acc, n, nan + step += 1 + loss, info = m.transition_loss(cur, tgt) + capped += info["field_scale"] < 0.999999 + acc = loss if acc is None else acc + loss; n += 1 + if n >= a.k: + window_step() + if step % 64 == 0: MB.flush(m) + + def window_step(): + nonlocal updates, acc, n, nan + if acc is None: return + opt.zero_grad(set_to_none=True); (acc / n).backward() + gn = torch.nn.utils.clip_grad_norm_(params, 1.0) + if not math.isfinite(float(gn)): nan = True; raise FloatingPointError("nan grad") + opt.step(); updates += 1; m.detach_field_graph(); acc = None; n = 0 + m.stabilize_dynamics_parameters() + + def leak_stats(): + lam = m.learnable_leak_rates().detach().reshape(-1) + out = {"leak_min_mean_max": [round(float(lam.min()), 4), round(float(lam.mean()), 4), round(float(lam.max()), 4)]} + if m.field_leak_slow_block is not None: + out["slow_leak"] = [round(float(lam[i]), 4) for i in m.field_leak_slow_block["modes"]] + return out + try: + while time.time() - t0 < a.minutes * 60: + if a.task == "recall": + chunk = b"".join(next(stream) for _ in range(8)) + pk = m.atomizer.encode_bytes(chunk, reset=False) + prev = getattr(m, "_bench_prev", None) + if prev is not None: tick(prev, pk[0]) + for i in range(len(pk) - 1): tick(pk[i], pk[i + 1]) + m._bench_prev = pk[-1] + else: + m.reset_state(reset_atomizer=True); pk = m.atomizer.encode_bytes(data, reset=True) + for i in range(len(pk) - 1): tick(pk[i], pk[i + 1]) + window_step() + if time.time() - t0 >= next_eval: + window_step(); next_eval += a.eval_min * 60 + r = {"min": round((time.time() - t0) / 60, 1), "step": step, "updates": updates, "cap_frac": round(capped / step, 4), **leak_stats()} + if a.task == "recall": + saved = m.core.state.alpha.clone(); r["recall"] = eval_recall(m, eval_eps) + m.reset_state(reset_atomizer=True); m._bench_prev = None + else: + r["tf_ce"] = MB.tf_ce(m, data); r["regen"] = MB.regen(m, data)[0] - 32 + log.append(r); print(json.dumps(r), flush=True) + except FloatingPointError as exc: + print("STOP:", exc, flush=True) + window_step() + res = {"name": a.name, "args": vars(a), "steps": step, "updates": updates, "minutes": round((time.time() - t0) / 60, 1), + "field_cap_fraction": capped / max(step, 1), "nan": nan, **leak_stats(), + "dynamics": {k: v for k, v in m.stabilize_dynamics_parameters().items() if k in ("energy_decay", "coupling_scale", "phase_sync")}} + if a.task == "recall": + res["final_recall"] = eval_recall(m, eval_eps) + else: + same, head = MB.regen(m, data) + res.update(final_tf_ce=MB.tf_ce(m, data), regen_bytes_past_prefix=same - 32, regen_head=head[:300]) + res["log"] = log + OUTDIR.mkdir(parents=True, exist_ok=True) + ck = OUTDIR / f"{a.name}.pt" + if not ck.exists(): + m.save(ck); res["checkpoint"] = str(ck.relative_to(ROOT)) + (HERE / f"bench_{a.name}.json").write_text(json.dumps(res, indent=1, ensure_ascii=False)) + print(json.dumps({k: v for k, v in res.items() if k != "log"}, ensure_ascii=False), flush=True) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/mix_long_memory/mix_common.py b/docs/artifacts/mix_long_memory/mix_common.py new file mode 100644 index 0000000000000000000000000000000000000000..beb6d532abce58ee24d5929be4f1eb0f16c5ffd5 --- /dev/null +++ b/docs/artifacts/mix_long_memory/mix_common.py @@ -0,0 +1,64 @@ +"""Held-out val sets for docs/MIX_DATA_LONG_MEMORY.md (same protocol as eval_windows.py: +contiguous 512-transition windows, state reset per window, eval/no_grad, normal + field-alone). + +* val_varied : 6 windows, one per held-out book slice of data/heldout/val_varied.txt (never in train) +* val_dialog : 4 windows of data/heldout/val_dialogue.txt (held-out dialogue blocks, never in train + verbatim; templated lines can recur in train) +* val2048 : the old fixed val (inside the old corpus, which is also ~25 % of the mix stream) +""" +import sys +from pathlib import Path +import numpy as np +import torch +HERE = Path(__file__).resolve().parent +ROOT = HERE.parents[2] +sys.path.insert(0, str(HERE.parent / "decfix_bptt")) +import dfb_common as C # noqa: E402 (val2048, probe_chats, load_model) +from src.io.atomizer import Atomizer # noqa: E402 +EW = C.EW +N = 512 + + +def _win(text_bytes, off): + t = text_bytes[off: off + 4 * N].decode("utf-8", errors="ignore") + pk = Atomizer(max_span_bytes=1).encode(t, reset=True)[: N + 1] + return list(zip(pk[:-1], pk[1:])) + + +def varied_windows(): + raw = (ROOT / "data/heldout/val_varied.txt").read_bytes() + out = [] + starts = [i for i in range(len(raw)) if raw.startswith(b"### ", i) and (i == 0 or raw[i - 1:i] == b"\n")] + for s in starts: + body = raw.index(b"\n", s) + 1 + out.append({"src": raw[s + 4: body - 1].decode(), "pairs": _win(raw, body + 2000)}) + return out + + +def dialog_windows(): + raw = (ROOT / "data/heldout/val_dialogue.txt").read_bytes() + out = [] + for f in (0.1, 0.35, 0.6, 0.85): + o = raw.index(b"\n\nUtilisateur:", int(len(raw) * f)) + 2 + out.append({"src": f"val_dialogue@{o}", "pairs": _win(raw, o)}) + return out + + +_CACHE = {} + + +def eval_set(m, name): + if name not in _CACHE: + _CACHE[name] = {"varied": varied_windows, "dialog": dialog_windows, "val2048": EW.windows}[name]() + normal, alone = [], [] + for w in _CACHE[name]: + normal += EW.run(m, w["pairs"], False); alone += EW.run(m, w["pairs"], True) + return float(np.mean(normal)), float(np.mean(alone)) + + +def all_vals(m): + out = {} + for n in ("dialog", "varied", "val2048"): + a, b = eval_set(m, n) + out[f"{n}_normal"] = a; out[f"{n}_field_alone"] = b + return out diff --git a/docs/artifacts/mix_long_memory/probe_recall_alpha.json b/docs/artifacts/mix_long_memory/probe_recall_alpha.json new file mode 100644 index 0000000000000000000000000000000000000000..b7bd8232aa7114463d63d718bd0f25577a938a81 --- /dev/null +++ b/docs/artifacts/mix_long_memory/probe_recall_alpha.json @@ -0,0 +1,116 @@ +{ + "checkpoints/mix_long_memory_bench/recall_k128_base.pt": { + "overall_acc": 0.09833333333333333, + "d<32": { + "n": 30, + "acc": 0.43333333333333335 + }, + "d32-63": { + "n": 126, + "acc": 0.15873015873015872 + }, + "d64-127": { + "n": 238, + "acc": 0.06302521008403361 + }, + "d128+": { + "n": 206, + "acc": 0.05339805825242718 + } + }, + "fresh": { + "overall_acc": 0.09333333333333334, + "d<32": { + "n": 30, + "acc": 0.23333333333333334 + }, + "d32-63": { + "n": 126, + "acc": 0.18253968253968253 + }, + "d64-127": { + "n": 238, + "acc": 0.058823529411764705 + }, + "d128+": { + "n": 206, + "acc": 0.05825242718446602 + } + }, + "checkpoints/mix_long_memory_bench/recall_k128_slow.pt": { + "overall_acc": 0.17833333333333334, + "d<32": { + "n": 30, + "acc": 0.5 + }, + "d32-63": { + "n": 126, + "acc": 0.3888888888888889 + }, + "d64-127": { + "n": 238, + "acc": 0.12184873949579832 + }, + "d128+": { + "n": 206, + "acc": 0.06796116504854369 + } + }, + "fresh_slow": { + "overall_acc": 0.14333333333333334, + "d<32": { + "n": 30, + "acc": 0.2 + }, + "d32-63": { + "n": 126, + "acc": 0.1746031746031746 + }, + "d64-127": { + "n": 238, + "acc": 0.15966386554621848 + }, + "d128+": { + "n": 206, + "acc": 0.0970873786407767 + } + }, + "checkpoints/mix_long_memory_bench/recall_k256_base.pt": { + "overall_acc": 0.12166666666666667, + "d<32": { + "n": 30, + "acc": 0.43333333333333335 + }, + "d32-63": { + "n": 126, + "acc": 0.24603174603174602 + }, + "d64-127": { + "n": 238, + "acc": 0.06302521008403361 + }, + "d128+": { + "n": 206, + "acc": 0.06796116504854369 + } + }, + "checkpoints/mix_long_memory_bench/recall_k256_slow.pt": { + "overall_acc": 0.195, + "d<32": { + "n": 30, + "acc": 0.6 + }, + "d32-63": { + "n": 126, + "acc": 0.48412698412698413 + }, + "d64-127": { + "n": 238, + "acc": 0.10084033613445378 + }, + "d128+": { + "n": 206, + "acc": 0.06796116504854369 + } + } +} \ No newline at end of file diff --git a/docs/artifacts/mix_long_memory/probe_recall_alpha.py b/docs/artifacts/mix_long_memory/probe_recall_alpha.py new file mode 100644 index 0000000000000000000000000000000000000000..4cd9447bf07344aa7fcefa54e92514985b8a33af --- /dev/null +++ b/docs/artifacts/mix_long_memory/probe_recall_alpha.py @@ -0,0 +1,65 @@ +"""Is the name still IN the field at the answer position? Frozen recall-bench checkpoint, eval mode, +stream of recall episodes (held-out filler half); at the first answer byte collect α (32x32 field) and +fit a ridge one-vs-rest linear probe (name, 16-way) on 1200 episodes, test on 600, per distance bucket. +Chance = 6.25 %. Separates 'memory retains the information' from 'readout learned to use it'. +usage: probe_recall_alpha.py OUT.json CKPT [CKPT ...]""" +import json, random, sys +from pathlib import Path +import numpy as np +import torch +HERE = Path(__file__).resolve().parent +sys.path.insert(0, str(HERE)) +import longmem_bench as LB # noqa: E402 +sys.path.insert(0, str(LB.ROOT / "tools")) +from chat_atom_native import load_model # noqa: E402 + + +@torch.no_grad() +def collect(m, eps): + m.eval(); m.reset_state(reset_atomizer=True); X, y, d = [], [], []; tick = 0 + for text, ans, dist, name in eps: + pk = m.atomizer.encode_bytes(text, reset=False) + for i in range(len(pk)): + m.forward_packet(pk[i]); tick += 1 + if tick % 64 == 0: LB.MB.flush(m) + if i + 1 == ans: + X.append(m.core.state.alpha.detach().reshape(-1).numpy().copy()); y.append(LB.NAMES.index(name)); d.append(dist) + return np.array(X), np.array(y), np.array(d) + + +def ridge_probe(Xtr, ytr, Xte, lam=1.0): + mu, sd = Xtr.mean(0), Xtr.std(0) + 1e-6 + A, B = (Xtr - mu) / sd, (Xte - mu) / sd + Y = np.eye(16)[ytr] + W = np.linalg.solve(A.T @ A + lam * len(A) * np.eye(A.shape[1]), A.T @ Y) + return (B @ W).argmax(1) + + +def main(): + torch.set_num_threads(1) + out, cks = sys.argv[1], sys.argv[2:] + src = LB.filler_source(); ev = src[len(src) // 2:] + rng = random.Random(4242) + eps = [LB.episode(rng, ev) for _ in range(1800)] + res = {} + for ck in cks: + if ck.startswith("fresh"): # untrained controls: "fresh" (λ .05) / "fresh_slow" (+ slow block .25) + import argparse + a = argparse.Namespace(seed=20260913, leak=0.05, slow_block=0.25 if ck == "fresh_slow" else 0.0, + slow_cap=0.02, slow_gain="ema", k=0, ladrop=0.5) + m = LB.build(a) + else: + m = load_model(ck) + X, y, d = collect(m, eps) + pred = ridge_probe(X[:1200], y[:1200], X[1200:], lam=1e-2) + yt, dt = y[1200:], d[1200:] + r = {"overall_acc": float((pred == yt).mean())} + for lo, hi, b in ((0, 32, "d<32"), (32, 64, "d32-63"), (64, 128, "d64-127"), (128, 999, "d128+")): + sel = (dt >= lo) & (dt < hi) + r[b] = {"n": int(sel.sum()), "acc": float((pred[sel] == yt[sel]).mean()) if sel.any() else None} + res[ck] = r; print(ck, json.dumps(r), flush=True) + Path(out).write_text(json.dumps(res, indent=1)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/mix_long_memory/pytest_full.txt b/docs/artifacts/mix_long_memory/pytest_full.txt new file mode 100644 index 0000000000000000000000000000000000000000..7af959451d479036059ea01aed455a456695d3b5 --- /dev/null +++ b/docs/artifacts/mix_long_memory/pytest_full.txt @@ -0,0 +1,87 @@ +..................F..................................................... [ 43%] +.......................s................................................ [ 86%] +.........F.F.......... [100%] +=================================== FAILURES =================================== +_ ChatMergeOffIngestTests.test_payload_copy_sees_distinct_atoms_when_merge_off _ + +self = + + def test_payload_copy_sees_distinct_atoms_when_merge_off(self) -> None: + """Distinct living payloads under merge-off boost target byte mass vs MERGE collapse.""" + torch.manual_seed(5) + model = self._tiny() + model.eval() + prompt = "AAA BBB CCC DDD EEE FFF " + packets = model.atomizer.encode(prompt, reset=True) + self.assertGreaterEqual(len(packets), 2) + + model.reset_state(reset_atomizer=True) + last_off = None + for p in packets: + last_off = model.forward_packet(p, merge_enabled=False) + assert last_off is not None + n_off = len(model.core.atoms) + logits_off = last_off["surface"]["byte_logits"] + # Bytes present in prompt payloads. + target = sorted({b for p in packets for b in (p.payload or b"")}) + mass_off = float(logits_off.softmax(dim=-1)[:, target].sum().item()) + + model.reset_state(reset_atomizer=True) + packets2 = model.atomizer.encode(prompt, reset=True) + last_on = None + for p in packets2: + last_on = model.forward_packet(p) + assert last_on is not None + n_on = len(model.core.atoms) + logits_on = last_on["surface"]["byte_logits"] + mass_on = float(logits_on.softmax(dim=-1)[:, target].sum().item()) + + self.assertGreaterEqual(n_off, 2) + self.assertEqual(n_on, 1) + # Soft check: merge-off should not be worse on prompt-byte mass. +> self.assertGreaterEqual( + mass_off + 1e-6, + mass_on * 0.9, + msg=f"mass_off={mass_off:.4f} mass_on={mass_on:.4f} n_off={n_off} n_on={n_on}", + ) +E AssertionError: 3.050107763839722 not greater than or equal to 3.1522358894348144 : mass_off=3.0501 mass_on=3.5025 n_off=3 n_on=1 + +test/test_chat_merge_off.py:123: AssertionError +____________________ SpeechLockUnitTests.test_dialogue_wrap ____________________ + +self = + + def test_dialogue_wrap(self) -> None: +> self.assertEqual( + format_dialogue_prompt("Bonjour"), + "Utilisateur: Bonjour\nAssistant:", + ) +E AssertionError: 'Utilisateur: Bonjour\nAssistant: ' != 'Utilisateur: Bonjour\nAssistant:' +E Utilisateur: Bonjour +E - Assistant: +E ? - +E + Assistant: + +test/test_speech_lock.py:17: AssertionError +__________ SpeechLockUnitTests.test_speech_ok_rejects_attractor_soup ___________ + +self = + + def test_speech_ok_rejects_attractor_soup(self) -> None: + self.assertFalse(speech_ok(b"")) +> self.assertFalse(speech_ok(b"auiseateu : aernun e")) +E AssertionError: True is not false + +test/test_speech_lock.py:25: AssertionError +=============================== warnings summary =============================== +test/test_field_hard_couple.py::FieldHardCoupleTests::test_load_keeps_tip_field_feat_norm + /workspace/exports/atom-ai/test/test_field_hard_couple.py:125: UserWarning: Converting a tensor with requires_grad=True to a scalar may lead to unexpected behavior. + Consider using tensor.detach() first. (Triggered internally at /__w/pytorch/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:820.) + float(model2.surface.field_hard_couple_byte.weight.abs().mean()), 0.0 + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +=========================== short test summary info ============================ +FAILED test/test_chat_merge_off.py::ChatMergeOffIngestTests::test_payload_copy_sees_distinct_atoms_when_merge_off +FAILED test/test_speech_lock.py::SpeechLockUnitTests::test_dialogue_wrap - As... +FAILED test/test_speech_lock.py::SpeechLockUnitTests::test_speech_ok_rejects_attractor_soup +3 failed, 162 passed, 1 skipped, 1 warning in 767.72s (0:12:47) diff --git a/docs/artifacts/mix_long_memory/tsv_mix.py b/docs/artifacts/mix_long_memory/tsv_mix.py new file mode 100644 index 0000000000000000000000000000000000000000..02a4f72418561dbf962baeed76ab93e35bde537c --- /dev/null +++ b/docs/artifacts/mix_long_memory/tsv_mix.py @@ -0,0 +1,36 @@ +"""Append one progress row for a mixed-corpus checkpoint: held-out dialogue / held-out varied / old +val2048 (normal + field-alone), train stats, 3 probe chats (unseeded) + seed 1. 1 thread. +usage: tsv_mix.py TSV CKPT RUN_METRICS_JSON [--no-chats]""" +import json, os, re, sys, time +from pathlib import Path +import torch +sys.path.insert(0, str(Path(__file__).resolve().parent)) +import mix_common as M + + +def main(): + torch.set_num_threads(1) + tsv, ck, rm = sys.argv[1:4] + t0 = time.time(); m = M.C.load_model(ck); v = M.all_vals(m) + tr = json.load(open(rm)).get("train", {}) if os.path.exists(rm) else {} + lam = tr.get("field_leak_learnable_rates") + chats = [] if "--no-chats" in sys.argv else M.C.probe_chats(m, seeds=(1,)) + step = re.search(r"step_(\d+)_", ck).group(1) + cols = [("step", step)] + [(k, f"{x:.4f}") for k, x in v.items()] + [ + ("train_final_loss", f"{tr.get('final_loss', float('nan')):.4f}"), + ("steps_per_s", f"{tr.get('transitions_per_second', 0):.1f}"), + ("cap_frac", f"{tr.get('field_limited_fraction', float('nan')):.3f}"), + ("nan", str(tr.get("nan_or_inf"))), + ("leak_mean", f"{sum(lam) / len(lam):.4f}" if lam else ""), + ("leak_min", f"{min(lam):.4f}" if lam else ""), + ("time", time.strftime("%Y-%m-%dT%H:%M:%S%z"))] + cols += [(f"chat_{r['seed'] or 'u'}_{i % 3}", " ".join(r["resp"].split())[:90].replace("\t", " ")) for i, r in enumerate(chats)] + new = not os.path.exists(tsv) + with open(tsv, "a", encoding="utf-8") as fh: + if new: fh.write("\t".join(c for c, _ in cols) + "\n") + fh.write("\t".join(x for _, x in cols) + "\n") + print("\t".join(x for _, x in cols), f"({time.time() - t0:.0f}s)", flush=True) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/multi_atom_ring/chat.txt b/docs/artifacts/multi_atom_ring/chat.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f7fd6f8e5fa2cb480779c5d05c622bfb72b56c1 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/chat.txt @@ -0,0 +1,17 @@ +===== PROMPT: Bonjour ===== +Prompt: Bonjour +Response: stu�sudteur:i ngliit �o + + + +===== PROMPT: Qui es-tu ? ===== +Prompt: Qui es-tu ? +Response: + +===== PROMPT: Il était une fois ===== +Prompt: Il était une fois +Response: A +asc aate: so i� t p e n + + + diff --git a/docs/artifacts/multi_atom_ring/field_probe_report.json b/docs/artifacts/multi_atom_ring/field_probe_report.json new file mode 100644 index 0000000000000000000000000000000000000000..6f80435a4510cd91340add3056e5ec095de15929 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/field_probe_report.json @@ -0,0 +1,444 @@ +{ + "timestamp_local": "2026-09-18 18:05:33 PDT", + "timestamp_utc": "2026-09-19T01:05:33.258029+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 32, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "enable_merge": true, + "merge_coherence_threshold": 0.45, + "merge_energy_floor": 0.08, + "slow_every": 1, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_contrast_margin": 0.55, + "field_ignorance_weight": 0.0, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "printable_aux_weight": 0.0, + "field_next_packet_weight": 0.05, + "merge_count_total": 72771 + }, + "training_meta": { + "step": 3498000, + "run_steps": 15000, + "seed": 20260913, + "episode_reset": false, + "atom_flush_every": 0, + "dynamics_on_load": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.4993484914302826, + "energy_decay_before": 0.30000001192092896, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_chat/atom_native.pt", + "checkpoint_bytes": 54533549 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 2, + "packet_payloads": [ + "Utilisateur: Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0025552583392709494, + "field_norm": 0.16353651881217957, + "field_mean_abs": 0.0018971064127981663, + "field_max_abs": 0.01749471388757229, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 1, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.019999999552965164 + }, + "stats_after_gen": { + "field_rms": 0.0212762001901865, + "field_norm": 1.3616769313812256, + "field_mean_abs": 0.015579604543745518, + "field_max_abs": 0.16742654144763947, + "alpha_numel": 4096, + "persistence_norm": 0.00023045156558509916, + "persistence_mean_abs": 2.8806445698137395e-05, + "persistence_strength": 0.07243102788925171, + "n_atoms": 1, + "consolidation_count": 960, + "abstraction_count": 0, + "t": 0.21000002324581146 + }, + "generated_preview": "\n\n\nauiseatiu : rernui e ie\n\n\n\nauiseatiu : erernuiee ie\n\nauiseatiu : e\ufffdernutee te\n\n\nauiseatiur: e\ufffdernutee te\n\nau seatiu : e\ufffdernut e \n\nau eateu : e\ufffdernut e", + "generated_bytes": 212, + "surface_byte_logits_norm": 1408.1553955078125 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur: Qui es-tu ?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.004478651098906994, + "field_norm": 0.2866336703300476, + "field_mean_abs": 0.003169607138261199, + "field_max_abs": 0.03362397477030754, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 1, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.02201659232378006, + "field_norm": 1.4090620279312134, + "field_mean_abs": 0.015995297580957413, + "field_max_abs": 0.16990996897220612, + "alpha_numel": 4096, + "persistence_norm": 0.00026916919159702957, + "persistence_mean_abs": 3.36461525876075e-05, + "persistence_strength": 0.07706887274980545, + "n_atoms": 1, + "consolidation_count": 1024, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "\n\n\n\n\nauiieatiu : ereinunee ote\n\n\nauiieatiu : ereinunee te\n\nauiieateu : e\ufffdeinunee te\n\nau ieateur: e\ufffdernunee \n\nau eateu : e\ufffdernun e \n\nau eateur: e\ufffdernun e ", + "generated_bytes": 210, + "surface_byte_logits_norm": 1435.13037109375 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur: Il \u00e9tait une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.003504096530377865, + "field_norm": 0.22426217794418335, + "field_mean_abs": 0.002597557380795479, + "field_max_abs": 0.02230105735361576, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 1, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.021159183233976364, + "field_norm": 1.3541878461837769, + "field_mean_abs": 0.015545116737484932, + "field_max_abs": 0.1669299453496933, + "alpha_numel": 4096, + "persistence_norm": 0.00022163291578181088, + "persistence_mean_abs": 2.7704112653736956e-05, + "persistence_strength": 0.07706887274980545, + "n_atoms": 1, + "consolidation_count": 1024, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "\n\n\nauiosatiu : \ufffdernue e ie\n\n\n\nauiieatiu : e\ufffdernui e ie\n\n\nauiieatiu : e\ufffdernui e te\n\nauiseateur: e\ufffdernut e te\n\n\nauiseateu : e\ufffdernut e \n\nau eateu :ee\ufffdernun ", + "generated_bytes": 212, + "surface_byte_logits_norm": 1586.9410400390625 + }, + { + "prompt": "Utilisateur: Bonjour\nAssistant:", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 2, + "packet_payloads": [ + "Utilisateur: Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0025552583392709494, + "field_norm": 0.16353651881217957, + "field_mean_abs": 0.0018971064127981663, + "field_max_abs": 0.01749471388757229, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 1, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.019999999552965164 + }, + "stats_after_gen": { + "field_rms": 0.0212762001901865, + "field_norm": 1.3616769313812256, + "field_mean_abs": 0.015579604543745518, + "field_max_abs": 0.16742654144763947, + "alpha_numel": 4096, + "persistence_norm": 0.00023045156558509916, + "persistence_mean_abs": 2.8806445698137395e-05, + "persistence_strength": 0.07243102788925171, + "n_atoms": 1, + "consolidation_count": 960, + "abstraction_count": 0, + "t": 0.21000002324581146 + }, + "generated_preview": "\n\n\nauiseatiu : rernui e ie\n\n\n\nauiseatiu : erernuiee ie\n\nauiseatiu : e\ufffdernutee te\n\n\nauiseatiur: e\ufffdernutee te\n\nau seatiu : e\ufffdernut e \n\nau eateu : e\ufffdernut e", + "generated_bytes": 212, + "surface_byte_logits_norm": 1408.1553955078125 + } + ], + "prompt_sensitivity": { + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "cosine_alpha": [ + [ + 1.0000001198848563, + 0.5723997626100198, + 0.4782710344315834, + 1.0000001198848563 + ], + [ + 0.5723997626100198, + 1.0000000313732404, + 0.5935560518159031, + 0.5723997626100198 + ], + [ + 0.4782710344315834, + 0.5935560518159031, + 0.999999913243217, + 0.4782710344315834 + ], + [ + 1.0000001198848563, + 0.5723997626100198, + 0.4782710344315834, + 1.0000001198848563 + ] + ], + "cosine_output_state": [ + [ + 0.9999999200269104, + 0.7557485577811226, + 0.8741069440643682, + 0.9999999200269104 + ], + [ + 0.7557485577811226, + 0.9999999644194125, + 0.812574246981293, + 0.7557485577811226 + ], + [ + 0.8741069440643682, + 0.812574246981293, + 0.9999999936767365, + 0.8741069440643682 + ], + [ + 0.9999999200269104, + 0.7557485577811226, + 0.8741069440643682, + 0.9999999200269104 + ] + ], + "cosine_surface_logits": [ + [ + 0.9999999275888765, + 0.9983408628178381, + 0.9984243081442599, + 0.9999999275888765 + ], + [ + 0.9983408628178381, + 0.9999998733360834, + 0.9985799400534325, + 0.9983408628178381 + ], + [ + 0.9984243081442599, + 0.9985799400534325, + 0.9999999216576336, + 0.9984243081442599 + ], + [ + 0.9999999275888765, + 0.9983408628178381, + 0.9984243081442599, + 0.9999999275888765 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.23503296077251434, + 0.20483282208442688, + 0.0 + ], + [ + 0.23503296077251434, + 0.0, + 0.236946240067482, + 0.23503296077251434 + ], + [ + 0.20483282208442688, + 0.236946240067482, + 0.0, + 0.20483282208442688 + ], + [ + 0.0, + 0.23503296077251434, + 0.20483282208442688, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.6158162942973276, + "mean_offdiag_cosine_output_state": 0.8453808617831976, + "mean_offdiag_cosine_surface_logits": 0.9986850349277508, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.23503296077251434, + 0.20483282208442688, + 0.0, + 0.236946240067482, + 0.23503296077251434, + 0.20483282208442688 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.18611296763022742, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 3.6532430385705084e-05, + "baseline_mean_mse": 0.000621866318397224, + "mse_improvement_vs_mean": 0.0005853338880115189, + "pred_target_cosine_per_prompt": [ + 0.9996123994309712, + 0.9977090132625108, + 0.9978436500913965, + 0.9996123994309712 + ], + "mean_pred_target_cosine": 0.9986943655539624, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 0.7915157649440582, + "per_prompt": [ + 0.7680577955314842, + 0.8786917924880981, + 0.7512556762251661, + 0.7680577955314842 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field differs across prompts but surface logits nearly identical \u2014 field not reliably read by surface (Transformer-regime risk / surface-only byte-LM behavior at decode)", + "mean_offdiag_cosine_surface_logits": 0.9986850349277508, + "mean_offdiag_cosine_alpha": 0.6158162942973276, + "mean_field_rms_after_prompt": 0.0032733160769566894, + "mean_field_rms_after_20_gen": 0.021432043984532356, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/multi_atom_ring/probe.txt b/docs/artifacts/multi_atom_ring/probe.txt new file mode 100644 index 0000000000000000000000000000000000000000..0b947695ee6cab7f313b8d38387c1cc96b47d049 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/probe.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_chat/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=3498000 +[probe] prompt='Bonjour' + RMS 0.002555 -> 0.021276 (norm 0.1635 -> 1.3617) atoms 1 -> 1 + gen_preview='\n\n\nauiseatiu : rernui e ie\n\n\n\nauiseatiu : erernuiee ie\n\nauiseatiu : e�ernutee te\n\n\nauiseatiur: e�ernutee te\n\nau seatiu : e�ernut e \n\nau eateu : e�ernut e' +[probe] prompt='Qui es-tu ?' + RMS 0.004479 -> 0.022017 (norm 0.2866 -> 1.4091) atoms 1 -> 1 + gen_preview='\n\n\n\n\nauiieatiu : ereinunee ote\n\n\nauiieatiu : ereinunee te\n\nauiieateu : e�einunee te\n\nau ieateur: e�ernunee \n\nau eateu : e�ernun e \n\nau eateur: e�ernun e ' +[probe] prompt='Il était une fois' + RMS 0.003504 -> 0.021159 (norm 0.2243 -> 1.3542) atoms 1 -> 1 + gen_preview='\n\n\nauiosatiu : �ernue e ie\n\n\n\nauiieatiu : e�ernui e ie\n\n\nauiieatiu : e�ernui e te\n\nauiseateur: e�ernut e te\n\n\nauiseateu : e�ernut e \n\nau eateu :ee�ernun ' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.002555 -> 0.021276 (norm 0.1635 -> 1.3617) atoms 1 -> 1 + gen_preview='\n\n\nauiseatiu : rernui e ie\n\n\n\nauiseatiu : erernuiee ie\n\nauiseatiu : e�ernutee te\n\n\nauiseatiur: e�ernutee te\n\nau seatiu : e�ernut e \n\nau eateu : e�ernut e' +[probe] mean off-diag cosine logits=0.998685 alpha=0.615816 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md +[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md +[probe] updated /workspace/exports/atom-ai/docs/SCALE.md +[probe] VERDICT: field differs across prompts but surface logits nearly identical — field not reliably read by surface (Transformer-regime risk / surface-only byte-LM behavior at decode) diff --git a/docs/artifacts/multi_atom_ring/pytest.txt b/docs/artifacts/multi_atom_ring/pytest.txt new file mode 100644 index 0000000000000000000000000000000000000000..ea97f931d6b61e4f5922d6d16cc2d3d2bba51707 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/pytest.txt @@ -0,0 +1,2 @@ +..........................................s............... [100%] +57 passed, 1 skipped in 3.81s diff --git a/docs/artifacts/multi_atom_ring/run_metrics.json b/docs/artifacts/multi_atom_ring/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..13e38806cad54dad8054b626e46ca77e9cd04bb8 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/run_metrics.json @@ -0,0 +1,148 @@ +{ + "stream": true, + "data_path": null, + "data_glob": "data/dialogue_shards/part_*", + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt" + ], + "data_bytes": 7066157, + "data_characters": null, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": null, + "train_packet_count": null, + "validation_packet_count": 2048, + "mean_packet_bytes": null, + "max_packet_bytes": null, + "min_packet_bytes": null, + "bytes_seen": 524288, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 32, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 0, + "learning_rate": 0.0003, + "surface_learning_rate": 0.0003, + "steps": 15000, + "start_step": 3483000, + "seed": 20260913, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "stream": true, + "chunk_bytes": 1048576, + "loop_shards": true, + "stream_buffer": 2048, + "stream_prefetch": true, + "enable_merge": true, + "merge_coherence_threshold": 0.45, + "merge_energy_floor": 0.08, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "printable_aux_weight": 0.0, + "field_next_packet_weight": 0.05, + "slow_every": 1 + }, + "packets_seen": 27462, + "stream_epoch": 0, + "train": { + "steps": 15000, + "start_step": 3483000, + "total_steps": 3498000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 0, + "elapsed_seconds": 438.8948808460009, + "transitions_per_second": 34.176748589745316, + "first_loss": 9.929795265197754, + "final_loss": 5.988890647888184, + "final_total_perplexity": 398.97176416745236, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0049476623535156, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9983531832695007, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 13230, + "field_limited_fraction": 0.882, + "final_dynamics": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.4993484914302826, + "energy_decay_before": 0.29977160692214966, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + }, + "final_atoms_before_validation": 1, + "stream": true, + "bytes_seen": 524288 + }, + "validation": { + "transitions": 256, + "loss": 5.62979685771279, + "total_perplexity": 278.6055153224614, + "byte_loss": 2.7872180770500563, + "byte_perplexity": 16.23579020095531, + "source": "stream_ring" + }, + "checkpoint": "checkpoints/atom_native_chat/atom_native.pt", + "reload": { + "n_atoms": 1, + "field_norm": 191.9999237060547, + "time": 149.99684143066406, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "0a0a0a", + "text": "\n\n\n", + "reload_text": "\n\n\n", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "0a0a0a65756c207261746975203a6f647275726e", + "text": "\n\n\neul ratiu :odrurn", + "reload_text": "\n\n\neul ratiu :odrurn", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "0a6175206f6161647474726d6f726d657269756e", + "text": "\nau oaadttrmormeriun", + "reload_text": "\nau oaadttrmormeriun", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/multi_atom_ring/summary.json b/docs/artifacts/multi_atom_ring/summary.json new file mode 100644 index 0000000000000000000000000000000000000000..db79b5c38eb0aa82f76630349722e8e4fac366a4 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/summary.json @@ -0,0 +1,15 @@ +{ + "timestamp_local": "2026-09-18 18:05:43 PT", + "mechanism": "multi_atom_payload_ring", + "fix": "atom_flush_every 256->0 (default + train)", + "start_step": 3483000, + "end_step": 3498000, + "run_steps": 15000, + "logits_cos": 0.998685, + "alpha_cos": 0.615816, + "atoms_during_train": 1, + "chat_coherent_fr": false, + "verdict": "STOP \u2014 still noise; logits cos\u22480.999; flush=0 did not de-homogenize (MERGE keeps atoms=1)", + "next_hypothesis": "Disable MERGE on chat/probe ingest (train MERGE stays at thr=0.45) so prompt packets remain distinct living atoms for \u03b1-gated payload copy-bias.", + "checkpoint": "checkpoints/atom_native_chat/atom_native.pt" +} diff --git a/docs/artifacts/multi_atom_ring/train_excerpt.txt b/docs/artifacts/multi_atom_ring/train_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..710bf624d57a5ea34016133ce52e49e73df34db8 --- /dev/null +++ b/docs/artifacts/multi_atom_ring/train_excerpt.txt @@ -0,0 +1,26 @@ +train lock skipped (--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3483000, legacy_surface_migrated=False, span_head_migrated=False) +atomizer pack_mode=linguistic max_span_bytes=32 +dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95)) +field_next_packet_weight=0.05 (predict next packet features from α+atoms) +MERGE gates: enable=True coherence_thr=0.450 energy_floor=0.080 +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*(α_MLP+payload_prod)) +field_obligatory_readout=ON (migrated=False) +optimizer groups: field/other lr=0.0003 (13 tensors), surface lr=0.0003 (16 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LR param groups differ from checkpoint +step=3483001 (run 1/15000) loss=9.92980 byte_ppl=194.269 atoms=1 merges=57772 field=0.1184 rms=0.0021 scale=1.0000 fcos=0.581 ign=0.0000 prn=nan nxp=0.385 mph=0.000 bytes=524288 pkts=27462 shard=0 +step=3483025 (run 25/15000) loss=4.70933 byte_ppl=60.222 atoms=1 merges=57796 field=1.2040 rms=0.0188 scale=1.0000 fcos=0.552 ign=0.0000 prn=nan nxp=0.193 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483050 (run 50/15000) loss=3.24655 byte_ppl=1.774 atoms=1 merges=57821 field=2.0174 rms=0.0315 scale=1.0000 fcos=0.548 ign=0.0000 prn=nan nxp=0.411 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483075 (run 75/15000) loss=7.34976 byte_ppl=37.598 atoms=1 merges=57846 field=2.9974 rms=0.0468 scale=1.0000 fcos=0.547 ign=0.0000 prn=nan nxp=0.142 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483100 (run 100/15000) loss=8.72047 byte_ppl=41.162 atoms=1 merges=57871 field=3.7876 rms=0.0592 scale=1.0000 fcos=0.543 ign=0.0000 prn=nan nxp=0.164 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483125 (run 125/15000) loss=6.50144 byte_ppl=18.350 atoms=1 merges=57896 field=4.5042 rms=0.0704 scale=1.0000 fcos=0.539 ign=0.0000 prn=nan nxp=0.497 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483150 (run 150/15000) loss=1.48831 byte_ppl=1.171 atoms=1 merges=57921 field=5.2320 rms=0.0818 scale=1.0000 fcos=0.537 ign=0.0000 prn=nan nxp=0.124 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483175 (run 175/15000) loss=7.39990 byte_ppl=23.895 atoms=1 merges=57946 field=6.0639 rms=0.0948 scale=1.0000 fcos=0.539 ign=0.0000 prn=nan nxp=0.094 mph=0.693 bytes=524288 pkts=27462 shard=0 +step=3483200 (run 200/15000) loss=4.71635 byte_ppl=14.057 atoms=1 merges=57971 field=6.8235 rms=0.1066 scale=1.0000 fcos=0.537 ign=0.0000 prn=nan nxp=0.013 mph=0.693 bytes=524288 pkts=27462 shard=0 +... + "atom_flush_every": 0, + "total_steps": 3498000, + "atom_flush_every": 0, + "transitions_per_second": 34.176748589745316, + "final_loss": 5.988890647888184, diff --git a/docs/artifacts/obligatory_hard_25k/chat_samples.txt b/docs/artifacts/obligatory_hard_25k/chat_samples.txt new file mode 100644 index 0000000000000000000000000000000000000000..467f9271f84473619353026156fdfbcd1ff1b062 --- /dev/null +++ b/docs/artifacts/obligatory_hard_25k/chat_samples.txt @@ -0,0 +1,4 @@ +# Hard obligatory @ 2,925,000 — no fluency claim +Bonjour -> (binary/noise) +Qui es-tu ? -> (binary/noise) +Il était une fois -> (binary/noise) diff --git a/docs/artifacts/obligatory_hard_25k/probe_25k.txt b/docs/artifacts/obligatory_hard_25k/probe_25k.txt new file mode 100644 index 0000000000000000000000000000000000000000..d1b3df3369c7c1c7a8a7b0724954c868c86fbfcc --- /dev/null +++ b/docs/artifacts/obligatory_hard_25k/probe_25k.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2925000 +[probe] prompt='Bonjour' + RMS 0.004023 -> 0.024764 (norm 0.2575 -> 1.5849) atoms 3 -> 22 + gen_preview='7���777�BF�BF"\'G 0.029481 (norm 0.4722 -> 1.8868) atoms 7 -> 26 + gen_preview='逷|ڼ逷qڼ騷qڼ騷qړ����������//}}}}' +[probe] prompt='Il était une fois' + RMS 0.006696 -> 0.023155 (norm 0.4285 -> 1.4819) atoms 6 -> 25 + gen_preview="7��a��7\r�a�߯�;< 0.024764 (norm 0.2575 -> 1.5849) atoms 3 -> 22 + gen_preview='7���777�BF�BF"\'G 0.027221 (norm 0.2525 -> 1.7421) atoms 3 -> 22 + gen_preview='77777���������%�C����%�C����*%�C��*%�C���*%�C' +[probe] prompt='Qui es-tu ?' + RMS 0.006702 -> 0.026896 (norm 0.4289 -> 1.7214) atoms 7 -> 26 + gen_preview='7��Xoկn�V��7�yX�_�n�V�47�yX�_�n�V��7��~�_�n�5�47��~�_�n�5�47��~�_�n�5�47L�~g.�{�5�/7��~g.��J5�/7��~\\_��Jb�/7�?~g.��Jb�/7�?~\\_�nJb�/7�?~\\_��Jb�/7�?~\\_��Jb�/7�?~' +[probe] prompt='Il était une fois' + RMS 0.007000 -> 0.025890 (norm 0.4480 -> 1.6570) atoms 6 -> 25 + gen_preview='���a�CA��a�CA�ea�CA�eaCC�0�<ݙAA77777777������' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003945 -> 0.027221 (norm 0.2525 -> 1.7421) atoms 3 -> 22 + gen_preview='77777���������%�C����%�C����*%�C��*%�C���*%�C' +[probe] mean off-diag cosine logits=0.775563 alpha=0.763413 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md +[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md +[probe] updated /workspace/exports/atom-ai/docs/SCALE.md +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/obligatory_hard_25k/run_metrics.json b/docs/artifacts/obligatory_hard_25k/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..bf20379b89bb385cadb7e123089e1a2f8163fd34 --- /dev/null +++ b/docs/artifacts/obligatory_hard_25k/run_metrics.json @@ -0,0 +1,128 @@ +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 20000, + "start_step": 2905000, + "seed": 20260918, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "slow_every": 1 + }, + "train": { + "steps": 20000, + "start_step": 2905000, + "total_steps": 2925000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 437.16986433600005, + "transitions_per_second": 45.74880757249177, + "first_loss": 8.122807502746582, + "final_loss": 8.504480361938477, + "final_total_perplexity": 4936.838185958101, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0091934204101562, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9969445466995239, + "field_norm_max": 191.99998474121094, + "field_limited_steps": 18941, + "field_limited_fraction": 0.94705, + "final_dynamics": { + "coupling_scale": 2.0, + "energy_decay": 0.44999998807907104, + "phase_sync": 0.6462218761444092, + "energy_decay_before": 0.4499572515487671, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 10, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 8.506844777909537, + "total_perplexity": 4948.524735499277, + "byte_loss": 5.687372722322979, + "byte_perplexity": 295.1172462583266, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt", + "reload": { + "n_atoms": 32, + "field_norm": 191.9999237060547, + "time": 199.96937561035156, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "dbf376f3f3360db771f3ae21714dae8825bcdfa8", + "text": "\ufffd\ufffdv\ufffd\ufffd6\r\ufffdq\ufffd!qM\ufffd\ufffd%\ufffd\u07e8", + "reload_text": "\ufffd\ufffdv\ufffd\ufffd6\r\ufffdq\ufffd!qM\ufffd\ufffd%\ufffd\u07e8", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "f328f320d9b76d7b20ae896d207bd9db6d2db6a4", + "text": "\ufffd(\ufffd \u0677m{ \ufffd\ufffdm {\ufffd\ufffdm-\ufffd\ufffd", + "reload_text": "\ufffd(\ufffd \u0677m{ \ufffd\ufffdm {\ufffd\ufffdm-\ufffd\ufffd", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "7628f3aedb61afd9d56d20aedb2528aedb2598ec", + "text": "v(\ufffd\ufffda\ufffd\ufffd\ufffdm \ufffd\ufffd%(\ufffd\ufffd%\ufffd\ufffd", + "reload_text": "v(\ufffd\ufffda\ufffd\ufffd\ufffdm \ufffd\ufffd%(\ufffd\ufffd%\ufffd\ufffd", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/obligatory_hard_25k/train_20k_cont.txt b/docs/artifacts/obligatory_hard_25k/train_20k_cont.txt new file mode 100644 index 0000000000000000000000000000000000000000..909d4934ab64288cbb63b4a131399257716de3ad --- /dev/null +++ b/docs/artifacts/obligatory_hard_25k/train_20k_cont.txt @@ -0,0 +1,175 @@ +train lock skipped (--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=2905000, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +field_obligatory_hard=ON (mix_floor=1.0, non-alpha bypass frozen) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (7 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LR param groups differ from checkpoint +step=2905001 (run 1/20000) loss=8.12281 byte_ppl=408.071 atoms=1 merges=0 field=0.1197 rms=0.0021 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.000 +step=2905500 (run 500/20000) loss=10.70699 byte_ppl=407.931 atoms=244 merges=0 field=33.4019 rms=0.5219 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.500 +step=2906000 (run 1000/20000) loss=7.10971 byte_ppl=361.405 atoms=232 merges=0 field=160.9214 rms=2.5144 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.500 +step=2906500 (run 1500/20000) loss=8.30913 byte_ppl=1131.248 atoms=220 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2907000 (run 2000/20000) loss=9.47044 byte_ppl=366.840 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2907500 (run 2500/20000) loss=10.57844 byte_ppl=432.019 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2908000 (run 3000/20000) loss=7.62944 byte_ppl=280.070 atoms=184 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2908500 (run 3500/20000) loss=10.33979 byte_ppl=372.956 atoms=172 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2909000 (run 4000/20000) loss=8.09690 byte_ppl=724.432 atoms=160 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2909500 (run 4500/20000) loss=9.76947 byte_ppl=518.640 atoms=148 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2910000 (run 5000/20000) loss=7.38883 byte_ppl=336.890 atoms=136 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2910500 (run 5500/20000) loss=10.32909 byte_ppl=532.936 atoms=124 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.000 ign=0.0000 mph=0.500 +step=2911000 (run 6000/20000) loss=7.72852 byte_ppl=127.333 atoms=112 merges=0 field=191.9999 rms=3.0000 scale=0.9972 fcos=0.000 ign=0.0000 mph=0.500 +step=2911500 (run 6500/20000) loss=9.58306 byte_ppl=327.433 atoms=100 merges=0 field=191.9999 rms=3.0000 scale=0.9972 fcos=0.000 ign=0.0000 mph=0.500 +step=2912000 (run 7000/20000) loss=9.03481 byte_ppl=402.431 atoms=88 merges=0 field=191.9999 rms=3.0000 scale=0.9972 fcos=0.000 ign=0.0000 mph=0.500 +step=2912500 (run 7500/20000) loss=8.43312 byte_ppl=368.444 atoms=76 merges=0 field=191.9999 rms=3.0000 scale=0.9973 fcos=0.000 ign=0.0000 mph=0.500 +step=2913000 (run 8000/20000) loss=7.67410 byte_ppl=391.854 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9972 fcos=0.000 ign=0.0000 mph=0.500 +step=2913500 (run 8500/20000) loss=9.16667 byte_ppl=608.181 atoms=52 merges=0 field=191.9999 rms=3.0000 scale=0.9972 fcos=0.000 ign=0.0000 mph=0.500 +step=2914000 (run 9000/20000) loss=8.98242 byte_ppl=332.777 atoms=40 merges=0 field=191.9999 rms=3.0000 scale=0.9972 fcos=0.000 ign=0.0000 mph=0.500 +step=2914500 (run 9500/20000) loss=7.71954 byte_ppl=96.421 atoms=28 merges=0 field=191.9999 rms=3.0000 scale=0.9973 fcos=0.000 ign=0.0000 mph=0.500 +step=2915000 (run 10000/20000) loss=7.71543 byte_ppl=96.218 atoms=16 merges=0 field=191.9999 rms=3.0000 scale=0.9973 fcos=0.000 ign=0.0000 mph=0.500 +step=2915500 (run 10500/20000) loss=8.69715 byte_ppl=281.352 atoms=4 merges=0 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(--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native_src.pt (recorded step=2900000, legacy_surface_migrated=True) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +field_obligatory_hard=ON (mix_floor=1.0, non-alpha bypass frozen) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (7 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LayerNorm migration changed bias scale +step=2900001 (run 1/5000) loss=8.98821 byte_ppl=445.092 atoms=1 merges=0 field=0.1193 rms=0.0021 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.000 +step=2900200 (run 200/5000) loss=9.08820 byte_ppl=665.611 atoms=200 merges=0 field=8.1461 rms=0.1273 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.500 +step=2900400 (run 400/5000) loss=8.24958 byte_ppl=185.387 atoms=144 merges=0 field=20.7515 rms=0.3242 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.500 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byte_ppl=1240.349 atoms=128 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2903400 (run 3400/5000) loss=8.89144 byte_ppl=306.969 atoms=72 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2903600 (run 3600/5000) loss=8.54826 byte_ppl=783.893 atoms=16 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2903800 (run 3800/5000) loss=8.11769 byte_ppl=209.715 atoms=216 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2904000 (run 4000/5000) loss=8.61052 byte_ppl=859.373 atoms=160 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2904200 (run 4200/5000) loss=9.28322 byte_ppl=155.433 atoms=104 merges=0 field=191.9999 rms=3.0000 scale=0.9969 fcos=0.000 ign=0.0000 mph=0.500 +step=2904400 (run 4400/5000) loss=8.71502 byte_ppl=868.578 atoms=48 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2904600 (run 4600/5000) loss=10.28176 byte_ppl=413.519 atoms=248 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2904800 (run 4800/5000) loss=8.21598 byte_ppl=277.477 atoms=192 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +step=2905000 (run 5000/5000) loss=7.38938 byte_ppl=282.637 atoms=136 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.000 ign=0.0000 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 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"\ufffd\ufffd\u059e\ufffd\ufffd\ufffdp@\ufffdQP@\ufffd!%C@\ufffd@", + "reload_text": "\ufffd\ufffd\u059e\ufffd\ufffd\ufffdp@\ufffdQP@\ufffd!%C@\ufffd@", + "reload_match": true + } + } +} diff --git a/docs/artifacts/obligatory_smoke_1k5/before_after.json b/docs/artifacts/obligatory_smoke_1k5/before_after.json new file mode 100644 index 0000000000000000000000000000000000000000..6317d7640da78195d588a25dfb6326bb924c6654 --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/before_after.json @@ -0,0 +1,22 @@ +{ + "part_a": { + "logits": 0.9799355809256632, + "alpha": 0.7067174167542339, + "rms_prompt": 0.005340076517313719, + "rms_gen": 0.026839961763471365 + }, + "migrate_only": { + "logits": 0.7534786422462006, + "alpha": 0.7067174167542339, + "mix": 0.6749999523162842 + }, + "after_smoke": { + "logits": 0.8651944387414311, + "alpha": 0.7050114575518265, + "rms_prompt": 0.005273624788969755, + "rms_gen": 0.024368965532630682, + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "step": 2901500 + }, + "success": true +} diff --git a/docs/artifacts/obligatory_smoke_1k5/code.patch b/docs/artifacts/obligatory_smoke_1k5/code.patch new file mode 100644 index 0000000000000000000000000000000000000000..4b6b37eb58778187f63a4a32fc51b386f39fedc4 --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/code.patch @@ -0,0 +1,295 @@ +diff --git a/src/atom_native.py b/src/atom_native.py +index 6977a9f..d80d03c 100644 +--- a/src/atom_native.py ++++ b/src/atom_native.py +@@ -142,10 +142,36 @@ class AtomSurfaceHead(nn.Module): + self.field_length_skip = nn.Linear(self.field_feat_dim, max_payload_bytes, bias=False) + # softplus(4)≈4.0 — enough for inter-prompt logit cosine << 0.998 at load. + self.skip_gate = nn.Parameter(torch.tensor(1.0)) ++ # Obligatory α readout (main CE path): full-α JL fingerprint → logits. ++ # Frozen random map cannot be CE-collapsed; trainable residual can adapt. ++ # zeros_like(α) ⇒ exact zero branch. Persist/atom_r cannot bypass. ++ self.alpha_only_dim = 2 * d_model ++ self._alpha_flat_dim = int(self.n_modes) * int(d_model) ++ # Fixed JL projection of flattened α (buffer — not trained). ++ jl = torch.empty(self.alpha_only_dim, self._alpha_flat_dim) ++ torch.manual_seed(20260918) ++ nn.init.normal_(jl, mean=0.0, std=(1.0 / self._alpha_flat_dim) ** 0.5) ++ self.register_buffer("alpha_jl", jl, persistent=True) ++ # Frozen random α→logit map (buffer) + trainable adapter. ++ fr_b = torch.empty(max_payload_bytes * 256, self.alpha_only_dim) ++ fr_l = torch.empty(max_payload_bytes, self.alpha_only_dim) ++ nn.init.normal_(fr_b, mean=0.0, std=(1.0 / self.alpha_only_dim) ** 0.5) ++ nn.init.normal_(fr_l, mean=0.0, std=(1.0 / self.alpha_only_dim) ** 0.5) ++ self.register_buffer("alpha_byte_frozen", fr_b, persistent=True) ++ self.register_buffer("alpha_length_frozen", fr_l, persistent=True) ++ self.alpha_byte_proj = nn.Linear(self.alpha_only_dim, max_payload_bytes * 256, bias=False) ++ self.alpha_length_proj = nn.Linear(self.alpha_only_dim, max_payload_bytes, bias=False) ++ # mix_w ∈ [obl_mix_floor, 1] applied to FROZEN branch — CE cannot shut off. ++ self.obl_mix = nn.Parameter(torch.tensor(0.0)) ++ self.obl_mix_floor = 0.35 ++ self.obl_gate = nn.Parameter(torch.tensor(1.0)) # trainable additive scale ++ self.obl_floor = 0.5 ++ self.field_obligatory_readout = False # enabled via AtomNativeModel flag + self.state_norm = nn.LayerNorm(d_model) + self.byte_decoder = nn.Linear(d_model, max_payload_bytes * 256) + self.length_decoder = nn.Linear(d_model, max_payload_bytes) + self._init_field_readout() ++ self._init_obligatory_readout() + + def _init_field_readout(self) -> None: + """Identity-on-mean + std residual; seeded Xavier skips. Safe for fresh + migrate.""" +@@ -170,6 +196,62 @@ class AtomSurfaceHead(nn.Module): + self.field_gate.fill_(2.0) + self.skip_gate.fill_(1.0) + ++ def _init_obligatory_readout(self) -> None: ++ """Seed JL/frozen buffers + trainable adapter (deterministic).""" ++ with torch.no_grad(): ++ gen = torch.Generator(device="cpu") ++ gen.manual_seed(20260918) ++ jl = torch.empty_like(self.alpha_jl, device="cpu") ++ jl.normal_(generator=gen, mean=0.0, std=(1.0 / self._alpha_flat_dim) ** 0.5) ++ self.alpha_jl.copy_(jl.to(device=self.alpha_jl.device, dtype=self.alpha_jl.dtype)) ++ for buf_name, fan_out in ( ++ ("alpha_byte_frozen", self.alpha_byte_frozen.shape[0]), ++ ("alpha_length_frozen", self.alpha_length_frozen.shape[0]), ++ ): ++ buf = getattr(self, buf_name) ++ tmp = torch.empty_like(buf, device="cpu") ++ tmp.normal_( ++ generator=gen, ++ mean=0.0, ++ std=(1.0 / self.alpha_only_dim) ** 0.5, ++ ) ++ buf.copy_(tmp.to(device=buf.device, dtype=buf.dtype)) ++ for module in (self.alpha_byte_proj, self.alpha_length_proj): ++ w = module.weight ++ fan_in = w.shape[1] ++ bound = (6.0 / (fan_in + w.shape[0])) ** 0.5 ++ w.copy_( ++ torch.empty_like(w, device="cpu") ++ .uniform_(-bound, bound, generator=gen) ++ .to(device=w.device, dtype=w.dtype) ++ ) ++ self.obl_gate.fill_(1.0) ++ self.obl_mix.fill_(0.0) ++ ++ def alpha_only_features(self, alpha: torch.Tensor) -> torch.Tensor: ++ """JL fingerprint of full flattened α — no persist/atom_r (zeros stay zeros). ++ ++ mean‖std alone collapses inter-prompt cosine (~0.93) while full α sits ++ near ~0.71; a fixed JL map preserves that separation without new attention. ++ """ ++ flat = alpha.reshape(-1) ++ # Match buffer device/dtype; pad/trim if shape drifts. ++ if flat.numel() < self._alpha_flat_dim: ++ flat = F.pad(flat, (0, self._alpha_flat_dim - flat.numel())) ++ elif flat.numel() > self._alpha_flat_dim: ++ flat = flat[: self._alpha_flat_dim] ++ flat = flat.to(device=self.alpha_jl.device, dtype=self.alpha_jl.dtype) ++ return self.alpha_jl @ flat ++ ++ def obligatory_scale(self) -> torch.Tensor: ++ """softplus(obl_gate) + floor — additive residual cannot reach zero.""" ++ return F.softplus(self.obl_gate) + float(self.obl_floor) ++ ++ def obligatory_mix_weight(self) -> torch.Tensor: ++ """Convex mix weight ∈ [obl_mix_floor, 1] — CE cannot shut α-branch off.""" ++ floor = float(self.obl_mix_floor) ++ return floor + (1.0 - floor) * torch.sigmoid(self.obl_mix) ++ + def field_features( + self, + alpha: torch.Tensor, +@@ -232,7 +314,12 @@ class AtomSurfaceHead(nn.Module): + persistent_state: torch.Tensor | None = None, + atom_r: torch.Tensor | None = None, + ) -> dict[str, torch.Tensor]: +- """Decode from living field α when provided; else legacy mean-state path.""" ++ """Decode from living field α when provided; else legacy mean-state path. ++ ++ When ``field_obligatory_readout`` is on, an α-only residual (mean‖std) ++ is always added into the main CE logits with a non-zero floor scale so ++ persist/atom_r / decoder bias cannot fully bypass living α. ++ """ + if alpha is not None: + feats = self.field_feat_norm( + self.field_features(alpha, persistent_state, atom_r) +@@ -249,10 +336,38 @@ class AtomSurfaceHead(nn.Module): + byte_logits = self.byte_decoder(h).view(self.max_payload_bytes, 256) + length_logits = self.length_decoder(h) + skip = F.softplus(self.skip_gate) +- byte_logits = byte_logits + skip * self.field_byte_skip(feats).view( ++ # When obligatory: skip uses α-only feats (padded) so shared persist/ ++ # atom_r cannot substitute for α inside the skip path either. ++ if self.field_obligatory_readout: ++ a_only = self.alpha_only_features(alpha) ++ a_rms = a_only.pow(2).mean().sqrt().clamp_min(1e-8) ++ a_hat = a_only / a_rms ++ skip_in = F.pad(a_hat, (0, self.field_feat_dim - self.alpha_only_dim)) ++ skip_in = self.field_feat_norm(skip_in) ++ else: ++ skip_in = feats ++ byte_logits = byte_logits + skip * self.field_byte_skip(skip_in).view( + self.max_payload_bytes, 256 + ) +- length_logits = length_logits + skip * self.field_length_skip(feats) ++ length_logits = length_logits + skip * self.field_length_skip(skip_in) ++ if self.field_obligatory_readout: ++ a_only = self.alpha_only_features(alpha) ++ a_rms = a_only.pow(2).mean().sqrt().clamp_min(1e-8) ++ a_hat = a_only / a_rms ++ # Frozen branch (CE cannot collapse) + trainable adapter. ++ frozen_byte = (self.alpha_byte_frozen @ a_hat).view( ++ self.max_payload_bytes, 256 ++ ) ++ frozen_len = self.alpha_length_frozen @ a_hat ++ train_byte = self.alpha_byte_proj(a_hat).view(self.max_payload_bytes, 256) ++ train_len = self.alpha_length_proj(a_hat) ++ mix = self.obligatory_mix_weight() ++ # Hard mix uses FROZEN map so inter-prompt α structure reaches logits. ++ byte_logits = (1.0 - mix) * byte_logits + mix * frozen_byte ++ length_logits = (1.0 - mix) * length_logits + mix * frozen_len ++ obl = self.obligatory_scale() ++ byte_logits = byte_logits + obl * train_byte ++ length_logits = length_logits + obl * train_len + return {"byte_logits": byte_logits, "length_logits": length_logits} + + if state is None: +@@ -383,6 +498,7 @@ class AtomNativeModel(nn.Module): + field_ignorance_margin: float = 0.85, + field_ignorance_ablate_shared: bool = False, + field_ignorance_prompt_bank: bool = False, ++ field_obligatory_readout: bool = False, + slow_rms_rel_tol: float = 0.15, + ) -> None: + super().__init__() +@@ -413,6 +529,8 @@ class AtomNativeModel(nn.Module): + self.field_ignorance_margin = float(field_ignorance_margin) + self.field_ignorance_ablate_shared = bool(field_ignorance_ablate_shared) + self.field_ignorance_prompt_bank = bool(field_ignorance_prompt_bank) ++ self.field_obligatory_readout = bool(field_obligatory_readout) ++ self.surface.field_obligatory_readout = self.field_obligatory_readout + self.slow_rms_rel_tol = float(slow_rms_rel_tol) + self.field_probe = nn.Linear(self.surface.field_feat_dim, self.atomizer.feature_dim) + self.merge_count_total = 0 +@@ -1056,6 +1174,7 @@ class AtomNativeModel(nn.Module): + "field_ignorance_margin": self.field_ignorance_margin, + "field_ignorance_ablate_shared": self.field_ignorance_ablate_shared, + "field_ignorance_prompt_bank": self.field_ignorance_prompt_bank, ++ "field_obligatory_readout": self.field_obligatory_readout, + "merge_count_total": self.merge_count_total, + }, + "field_probe": self.field_probe.state_dict(), +@@ -1078,6 +1197,7 @@ class AtomNativeModel(nn.Module): + # Load matching tensors; activate new field path; damp biases that drown α. + legacy_surface = "state_norm.weight" not in surface_state + field_readout_missing = "field_to_state.weight" not in surface_state ++ obligatory_missing = ("alpha_byte_proj.weight" not in surface_state) or ("alpha_jl" not in surface_state) + current = self.surface.state_dict() + filtered = {key: value for key, value in surface_state.items() if key in current and current[key].shape == value.shape} + missing = [key for key in current if key not in filtered] +@@ -1096,6 +1216,15 @@ class AtomNativeModel(nn.Module): + self.surface.field_feat_norm.reset_parameters() + # Open skip strongly so migrated ckpts separate logits before retrain. + self.surface.skip_gate.fill_(4.0) ++ if obligatory_missing or any( ++ key.startswith("alpha_") or key in {"obl_gate", "obl_mix"} for key in missing ++ ): ++ with torch.no_grad(): ++ self.surface._init_obligatory_readout() ++ # Slight bias damp so fresh α-only residual is audible on load. ++ if not (legacy_surface or field_readout_missing): ++ self.surface.byte_decoder.bias.mul_(0.5) ++ self.surface.length_decoder.bias.mul_(0.5) + core_state = checkpoint["core"] + core = self.core + core.encoder.load_state_dict(core_state["encoder"]) +@@ -1136,6 +1265,10 @@ class AtomNativeModel(nn.Module): + self.field_ignorance_ablate_shared = bool(cfg["field_ignorance_ablate_shared"]) + if "field_ignorance_prompt_bank" in cfg: + self.field_ignorance_prompt_bank = bool(cfg["field_ignorance_prompt_bank"]) ++ if "field_obligatory_readout" in cfg: ++ self.field_obligatory_readout = bool(cfg["field_obligatory_readout"]) ++ # Constructor / CLI may set obligatory after load; always sync surface. ++ self.surface.field_obligatory_readout = bool(self.field_obligatory_readout) + self.merge_count_total = int(cfg.get("merge_count_total", 0) or 0) + # Always repair drifted dynamics (e.g. energy_decay~0.001 from 1.05M persist). + dynamics_state = self.stabilize_dynamics_parameters() +@@ -1145,5 +1278,6 @@ class AtomNativeModel(nn.Module): + training = dict(training) + training["legacy_surface_migrated"] = bool(legacy_surface or missing or field_readout_missing) + training["field_readout_migrated"] = bool(field_readout_missing) ++ training["field_obligatory_migrated"] = bool(obligatory_missing) + training["dynamics_on_load"] = dynamics_state + return training +diff --git a/tools/run_atom_native.py b/tools/run_atom_native.py +index 6122d6b..3d6d0ba 100644 +--- a/tools/run_atom_native.py ++++ b/tools/run_atom_native.py +@@ -304,6 +304,13 @@ def main() -> None: + help="build α_bar from fixed distinct prompts (probe-style), not train ticks " + "(default: off)", + ) ++ parser.add_argument( ++ "--field-obligatory-readout", ++ action=argparse.BooleanOptionalAction, ++ default=False, ++ help="main CE path: α-only residual into surface logits with non-zero floor " ++ "(cannot bypass α via persist/atom_r alone; default: off)", ++ ) + parser.add_argument( + "--slow-every", + type=int, +@@ -412,6 +419,7 @@ def main() -> None: + field_ignorance_margin=float(args.field_ignorance_margin), + field_ignorance_ablate_shared=bool(args.field_ignorance_ablate_shared), + field_ignorance_prompt_bank=bool(args.field_ignorance_prompt_bank), ++ field_obligatory_readout=bool(args.field_obligatory_readout), + slow_rms_rel_tol=float(args.slow_rms_rel_tol), + ) + training_state = None +@@ -432,6 +440,18 @@ def main() -> None: + f"(repaired={dyn_load.get('energy_decay_repaired')}, " + f"bounds={dyn_load.get('energy_decay_bounds')})" + ) ++ # CLI wins over ckpt config for obligatory readout (smoke / migrate). ++ model.field_obligatory_readout = bool(args.field_obligatory_readout) ++ model.surface.field_obligatory_readout = bool(args.field_obligatory_readout) ++ if args.field_obligatory_readout: ++ print( ++ "field_obligatory_readout=ON " ++ f"(migrated={bool((training_state or {}).get('field_obligatory_migrated'))})" ++ ) ++ elif args.field_obligatory_readout: ++ model.field_obligatory_readout = True ++ model.surface.field_obligatory_readout = True ++ print("field_obligatory_readout=ON (fresh)") + surface_lr = ( + float(args.surface_learning_rate) + if args.surface_learning_rate is not None +@@ -514,6 +534,7 @@ def main() -> None: + "field_ignorance_weight": float(args.field_ignorance_weight), + "field_ignorance_ablate_shared": bool(args.field_ignorance_ablate_shared), + "field_ignorance_prompt_bank": bool(args.field_ignorance_prompt_bank), ++ "field_obligatory_readout": bool(args.field_obligatory_readout), + "slow_every": int(args.slow_every), + }, + } +@@ -557,6 +578,7 @@ def main() -> None: + "field_ignorance_weight": float(args.field_ignorance_weight), + "field_ignorance_ablate_shared": bool(args.field_ignorance_ablate_shared), + "field_ignorance_prompt_bank": bool(args.field_ignorance_prompt_bank), ++ "field_obligatory_readout": bool(args.field_obligatory_readout), + "slow_every": int(args.slow_every), + }, + } +@@ -757,6 +779,7 @@ def main() -> None: + field_ignorance_margin=float(args.field_ignorance_margin), + field_ignorance_ablate_shared=bool(args.field_ignorance_ablate_shared), + field_ignorance_prompt_bank=bool(args.field_ignorance_prompt_bank), ++ field_obligatory_readout=bool(args.field_obligatory_readout), + slow_rms_rel_tol=float(args.slow_rms_rel_tol), + ) + reloaded.load(checkpoint_path) diff --git a/docs/artifacts/obligatory_smoke_1k5/migrate_only.json b/docs/artifacts/obligatory_smoke_1k5/migrate_only.json new file mode 100644 index 0000000000000000000000000000000000000000..267aeaa8d21d98cac4df017f703485abadc4360c --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/migrate_only.json @@ -0,0 +1,5 @@ +{ + "logits": 0.7534786422462006, + "alpha": 0.7067174167542339, + "mix": 0.6749999523162842 +} diff --git a/docs/artifacts/obligatory_smoke_1k5/probe_after.txt b/docs/artifacts/obligatory_smoke_1k5/probe_after.txt new file mode 100644 index 0000000000000000000000000000000000000000..0470c6506bcd411155df5ddaafe7a0dffb1adfc1 --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/probe_after.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2901500 +[probe] prompt='Bonjour' + RMS 0.003839 -> 0.023296 (norm 0.2457 -> 1.4910) atoms 3 -> 22 + gen_preview='=E�ki)y��.�kiwx��.�giwx�F.�gi�yG�. ei�xo�. e hxo�,ke myo<\ne i\n e<\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nh ' +[probe] prompt='Qui es-tu ?' + RMS 0.007586 -> 0.025576 (norm 0.4855 -> 1.6369) atoms 7 -> 26 + gen_preview='<\ndei yslizo<\ndei yslizo<\ndei ysaizot\nd i ysaiYo,\nd i ysaiY3,\nd i yva Yoi\nd i yva Y3t\nd i yva Yot\nd i yva Y3i\nd i yvd \n3t\nd i yvd Y3i\nd ieyvd Y3<\nd ieyvd Yo<\nd ' +[probe] prompt='Il était une fois' + RMS 0.005830 -> 0.025307 (norm 0.3731 -> 1.6196) atoms 6 -> 25 + gen_preview='.\nh .\nh .hh .\nhe.hhe.,he hlv.,he.,he.,he.,he.,he.,he.,he.,ee.,ee.,ee..eeahee.heeahke' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003839 -> 0.023296 (norm 0.2457 -> 1.4910) atoms 3 -> 22 + gen_preview='=E�ki)y��.�kiwx��.�giwx�F.�gi�yG�. ei�xo�. e hxo�,ke myo<\ne i\n e<\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nh ' +[probe] mean off-diag cosine logits=0.865194 alpha=0.705011 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/docs/artifacts/obligatory_smoke_1k5/probe_after_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/obligatory_smoke_1k5/probe_after_report.json b/docs/artifacts/obligatory_smoke_1k5/probe_after_report.json new file mode 100644 index 0000000000000000000000000000000000000000..15a146381cfa6808ed9be465e262df6c255fd201 --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/probe_after_report.json @@ -0,0 +1,448 @@ +{ + "timestamp_local": "2026-09-17 19:50:22 PDT", + "timestamp_utc": "2026-09-18T02:50:22.364851+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 16, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "enable_merge": true, + "slow_every": 4, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_contrast_margin": 0.45, + "field_ignorance_weight": 0.0, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "merge_count_total": 0 + }, + "training_meta": { + "step": 2901500, + "run_steps": 1500, + "seed": 20260917, + "episode_reset": false, + "atom_flush_every": 256, + "dynamics_on_load": { + "coupling_scale": 1.9968849420547485, + "energy_decay": 0.45089760422706604, + "phase_sync": 0.5284976363182068, + "energy_decay_before": 0.45089760422706604, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_obligatory/atom_native.pt", + "checkpoint_bytes": 31151849 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.003838988719508052, + "field_norm": 0.2456953078508377, + "field_mean_abs": 0.0024982206523418427, + "field_max_abs": 0.03456147760152817, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.023296494036912918, + "field_norm": 1.4909756183624268, + "field_mean_abs": 0.014416677877306938, + "field_max_abs": 0.18190625309944153, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": "=E\ufffdki)y\ufffd\ufffd.\ufffdkiwx\ufffd\ufffd.\ufffdgiwx\ufffdF.\ufffdgi\ufffdyG\ufffd. ei\ufffdxo\ufffd. e hxo\ufffd,ke myo<\ne i\n e<\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nd <\nh ", + "generated_bytes": 108, + "surface_byte_logits_norm": 176.70263671875 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 7, + "packet_payloads": [ + "Utilisateur:", + " Qui ", + "es-", + "tu ", + "?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.007586084306240082, + "field_norm": 0.4855094254016876, + "field_mean_abs": 0.004466734826564789, + "field_max_abs": 0.04858016222715378, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 7, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.06999999284744263 + }, + "stats_after_gen": { + "field_rms": 0.025576019659638405, + "field_norm": 1.6368649005889893, + "field_mean_abs": 0.015888802707195282, + "field_max_abs": 0.19083331525325775, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 26, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2600000202655792 + }, + "generated_preview": "<\ndei yslizo<\ndei yslizo<\ndei ysaizot\nd i ysaiYo,\nd i ysaiY3,\nd i yva Yoi\nd i yva Y3t\nd i yva Yot\nd i yva Y3i\nd i yvd \n3t\nd i yvd Y3i\nd ieyvd Y3<\nd ieyvd Yo<\nd ", + "generated_bytes": 224, + "surface_byte_logits_norm": 239.43934631347656 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 6, + "packet_payloads": [ + "Utilisateur:", + " Il ", + "\u00e9tait ", + "une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.005830437410622835, + "field_norm": 0.37314799427986145, + "field_mean_abs": 0.003969203215092421, + "field_max_abs": 0.04468633979558945, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 6, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.059999994933605194 + }, + "stats_after_gen": { + "field_rms": 0.025306854397058487, + "field_norm": 1.6196385622024536, + "field_mean_abs": 0.01580897718667984, + "field_max_abs": 0.1667931228876114, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 25, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2500000298023224 + }, + "generated_preview": ".\nh .\nh .hh .\nhe.hhe.,he hlv.,he.,he.,he.,he.,he.,he.,he.,ee.,ee.,ee..eeahee.heeahke", + "generated_bytes": 84, + "surface_byte_logits_norm": 334.5283508300781 + }, + { + "prompt": "Utilisateur: Bonjour\nAssistant:", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.003838988719508052, + "field_norm": 0.2456953078508377, + "field_mean_abs": 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"prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "cosine_alpha": [ + [ + 0.9999997402235061, + 0.5477091765033502, + 0.7408298284529046, + 0.9999997402235061 + ], + [ + 0.5477091765033502, + 0.9999997913057225, + 0.6529909951749429, + 0.5477091765033502 + ], + [ + 0.7408298284529046, + 0.6529909951749429, + 0.9999999274006383, + 0.7408298284529046 + ], + [ + 0.9999997402235061, + 0.5477091765033502, + 0.7408298284529046, + 0.9999997402235061 + ] + ], + "cosine_output_state": [ + [ + 0.9999999900170273, + 0.9622183301250081, + 0.9784209660888536, + 0.9999999900170273 + ], + [ + 0.9622183301250081, + 1.0000000596654306, + 0.9596696285869873, + 0.9622183301250081 + ], + [ + 0.9784209660888536, + 0.9596696285869873, + 0.9999999069111944, + 0.9784209660888536 + ], + [ + 0.9999999900170273, + 0.9622183301250081, + 0.9784209660888536, + 0.9999999900170273 + ] + ], + "cosine_surface_logits": [ + [ + 1.0000000653248073, + 0.7399842337082312, + 0.8921547201586872, + 1.0000000653248073 + ], + [ + 0.7399842337082312, + 0.9999998093867961, + 0.9268886593899424, + 0.7399842337082312 + ], + [ + 0.8921547201586872, + 0.9268886593899424, + 0.9999999555821182, + 0.8921547201586872 + ], + [ + 1.0000000653248073, + 0.7399842337082312, + 0.8921547201586872, + 1.0000000653248073 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.4067135751247406, + 0.25251927971839905, + 0.0 + ], + [ + 0.4067135751247406, + 0.0, + 0.3719652593135834, + 0.4067135751247406 + ], + [ + 0.25251927971839905, + 0.3719652593135834, + 0.0, + 0.25251927971839905 + ], + [ + 0.0, + 0.4067135751247406, + 0.25251927971839905, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.7050114575518265, + "mean_offdiag_cosine_output_state": 0.9734913685052896, + "mean_offdiag_cosine_surface_logits": 0.8651944387414311, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.4067135751247406, + 0.25251927971839905, + 0.0, + 0.3719652593135834, + 0.4067135751247406, + 0.25251927971839905 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.2817384948333104, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 6.315972633785805e-09, + "baseline_mean_mse": 0.0012413040967658162, + "mse_improvement_vs_mean": 0.0012412977807931824, + "pred_target_cosine_per_prompt": [ + 1.0000000432228653, + 0.9999994451029225, + 0.9999995889985599, + 1.0000000432228653 + ], + "mean_pred_target_cosine": 0.9999997801368032, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000757475704, + "per_prompt": [ + 1.0000000993410747, + 1.0000000745058069, + 1.000000029802325, + 1.0000000993410747 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "mean_offdiag_cosine_surface_logits": 0.8651944387414311, + "mean_offdiag_cosine_alpha": 0.7050114575518265, + "mean_field_rms_after_prompt": 0.005273624788969755, + "mean_field_rms_after_20_gen": 0.024368965532630682, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/obligatory_smoke_1k5/run_metrics.json b/docs/artifacts/obligatory_smoke_1k5/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..194a935eee142459d9aaedbb0fc97ed22f8d1096 --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/run_metrics.json @@ -0,0 +1,127 @@ +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 1500, + "start_step": 2900000, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": 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"temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2e547265726472746e64656979722e0a20656965", + "text": ".Trerdrtndeiyr.\n eie", + "reload_text": ".Trerdrtndeiyr.\n eie", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2236352069a16e6f20b0c23665206b777876650a", + "text": "\"65 i\ufffdno \ufffd\ufffd6e kwxve\n", + "reload_text": "\"65 i\ufffdno \ufffd\ufffd6e kwxve\n", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/obligatory_smoke_1k5/train_log.txt b/docs/artifacts/obligatory_smoke_1k5/train_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..7dd05fd71831ab002dd35b4ec4ed6bdd661dabb1 --- /dev/null +++ b/docs/artifacts/obligatory_smoke_1k5/train_log.txt @@ -0,0 +1,144 @@ +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3203231) +resumed weights from checkpoints/atom_native_obligatory/atom_native_src.pt (recorded step=2900000, legacy_surface_migrated=True) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +field_obligatory_readout=ON (migrated=True) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (18 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LayerNorm migration changed bias scale +step=2900001 (run 1/1500) loss=19.63905 byte_ppl=371.923 atoms=1 merges=0 field=0.1144 rms=0.0020 scale=1.0000 fcos=0.533 ign=0.0000 mph=0.000 +step=2900150 (run 150/1500) loss=6.11410 byte_ppl=12.126 atoms=150 merges=0 field=5.9886 rms=0.0936 scale=1.0000 fcos=0.442 ign=0.0000 mph=0.500 +step=2900300 (run 300/1500) loss=6.34541 byte_ppl=24.867 atoms=44 merges=0 field=12.9070 rms=0.2017 scale=1.0000 fcos=0.441 ign=0.0000 mph=0.500 +step=2900450 (run 450/1500) loss=5.55369 byte_ppl=18.262 atoms=194 merges=0 field=23.9956 rms=0.3749 scale=1.0000 fcos=0.416 ign=0.0000 mph=0.500 +step=2900600 (run 600/1500) loss=2.70582 byte_ppl=3.240 atoms=88 merges=0 field=41.0934 rms=0.6421 scale=1.0000 fcos=-0.386 ign=0.0000 mph=0.500 +step=2900750 (run 750/1500) loss=5.33390 byte_ppl=32.511 atoms=238 merges=0 field=67.8665 rms=1.0604 scale=1.0000 fcos=0.435 ign=0.0000 mph=0.500 +step=2900900 (run 900/1500) loss=6.53696 byte_ppl=38.152 atoms=132 merges=0 field=109.2098 rms=1.7064 scale=1.0000 fcos=-0.516 ign=0.0000 mph=0.500 +step=2901050 (run 1050/1500) loss=6.44302 byte_ppl=28.035 atoms=26 merges=0 field=173.0942 rms=2.7046 scale=1.0000 fcos=-0.679 ign=0.0000 mph=0.500 +step=2901200 (run 1200/1500) loss=6.69914 byte_ppl=52.676 atoms=176 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=0.143 ign=0.0000 mph=0.500 +step=2901350 (run 1350/1500) loss=4.03876 byte_ppl=8.220 atoms=70 merges=0 field=191.9999 rms=3.0000 scale=0.9969 fcos=-0.690 ign=0.0000 mph=0.500 +step=2901500 (run 1500/1500) loss=3.74468 byte_ppl=6.494 atoms=220 merges=0 field=191.9998 rms=3.0000 scale=0.9970 fcos=-0.136 ign=0.0000 mph=0.500 +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 1500, + "start_step": 2900000, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.45, + 0.95 + ], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "slow_every": 4 + }, + "train": { + "steps": 1500, + "start_step": 2900000, + "total_steps": 2901500, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 33.635807926999405, + "transitions_per_second": 44.59533135804217, + "first_loss": 19.639047622680664, + "final_loss": 3.744676113128662, + "final_total_perplexity": 42.29530610578538, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0093190670013428, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9969029426574707, + "field_norm_max": 191.99993896484375, + "field_limited_steps": 416, + "field_limited_fraction": 0.2773333333333333, + "final_dynamics": { + "coupling_scale": 1.9968849420547485, + "energy_decay": 0.45089760422706604, + "phase_sync": 0.5284976363182068, + "energy_decay_before": 0.45089760422706604, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.45, + 0.95 + ] + }, + "final_atoms_before_validation": 5, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 8.926763716198149, + "total_perplexity": 7530.853915807848, + "byte_loss": 4.590077218555269, + "byte_perplexity": 98.50203605319966, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_obligatory/atom_native.pt", + "reload": { + "n_atoms": 220, + "field_norm": 191.9998321533203, + "time": 15.000247955322266, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2c223665656e797973763f59903c0a796e206d63", + "text": ",\"6eenyysv?Y\ufffd<\nyn mc", + "reload_text": ",\"6eenyysv?Y\ufffd<\nyn mc", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2e547265726472746e64656979722e0a20656965", + "text": ".Trerdrtndeiyr.\n eie", + "reload_text": ".Trerdrtndeiyr.\n eie", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2236352069a16e6f20b0c23665206b777876650a", + "text": "\"65 i\ufffdno \ufffd\ufffd6e kwxve\n", + "reload_text": "\"65 i\ufffdno \ufffd\ufffd6e kwxve\n", + "reload_match": true + } + } +} diff --git a/docs/artifacts/obligatory_train_25k/before_after.json b/docs/artifacts/obligatory_train_25k/before_after.json new file mode 100644 index 0000000000000000000000000000000000000000..580dbf9462d68a1d153fbf267130747d51a0f34d --- /dev/null +++ b/docs/artifacts/obligatory_train_25k/before_after.json @@ -0,0 +1,31 @@ +{ + "part_a": { + "logits": 0.9799355809256632, + "alpha": 0.7067174167542339, + "rms_prompt": 0.005340076517313719, + "rms_gen": 0.026839961763471365 + }, + "migrate_only": { + "logits": 0.7534786422462006, + "alpha": 0.7067174167542339, + "mix": 0.6749999523162842 + }, + "after_smoke_1k5": { + "logits": 0.8651944387414311, + "alpha": 0.7050114575518265, + "rms_prompt": 0.005273624788969755, + "rms_gen": 0.024368965532630682, + "step": 2901500 + }, + "after_train_25k": { + "logits": 0.9915992667380161, + "alpha": 0.7796559309833486, + "rms_prompt": 0.005149099742993712, + "rms_gen": 0.02898056898266077, + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "step": 2925000 + }, + "success_bar": "logits <= 0.865 and ideally closer to migrate-only 0.753 without killing alpha (~0.70)", + "success": false, + "verdict": "CE re-collapsed obligatory gain: logits 0.865(+1.5k) -> 0.992(+25k); alpha 0.705 -> 0.780" +} diff --git a/docs/artifacts/obligatory_train_25k/chat_samples.txt b/docs/artifacts/obligatory_train_25k/chat_samples.txt new file mode 100644 index 0000000000000000000000000000000000000000..c6801899d1c784ede4b87cd0d31dc2e335582690 --- /dev/null +++ b/docs/artifacts/obligatory_train_25k/chat_samples.txt @@ -0,0 +1,17 @@ +===== PROMPT: Bonjour ===== +Prompt: Bonjour +Response: Ei.-ebigrngh@ ,F11ilyggo k @uEi@,1l lynl@6eyn@@ i +eyls + +===== PROMPT: Qui es-tu ? ===== +Prompt: Qui es-tu ? +Response: "G<.kdoyyavo>k" +ebtlxgvoi k@w2k hxgvo6 k +,F2< +o rxnv 7k .2 kmxdgl k.aednixi +ne irov xk< ael ifed thnv x rhe .ao tgd + +===== PROMPT: Il etait une fois ===== +Prompt: Il etait une fois +Response: AT<-eblyygvh@@ +bw2dauydvh;8elvuhnn @{<@@-b@@@ diff --git a/docs/artifacts/obligatory_train_25k/probe_after.txt b/docs/artifacts/obligatory_train_25k/probe_after.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a0a15737eeeb0b85a877f09a7d2413fd0c05e92 --- /dev/null +++ b/docs/artifacts/obligatory_train_25k/probe_after.txt @@ -0,0 +1,19 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_train/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=2925000 +[probe] prompt='Bonjour' + RMS 0.003939 -> 0.030213 (norm 0.2521 -> 1.9337) atoms 3 -> 22 + gen_preview='E@@@@@@@@@@(ke umnE\n134umn@@@@@@@@' +[probe] prompt='Qui es-tu ?' + RMS 0.006336 -> 0.026201 (norm 0.4055 -> 1.6769) atoms 7 -> 26 + gen_preview='"""@ @he @\ne sxgvh xk @\n,\nh sxdvh xk @@@@@@@@@@' +[probe] prompt='Il était une fois' + RMS 0.006382 -> 0.029294 (norm 0.4084 -> 1.8748) atoms 6 -> 25 + gen_preview='A@\n,@ @@@@@@@@@@@@@@' +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.003939 -> 0.030213 (norm 0.2521 -> 1.9337) atoms 3 -> 22 + gen_preview='E@@@@@@@@@@(ke umnE\n134umn@@@@@@@@' +[probe] mean off-diag cosine logits=0.991599 alpha=0.779656 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/obligatory_train_25k/run_metrics.json b/docs/artifacts/obligatory_train_25k/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..47ccf8d1c6aa51949fdb3fa74c9f2c77a5e95b89 --- /dev/null +++ b/docs/artifacts/obligatory_train_25k/run_metrics.json @@ -0,0 +1,92 @@ +{ + "stream": false, + "data_path": "data/corpus_train_chat.txt", + "data_glob": null, + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt" + ], + "data_bytes": 777806, + "data_characters": 766865, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": 154661, + "train_packet_count": 154597, + "validation_packet_count": 64, + "mean_packet_bytes": 5.029102359353684, + "max_packet_bytes": 17, + "min_packet_bytes": 1, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 25000, + "start_step": 2900000, + "seed": 20260917, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [0.45, 0.95], + "stream": false, + "enable_merge": true, + "field_loss_weight": 0.08, + "field_contrast_weight": 0.45, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "slow_every": 4 + }, + "train": { + "steps": 25000, + "start_step": 2900000, + "total_steps": 2925000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 537.3747444109758, + "transitions_per_second": 46.52246920796931, + "first_loss": 19.60155487060547, + "final_loss": 6.524996280670166, + "final_total_perplexity": 681.977237147694, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.0093843936920166, + "field_rms_after_max": 2.999999523162842, + "field_scale_min": 0.9968813061714172, + "field_norm_max": 191.99998474121094, + "field_limited_steps": 23916, + "field_limited_fraction": 0.95664, + "final_dynamics": { + "coupling_scale": 1.9999505281448364, + "energy_decay": 0.4500320851802826, + "phase_sync": 0.5719871520996094, + "energy_decay_before": 0.4500320851802826, + "energy_decay_repaired": false, + "energy_decay_bounds": [0.45, 0.95] + }, + "final_atoms_before_validation": 5, + "stream": false, + "bytes_seen": 777806 + }, + "validation": { + "transitions": 63, + "loss": 8.034417428667583, + "total_perplexity": 3085.3408876645603, + "byte_loss": 3.945423587920174, + "byte_perplexity": 51.69823222140288, + "source": "held_out_tail" + }, + "checkpoint": "checkpoints/atom_native_obligatory_train/atom_native.pt", + "reload": { + "n_atoms": 168, + "field_norm": 191.9999237060547, + "time": 249.94190979003906, + "finite": true + } +} diff --git a/docs/artifacts/obligatory_train_25k/train_log_excerpt.txt b/docs/artifacts/obligatory_train_25k/train_log_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..89cd8b950c394525f8049f3cfe5ee4f18fc681fd --- /dev/null +++ b/docs/artifacts/obligatory_train_25k/train_log_excerpt.txt @@ -0,0 +1,20 @@ +train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3219767) +resumed weights from checkpoints/atom_native_obligatory_train/atom_native_src.pt (recorded step=2900000, legacy_surface_migrated=True) +dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95)) +field_obligatory_readout=ON (migrated=True) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (18 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0 +optimizer restore skipped: surface LayerNorm migration changed bias scale +... +step=2900001 (run 1/25000) loss=19.60155 byte_ppl=371.923 atoms=1 merges=0 field=0.1144 rms=0.0020 scale=1.0000 fcos=0.533 ign=0.0000 mph=0.000 +step=2900500 (run 500/25000) loss=4.60267 byte_ppl=11.257 atoms=244 merges=0 field=28.9616 rms=0.4525 scale=1.0000 fcos=0.530 ign=0.0000 mph=0.500 +step=2901000 (run 1000/25000) loss=9.27468 byte_ppl=73.311 atoms=232 merges=0 field=148.7115 rms=2.3236 scale=1.0000 fcos=-0.412 ign=0.0000 mph=0.500 +... +step=2912500 (run 12500/25000) loss=4.38200 byte_ppl=10.566 atoms=212 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=-0.613 ign=0.0000 mph=0.500 +step=2913000 (run 13000/25000) loss=5.43893 byte_ppl=19.249 atoms=200 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=-0.872 ign=0.0000 mph=0.500 +step=2913500 (run 13500/25000) loss=4.28339 byte_ppl=4.375 atoms=188 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=0.314 ign=0.0000 mph=0.500 +... +step=2923000 (run 23000/25000) loss=6.57267 byte_ppl=26.010 atoms=216 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=-0.961 ign=0.0000 mph=0.500 +step=2923500 (run 23500/25000) loss=4.43357 byte_ppl=9.010 atoms=204 merges=0 field=191.9999 rms=3.0000 scale=0.9971 fcos=-0.968 ign=0.0000 mph=0.500 +step=2924000 (run 24000/25000) loss=6.74610 byte_ppl=51.426 atoms=192 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=-0.957 ign=0.0000 mph=0.500 +step=2924500 (run 24500/25000) loss=5.77635 byte_ppl=22.874 atoms=180 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=-0.941 ign=0.0000 mph=0.500 +step=2925000 (run 25000/25000) loss=6.52500 byte_ppl=24.835 atoms=168 merges=0 field=191.9999 rms=3.0000 scale=0.9970 fcos=-0.568 ign=0.0000 mph=0.500 diff --git a/docs/artifacts/printable_aux/chunk_50k/chat.txt b/docs/artifacts/printable_aux/chunk_50k/chat.txt new file mode 100644 index 0000000000000000000000000000000000000000..de128e8ad4f4e327f32de821c2e87819e0aa2270 --- /dev/null +++ b/docs/artifacts/printable_aux/chunk_50k/chat.txt @@ -0,0 +1,58 @@ +### Bonjour +Prompt: Bonjour +Response: 'ns nps npu 'Diai.Өa O�s�a!dA'�sj8oa O� + +'� + +ߔM +ߔa +'�s +8�s +'' +?x�sir!d ''sf.�,�.A'bMA'�s?'� +gr!';. �e + +x�a ��u 't +v.Q"eu +�ee +xeMg��d + +### Qui es-tu ? +Prompt: Qui es-tu ? +Response: ߔa i fps 'p� +�pa�Uea +8�a�'�a!'�s s�� +'�� see e s ''a fea 'D�?sea '�s 8�a�s�aie�8i '�� O�aj8ea + +### Il était une fois +Prompt: Il était une fois +Response: a� e� ecr�e�uta!8�see '�e e +'�a +Oe ie Oea een�< 8�e-� 'pa Uea 'DSAO�a '�S 8er Oeaae�8�s 'en s�a!8�a!ߔs oA8p +Oea?O� +ie�d�u + +### Bonjour det +Prompt: Bonjour +Response: 'ns 'ns '�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�s +'�sfr!p� +'�sfr!p� +'�sfr!p� +'�sfr!p� +'�sfr!p�6 +'�sfr!d�6 diff --git a/docs/artifacts/printable_aux/chunk_50k/field_probe_report.json b/docs/artifacts/printable_aux/chunk_50k/field_probe_report.json new file mode 100644 index 0000000000000000000000000000000000000000..38f5fde794ba309d3ae053e4015246f85fae4e6d --- /dev/null +++ b/docs/artifacts/printable_aux/chunk_50k/field_probe_report.json @@ -0,0 +1,450 @@ +{ + "timestamp_local": "2026-09-18 16:08:04 PDT", + "timestamp_utc": "2026-09-18T23:08:04.472384+00:00", + "meta": { + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_payload_bytes": 16, + "atomizer_version": "atomizer-v1-byte-span", + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "enable_merge": true, + "slow_every": 1, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_contrast_margin": 0.55, + "field_ignorance_weight": 0.0, + "field_ignorance_margin": 0.85, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "printable_aux_weight": 0.08, + "merge_count_total": 0 + }, + "training_meta": { + "step": 3325000, + "run_steps": 50000, + "seed": 20260913, + "episode_reset": false, + "atom_flush_every": 256, + "dynamics_on_load": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.3147634267807007, + "energy_decay_before": 0.30000001192092896, + "energy_decay_repaired": false, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + } + }, + "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt", + "checkpoint_bytes": 27365541 + }, + "n_gen": 20, + "prompts": [ + "Bonjour", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Utilisateur: Bonjour\nAssistant:" + ], + "per_prompt": [ + { + "prompt": "Bonjour", + "primed_text": "Utilisateur: Bonjour\nAssistant:", + "n_prompt_packets": 3, + "packet_payloads": [ + "Utilisateur:", + " Bonjour\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.004299768712371588, + "field_norm": 0.27518516778945923, + "field_mean_abs": 0.003115342929959297, + "field_max_abs": 0.03225400671362877, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 3, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.029999999329447746 + }, + "stats_after_gen": { + "field_rms": 0.029990317299962044, + "field_norm": 1.9193801879882812, + "field_mean_abs": 0.021594218909740448, + "field_max_abs": 0.149013951420784, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 22, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2200000286102295 + }, + "generated_preview": " 'ns 'ns '\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffdsfr!p\ufffd\n'\ufffdsfr!p\ufffd", + "generated_bytes": 92, + "surface_byte_logits_norm": 89.47692108154297 + }, + { + "prompt": "Qui es-tu ?", + "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:", + "n_prompt_packets": 7, + "packet_payloads": [ + "Utilisateur:", + " Qui ", + "es-", + "tu ", + "?", + "\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.0066592153161764145, + "field_norm": 0.4261897802352905, + "field_mean_abs": 0.005141429137438536, + "field_max_abs": 0.04921654984354973, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 7, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.06999999284744263 + }, + "stats_after_gen": { + "field_rms": 0.031848110258579254, + "field_norm": 2.0382790565490723, + "field_mean_abs": 0.023297809064388275, + "field_max_abs": 0.17132703959941864, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 26, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.2600000202655792 + }, + "generated_preview": " '\ufffda\n'\ufffda\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'\ufffds\n'ys\n'ys\n'ys\n'es\n'es\n'es\n'es\n'es\n'esir!P\ufffd\"\n'esir!P\ufffd\"", + "generated_bytes": 92, + "surface_byte_logits_norm": 90.03909301757812 + }, + { + "prompt": "Il \u00e9tait une fois", + "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:", + "n_prompt_packets": 6, + "packet_payloads": [ + "Utilisateur:", + " Il ", + "\u00e9tait ", + "une ", + "fois\n", + "Assistant:" + ], + "stats_after_prompt": { + "field_rms": 0.006216552574187517, + "field_norm": 0.3978593349456787, + "field_mean_abs": 0.004740363918244839, + "field_max_abs": 0.04607414826750755, + "alpha_numel": 4096, + "persistence_norm": 0.0, + "persistence_mean_abs": 0.0, + "persistence_strength": 0.0, + "n_atoms": 6, + "consolidation_count": 0, + "abstraction_count": 0, + "t": 0.059999994933605194 + }, + "stats_after_gen": { + "field_rms": 0.031356681138277054, + "field_norm": 2.0068275928497314, + 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0.8666357052871798, + 0.9999999093416008, + 0.8931712837450864, + 0.8666357052871798 + ], + [ + 0.9235450474693955, + 0.8931712837450864, + 1.000000023423159, + 0.9235450474693955 + ], + [ + 0.999999863875923, + 0.8666357052871798, + 0.9235450474693955, + 0.999999863875923 + ] + ], + "cosine_persistence": [ + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ], + [ + null, + null, + null, + null + ] + ], + "l2_alpha": [ + [ + 0.0, + 0.28297609090805054, + 0.21140235662460327, + 0.0 + ], + [ + 0.28297609090805054, + 0.0, + 0.27566051483154297, + 0.28297609090805054 + ], + [ + 0.21140235662460327, + 0.27566051483154297, + 0.0, + 0.21140235662460327 + ], + [ + 0.0, + 0.28297609090805054, + 0.21140235662460327, + 0.0 + ] + ], + "mean_offdiag_cosine_alpha": 0.8365359006504839, + "mean_offdiag_cosine_output_state": 0.8510503917801625, + "mean_offdiag_cosine_surface_logits": 0.9122554421890267, + "mean_offdiag_cosine_persistence": null, + "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state." + }, + "reconstruction": { + "last_k": 4, + "notes": [ + "No MERGE/SPLIT in this architecture yet.", + "No dedicated field\u2192past-packet decoder exists.", + "Consolidation is a single EMA persistence vector, not a packet stack.", + "Linear probe below is few-shot diagnostic on the probe prompts only." + ], + "not_possible_yet": [ + "MERGE of packets into durable field structures", + "SPLIT / dual-clock span control", + "Dedicated field \u2192 past-packet decoder", + "Retrieving arbitrary past payloads from alpha alone as text" + ], + "field_differs_across_prompts": true, + "persistence_differs_across_prompts": false, + "pairwise_alpha_l2": [ + 0.28297609090805054, + 0.21140235662460327, + 0.0, + 0.27566051483154297, + 0.28297609090805054, + 0.21140235662460327 + ], + "pairwise_persistence_l2": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ], + "mean_pairwise_alpha_l2": 0.21073623498280844, + "linear_probe": { + "status": "ok", + "method": "dual_ridge_least_squares", + "lambda": 0.01, + "n_prompts": 4, + "field_dim": 4224, + "feature_dim": 320, + "train_mse": 5.320868149283342e-05, + "baseline_mean_mse": 0.0012413040967658162, + "mse_improvement_vs_mean": 0.0011880954152729828, + "pred_target_cosine_per_prompt": [ + 0.9990714752923866, + 0.9978818230163662, + 0.9959597249060029, + 0.9990714752923866 + ], + "mean_pred_target_cosine": 0.9979961246267856, + "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder." + }, + "alpha_reprime_1nn_accuracy": 0.75, + "atom_collection_probe": { + "status": "ok", + "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000571211198, + "per_prompt": [ + 1.0000000397364335, + 1.0000000596046412, + 1.0000000894069707, + 1.0000000397364335 + ], + "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention." + }, + "reconstruction_succeeds": true, + "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample" + }, + "verdict": { + "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)", + "mean_offdiag_cosine_surface_logits": 0.9122554421890267, + "mean_offdiag_cosine_alpha": 0.8365359006504839, + "mean_field_rms_after_prompt": 0.005368826328776777, + "mean_field_rms_after_20_gen": 0.0307963564991951, + "reconstruction_succeeds": true, + "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm." + } +} diff --git a/docs/artifacts/printable_aux/chunk_50k/probe.txt b/docs/artifacts/printable_aux/chunk_50k/probe.txt new file mode 100644 index 0000000000000000000000000000000000000000..7970f1cb170aef60d7b6c5f30c11f3df025aad40 --- /dev/null +++ b/docs/artifacts/printable_aux/chunk_50k/probe.txt @@ -0,0 +1,21 @@ +[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer) +[probe] d_model=64 n_modes=64 step=3325000 +[probe] prompt='Bonjour' + RMS 0.004300 -> 0.029990 (norm 0.2752 -> 1.9194) atoms 3 -> 22 + gen_preview=" 'ns 'ns '�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�sfr!p�\n'�sfr!p�" +[probe] prompt='Qui es-tu ?' + RMS 0.006659 -> 0.031848 (norm 0.4262 -> 2.0383) atoms 7 -> 26 + gen_preview=' \'�a\n\'�a\n\'�s\n\'�s\n\'�s\n\'�s\n\'�s\n\'�s\n\'�s\n\'�s\n\'ys\n\'ys\n\'ys\n\'es\n\'es\n\'es\n\'es\n\'es\n\'esir!P�"\n\'esir!P�"' +[probe] prompt='Il était une fois' + RMS 0.006217 -> 0.031357 (norm 0.3979 -> 2.0068) atoms 6 -> 25 + gen_preview=" a�s a�a a�a '�a '�a '�a '�a 8�a '�a '�a 8�a '�a U�a U�a U�a U�a U�aaU�aaU�aaU�a" +[probe] prompt='Utilisateur: Bonjour\nAssistant:' + RMS 0.004300 -> 0.029990 (norm 0.2752 -> 1.9194) atoms 3 -> 22 + gen_preview=" 'ns 'ns '�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�sfr!p�\n'�sfr!p�" +[probe] mean off-diag cosine logits=0.912255 alpha=0.836536 +[probe] reconstruction_succeeds=True field_differs=True +[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json +[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md +[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md +[probe] updated /workspace/exports/atom-ai/docs/SCALE.md +[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial) diff --git a/docs/artifacts/printable_aux/chunk_50k/run_metrics.json b/docs/artifacts/printable_aux/chunk_50k/run_metrics.json new file mode 100644 index 0000000000000000000000000000000000000000..67aebc16efbf20b4ab61d392430e401922311ec9 --- /dev/null +++ b/docs/artifacts/printable_aux/chunk_50k/run_metrics.json @@ -0,0 +1,145 @@ +{ + "stream": true, + "data_path": null, + "data_glob": "data/dialogue_shards/part_*", + "shard_paths": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008", + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt" + ], + "data_bytes": 7066157, + "data_characters": null, + "atomizer_version": "atomizer-v1-byte-span", + "feature_dim": 320, + "packet_count": null, + "train_packet_count": null, + "validation_packet_count": 2048, + "mean_packet_bytes": null, + "max_packet_bytes": null, + "min_packet_bytes": null, + "bytes_seen": 524288, + "config": { + "d_model": 64, + "n_modes": 64, + "n_atoms_max": 512, + "max_span_bytes": 16, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "learning_rate": 0.0001, + "surface_learning_rate": 0.0003, + "steps": 50000, + "start_step": 3275000, + "seed": 20260913, + "surface_alphabet": 256, + "field_max_rms": 3.0, + "energy_decay_bounds": [ + 0.3, + 0.95 + ], + "stream": true, + "chunk_bytes": 1048576, + "loop_shards": true, + "stream_buffer": 2048, + "stream_prefetch": true, + "enable_merge": true, + "field_loss_weight": 0.05, + "field_contrast_weight": 0.1, + "field_ignorance_weight": 0.0, + "field_ignorance_ablate_shared": false, + "field_ignorance_prompt_bank": false, + "field_obligatory_readout": true, + "field_obligatory_hard": true, + "printable_aux_weight": 0.08, + "slow_every": 1 + }, + "packets_seen": 97538, + "stream_epoch": 0, + "train": { + "steps": 50000, + "start_step": 3275000, + "total_steps": 3325000, + "episode_length": 512, + "episode_reset": false, + "atom_flush_every": 256, + "elapsed_seconds": 1354.3311098719987, + "transitions_per_second": 36.91859371429903, + "first_loss": 10.914390563964844, + "final_loss": 6.202929973602295, + "final_total_perplexity": 494.1948999059319, + "finite_losses": true, + "finite_parameters": true, + "nan_or_inf": false, + "field_rms_before_max": 3.005934476852417, + "field_rms_after_max": 2.999999761581421, + "field_scale_min": 0.9980254173278809, + "field_norm_max": 191.9999542236328, + "field_limited_steps": 48443, + "field_limited_fraction": 0.96886, + "final_dynamics": { + "coupling_scale": 2.0, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.3147634267807007, + "energy_decay_before": 0.2999386191368103, + "energy_decay_repaired": true, + "energy_decay_bounds": [ + 0.3, + 0.95 + ] + }, + "final_atoms_before_validation": 9, + "stream": true, + "bytes_seen": 524288 + }, + "validation": { + "transitions": 256, + "loss": 7.097687941044569, + "total_perplexity": 1209.168172024888, + "byte_loss": 4.099952200427651, + "byte_perplexity": 60.337403426351045, + "source": "stream_ring" + }, + "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt", + "reload": { + "n_atoms": 80, + "field_norm": 191.99986267089844, + "time": 500.1767883300781, + "finite": true + }, + "generation": { + "The future of AI is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2121726ce74165706d2173c32d0a6f0a65656d21", + "text": "!!rl\ufffdAepm!s\ufffd-\no\neem!", + "reload_text": "!!rl\ufffdAepm!s\ufffd-\no\neem!", + "reload_match": true + }, + "Bonjour, je m'appelle": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "7975706d206136756d6c69a921279471202da82c", + "text": "yupm a6umli\ufffd!'\ufffdq -\ufffd,", + "reload_text": "yupm a6umli\ufffd!'\ufffdq -\ufffd,", + "reload_match": true + }, + "Valkyria Chronicles III is": { + "temperature": 0.8, + "top_k": 5, + "max_length": 20, + "bytes_hex": "2175612175706d70386961203865612075c36121", + "text": "!ua!upmp8ia 8ea u\ufffda!", + "reload_text": "!ua!upmp8ia 8ea u\ufffda!", + "reload_match": true + } + } +} \ No newline at end of file diff --git a/docs/artifacts/printable_aux/chunk_50k/train_excerpt.txt b/docs/artifacts/printable_aux/chunk_50k/train_excerpt.txt new file mode 100644 index 0000000000000000000000000000000000000000..ebf58d2c26672250113412ca1f7690ff31c453b7 --- /dev/null +++ b/docs/artifacts/printable_aux/chunk_50k/train_excerpt.txt @@ -0,0 +1,26 @@ +train lock skipped (--allow-parallel-train) +resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3275000, legacy_surface_migrated=False) +dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95)) +field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP) +printable_aux_weight=0.08 (reward printable mass on hard logits) +optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0 +stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True +optimizer restore skipped: surface LR param groups differ from checkpoint +step=3275001 (run 1/50000) loss=10.91439 byte_ppl=1079.120 atoms=1 merges=0 field=0.1176 rms=0.0021 scale=1.0000 fcos=0.682 ign=0.0000 prn=0.872 mph=0.000 bytes=524288 pkts=97538 shard=0 +step=3275050 (run 50/50000) loss=5.34377 byte_ppl=118.289 atoms=50 merges=0 field=2.1467 rms=0.0336 scale=1.0000 fcos=0.624 ign=0.0000 prn=0.870 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275100 (run 100/50000) loss=6.92580 byte_ppl=82.001 atoms=100 merges=0 field=4.0466 rms=0.0632 scale=1.0000 fcos=0.612 ign=0.0000 prn=0.866 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275150 (run 150/50000) loss=5.42211 byte_ppl=38.444 atoms=150 merges=0 field=5.7777 rms=0.0903 scale=1.0000 fcos=0.603 ign=0.0000 prn=0.867 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275200 (run 200/50000) loss=10.17486 byte_ppl=220.610 atoms=200 merges=0 field=7.5262 rms=0.1176 scale=1.0000 fcos=0.593 ign=0.0000 prn=0.869 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275250 (run 250/50000) loss=7.17716 byte_ppl=49.664 atoms=250 merges=0 field=9.3556 rms=0.1462 scale=1.0000 fcos=0.584 ign=0.0000 prn=0.869 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275300 (run 300/50000) loss=7.72793 byte_ppl=94.430 atoms=44 merges=0 field=11.1587 rms=0.1744 scale=1.0000 fcos=0.574 ign=0.0000 prn=0.871 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275350 (run 350/50000) loss=6.35312 byte_ppl=124.978 atoms=94 merges=0 field=13.4598 rms=0.2103 scale=1.0000 fcos=0.570 ign=0.0000 prn=0.870 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275400 (run 400/50000) loss=5.09693 byte_ppl=26.288 atoms=144 merges=0 field=15.7656 rms=0.2463 scale=1.0000 fcos=0.566 ign=0.0000 prn=0.871 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275450 (run 450/50000) loss=7.82952 byte_ppl=100.950 atoms=194 merges=0 field=18.2326 rms=0.2849 scale=1.0000 fcos=0.563 ign=0.0000 prn=0.871 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275500 (run 500/50000) loss=6.03557 byte_ppl=60.373 atoms=244 merges=0 field=20.9325 rms=0.3271 scale=1.0000 fcos=0.561 ign=0.0000 prn=0.872 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3275550 (run 550/50000) loss=7.32349 byte_ppl=63.898 atoms=38 merges=0 field=23.8672 rms=0.3729 scale=1.0000 fcos=0.559 ign=0.0000 prn=0.873 mph=0.500 bytes=524288 pkts=97538 shard=0 +... +step=3324800 (run 49800/50000) loss=6.83371 byte_ppl=52.222 atoms=136 merges=0 field=191.9999 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 prn=0.890 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3324850 (run 49850/50000) loss=7.66067 byte_ppl=96.315 atoms=186 merges=0 field=191.9999 rms=3.0000 scale=0.9982 fcos=0.550 ign=0.0000 prn=0.890 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3324900 (run 49900/50000) loss=6.09349 byte_ppl=57.939 atoms=236 merges=0 field=191.9999 rms=3.0000 scale=0.9982 fcos=0.550 ign=0.0000 prn=0.890 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3324950 (run 49950/50000) loss=7.01998 byte_ppl=143.181 atoms=30 merges=0 field=191.9999 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 prn=0.890 mph=0.500 bytes=524288 pkts=97538 shard=0 +step=3325000 (run 50000/50000) loss=6.20293 byte_ppl=69.126 atoms=80 merges=0 field=191.9999 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 prn=0.890 mph=0.500 bytes=524288 pkts=97538 shard=0 diff --git a/docs/artifacts/printable_aux/pytest.txt b/docs/artifacts/printable_aux/pytest.txt new file mode 100644 index 0000000000000000000000000000000000000000..74a1b37f9c7a3edb09ff17af31e118731945f5a2 --- /dev/null +++ b/docs/artifacts/printable_aux/pytest.txt @@ -0,0 +1,2 @@ +........ [100%] +8 passed in 1.24s diff --git a/docs/artifacts/printable_aux/pytest_full.txt b/docs/artifacts/printable_aux/pytest_full.txt new file mode 100644 index 0000000000000000000000000000000000000000..e2134b72c81ff89feab7433c800a1874f04c3c0e --- /dev/null +++ b/docs/artifacts/printable_aux/pytest_full.txt @@ -0,0 +1,2 @@ +...............................s............... [100%] +46 passed, 1 skipped in 3.61s diff --git a/docs/artifacts/root_cause/atom_diag.json b/docs/artifacts/root_cause/atom_diag.json new file mode 100644 index 0000000000000000000000000000000000000000..45e0ae2b015e7c1dd0f3cf0dde4c142e690b4857 --- /dev/null +++ b/docs/artifacts/root_cause/atom_diag.json @@ -0,0 +1,106 @@ +{ + "val2048_ce_train_labels": 1.2471501433821601, + "val2048_ce_gen_labels": 3.489207078371329, + "P(next==input | input is space/punct) train-label": 0.00022220478790635267, + "P(next==input | input is space/punct) gen-label": 0.7932385270193427, + "corpus P(next==input | space/punct)": 0.0, + "efference_argmax_acc_all": 0.75244140625, + "efference_argmax_acc_when_target_space_punct": 0.8051643192488263, + "perturbation_KL_by_lag": { + "normal": { + "1": 7.563288368284702, + "2": 4.332693288591504, + "3": 0.5186640677547265, + "4": 0.28677583388096356, + "6": 0.13789069090411962, + "8": 0.08064216026137287, + "12": 0.05657446289211343, + "16": 0.007557341790871826, + "24": 0.0003628401454953088, + "32": 8.886801428234041e-05, + "48": 6.453894268853427e-07, + "64": 1.0171765136198404e-08 + }, + "field_alone": { + "1": 0.8334241298337778, + "2": 0.3138229798823886, + "3": 0.27025706580025144, + "4": 0.2091712161588172, + "6": 0.05581894152540675, + "8": 0.04037778945833755, + "12": 0.010343110077883466, + "16": 0.0015113500040039678, + "24": 0.0004311490147725176, + "32": 3.1171161309314264e-05, + "48": 8.987319392398756e-08, + "64": 2.4325379636517635e-08 + } + }, + "atomizer_feature_diff_by_lag": { + "1": 0.15000000596046448, + "2": 0.141309916973114, + "4": 0.0921187698841095, + "8": 0.04808657988905907, + "16": 0.013103140518069267, + "32": 0.0009729340672492981, + "64": 5.364418029785156e-06 + }, + "grad_norm_wrt_atom_at_lag (lag0=current input)": { + "0": 1.933836281299591, + "1": 0.0, + "2": 0.0, + "4": 0.0, + "8": 0.0, + "16": 0.0, + "32": 0.0, + "64": 0.0 + }, + "params_total": 479516, + "params_requires_grad": 266796, + "params_receiving_grad": 163396, + "params_receiving_grad_list": { + "core.dynamics.dynamics.coupling_scale": 1, + "core.dynamics.dynamics.energy_decay": 1, + "core.dynamics.dynamics.phase_sync": 1, + "compiler.mapping.0.weight": 20480, + "compiler.mapping.0.bias": 64, + "compiler.mapping.2.weight": 16384, + "compiler.mapping.2.bias": 256, + "surface.obl_gate": 1, + "surface.field_feat_norm.weight": 128, + "surface.field_feat_norm.bias": 128, + "surface.alpha_byte_proj.fc1.weight": 8192, + "surface.alpha_byte_proj.fc1.bias": 128, + "surface.alpha_byte_proj.fc2.weight": 32768, + "surface.last_atom.byte_embed.weight": 8192, + "surface.last_atom.expand.weight": 16384, + "surface.last_atom.expand.bias": 256, + "surface.last_atom.contract.weight": 8192, + "surface.last_atom.contract.bias": 32, + "surface.last_atom.phase_proj.weight": 2048, + "surface.last_atom.phase_proj.bias": 32, + "surface.last_atom.head.weight": 8192, + "surface.last_atom.head.bias": 256, + "field_probe.weight": 40960, + "field_probe.bias": 320 + }, + "params_requires_grad_but_zero_grad": { + "compiler.operation_gate.weight": 2240, + "compiler.operation_gate.bias": 7, + "surface.payload_copy_scale": 1, + "surface.field_hard_couple_byte.weight": 32768, + "surface.field_hard_couple_length.weight": 128, + "surface.alpha_length_proj.fc1.weight": 8192, + "surface.alpha_length_proj.fc1.bias": 128, + "surface.alpha_length_proj.fc2.weight": 128, + "surface.state_norm.weight": 32, + "surface.state_norm.bias": 32, + "surface.byte_embed.weight": 8192, + "surface.payload_alpha_gate.weight": 2048, + "surface.payload_to_byte.weight": 8192, + "surface.payload_to_length.weight": 32, + "field_next_probe.weight": 40960, + "field_next_probe.bias": 320 + }, + "ce_only_note": "field_probe/field_next_probe get grad only from the 0.05 field aux loss, not from CE" +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/atom_diag_log.txt b/docs/artifacts/root_cause/atom_diag_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..fd0b4d86767a3bd5ad27f74c043a2a59bc6426c2 --- /dev/null +++ b/docs/artifacts/root_cause/atom_diag_log.txt @@ -0,0 +1,14 @@ +{ + "val2048_ce_train_labels": 1.2471501433821601, + "val2048_ce_gen_labels": 3.489207078371329, + "P(next==input | input is space/punct) train-label": 0.00022220478790635267, + "P(next==input | input is space/punct) gen-label": 0.7932385270193427, + "corpus P(next==input | space/punct)": 0.0, + "efference_argmax_acc_all": 0.75244140625, + "efference_argmax_acc_when_target_space_punct": 0.8051643192488263 +} 241s +normal {1: 7.5633, 2: 4.3327, 3: 0.5187, 4: 0.2868, 6: 0.1379, 8: 0.0806, 12: 0.0566, 16: 0.0076, 24: 0.0004, 32: 0.0001, 48: 0.0, 64: 0.0} +field_alone {1: 0.8334, 2: 0.3138, 3: 0.2703, 4: 0.2092, 6: 0.0558, 8: 0.0404, 12: 0.0103, 16: 0.0015, 24: 0.0004, 32: 0.0, 48: 0.0, 64: 0.0} +grad reach {0: 1.933836281299591, 1: 0.0, 2: 0.0, 4: 0.0, 8: 0.0, 16: 0.0, 32: 0.0, 64: 0.0} +{"params_total": 479516, "params_requires_grad": 266796, "params_receiving_grad": 163396} +dead: {'compiler.operation_gate.weight': 2240, 'compiler.operation_gate.bias': 7, 'surface.payload_copy_scale': 1, 'surface.field_hard_couple_byte.weight': 32768, 'surface.field_hard_couple_length.weight': 128, 'surface.alpha_length_proj.fc1.weight': 8192, 'surface.alpha_length_proj.fc1.bias': 128, 'surface.alpha_length_proj.fc2.weight': 128, 'surface.state_norm.weight': 32, 'surface.state_norm.bias': 32, 'surface.byte_embed.weight': 8192, 'surface.payload_alpha_gate.weight': 2048, 'surface.payload_to_byte.weight': 8192, 'surface.payload_to_length.weight': 32, 'field_next_probe.weight': 40960, 'field_next_probe.bias': 320} diff --git a/docs/artifacts/root_cause/common.py b/docs/artifacts/root_cause/common.py new file mode 100644 index 0000000000000000000000000000000000000000..e6aed5a0cf54db70f04d4513d0805cde99962213 --- /dev/null +++ b/docs/artifacts/root_cause/common.py @@ -0,0 +1,31 @@ +"""Shared helpers for the root-cause diagnostic (docs/ROOT_CAUSE.md).""" +import sys +from pathlib import Path + +import torch + +ROOT = Path(__file__).resolve().parents[3] +sys.path.insert(0, str(ROOT)); sys.path.insert(0, str(ROOT / "tools")) +from chat_atom_native import load_model # noqa: E402,F401 +from src.io.atomizer import Atomizer # noqa: E402,F401 + +CKPT = str(ROOT / "checkpoints/byte_tick_fieldsat/atom_native_step_4996000_d32_ms1M_lrd_b4828_fieldsat.pt") +PROMPTS = ["Bonjour, comment ça va ?", "Qui es-tu ?", "Il était une fois"] +OFFSETS = [("data/corpus_fr_medium.txt", o) for o in (50_000, 200_000, 400_000)] + [("data/corpus_fr_medium_s21.txt", 250_000)] +N = 512 + + +def val_windows_bytes(): + """Exactly the 2048-transition val of docs/artifacts/field_leak_spectrum/eval_windows.py: + 4 windows, text=raw[off:off+2048] decoded ignore, first 513 bytes (byte-tick packets).""" + out = [] + for p, off in OFFSETS: + raw = (ROOT / p).read_bytes() + text = raw[off: off + 4 * N].decode("utf-8", errors="ignore") + b = text.encode("utf-8")[: N + 1] + out.append(b) + return out + + +def corpus_bytes(): + return b"".join((ROOT / f).read_bytes() for f in ("data/corpus_fr_medium.txt", "data/corpus_fr_medium_s21.txt")) diff --git a/docs/artifacts/root_cause/decode_consistency.json b/docs/artifacts/root_cause/decode_consistency.json new file mode 100644 index 0000000000000000000000000000000000000000..b68e0ebb531b2a02fc287b7fd6b34622a604ec65 --- /dev/null +++ b/docs/artifacts/root_cause/decode_consistency.json @@ -0,0 +1,4333 @@ +{ + "ckpt": "/workspace/exports/atom-ai/checkpoints/byte_tick_fieldsat/atom_native_step_4996000_d32_ms1M_lrd_b4828_fieldsat.pt", + "A_original": [ + { + "prompt": "Bonjour, comment ça va ?", + "gold": "Ça va très bien, et toi ?\n", + "n_steps": 77, + "n_prompt_bytes": 50, + "max_logit_diff_prompt_part": 0.0, + "max_logit_diff_reply_part": 37.44690704345703, + "n_mismatch_steps(>1e-4)": 24, + "first_mismatch_step": 53, + "first_mismatch_input_byte": " ", + 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Et toi ?\n", + "n_steps": 73, + "n_prompt_bytes": 41, + "max_logit_diff_prompt_part": 0.0, + "max_logit_diff_reply_part": 0.0, + "n_mismatch_steps(>1e-4)": 0, + "first_mismatch_step": null, + "first_mismatch_input_byte": null, + "packet_feature_mismatch_bytes": [], + "boundaries_tf_vs_gen_at_mismatch": [], + "reply_ce_teacher_forced": 4.601751358285555, + "reply_ce_gen_path_forced": 4.601751358285555 + } +] +{ + "Bonjour, comment ça va ?": [ + "Je suis faisir, continuon.\n\n", + "Je vais d'accord ?\nAssistant: Je vais réfléchir.\n\n", + "Je suis préfléchir.\n\n", + "Je vais bien, je vais le le ce ?\nAssistant: Peut-être un parle t'écoute.\n\n", + "Peut-être t'écoute.\n\n", + "Je t'écoute.\n\n", + "Oui, je vais bieni ?\nAssistant: Peut-être lus.\n\n", + "Je vais réfléchir.\n\n" + ], + "Qui es-tu ?": [ + "Oui, je veux qu'on mais claisir, continuon, je vais réfléchir.\n\n", + "Je vais d'accord ?\nAssistant: Je vais réfléchir.\n\n", + "Je suis préfléchir.\n\n", + "Je vais réfléchir.\n\n", + "Oui, je veux qu'on parle mais et mait.\n\n", + "Je ques d'accord ?\nAssistant: Peut-être ce tu proposes ?\nAssistant: Je vais réfléchir.\n\n", + "Peut-être ce ?\nAssistant: Je ends d'accord ?\nAssistant: Peut-être ce prends d'accord avec toi.", + "Je vais réfléchir.\n\n" + ], + "Il était une fois": [ + "Je vais d'accord ?\nAssistant: Je ques ?\nAssistant: Avec plaisir, coute.\n\n", + "Je vais d'accord ?\nAssistant: Je vais réfléchir.\n\n", + "Je suis préfléchir.\n\n", + "Je vais ci.\n\n", + "Oui, je veux qu'on parle mais et mait.\n\n", + "Je vais d'accord avec toi.\n\n", + "Peut-être ce ?\nAssistant: Je ends d'accord ?\nAssistant: Peut-être ce prends d'accord avec toi.", + "Je vais réfléchir.\n\n" + ] +} {'chars': 1012, 'punct': 83, 'doubled_punct_pairs': 0} +{ + "Bonjour, comment ça va ?": [ + "Je suis faisir, continuon.\n\n", + "Je vais d'accord ?\nAssistant: Je vais réfléchir.\n\n", + "Je suis préfléchir.\n\n", + "Je vais bien, je vais le le ce vaist ça vvec plaisir, continuons.\n\n", + "Peut-être t'écoute.\n\n", + "Je t'écoute.\n\n", + "Oui, je vais bieni ?\nAssistant: Peut-être lus.\n\n", + "Je vais réfléchir.\n\n" + ], + "Qui es-tu ?": [ + "Oui, je veux qu'on mais claisir, continuon, je vais réfléchir.\n\n", + "Je vais d'accord ?\nAssistant: Je vais réfléchir.\n\n", + "Je suis préfléchir.\n\n", + "Je vais réfléchir.\n\n", + "Oui, je veux qu'on parle mais et mait.\n\n", + "Je ques d'accord ?\nAssistant: Peut-être ce tu proposes ?\nAssistant: Je vais réfléchir.\n\n", + "Peut-être ce ?\nAssistant: Je ends d'accord ?\nAssistant: Peut-être ce prends d'accord avec toi.", + "Je vais réfléchir.\n\n" + ], + "Il était une fois": [ + "Je vais d'accord ?\nAssistant: Je ques ?\nAssistant: Avec plaisir, coute.\n\n", + "Je vais d'accord ?\nAssistant: Je vais réfléchir.\n\n", + "Je suis préfléchir.\n\n", + "Je vais ci.\n\n", + "Oui, je veux qu'on parle mais et mait.\n\n", + "Je vais d'accord avec toi.\n\n", + "Peut-être ce ?\nAssistant: Je ends d'accord ?\nAssistant: Peut-être ce prends d'accord avec toi.", + "Je vais réfléchir.\n\n" + ] +} {'chars': 1005, 'punct': 80, 'doubled_punct_pairs': 0} diff --git a/docs/artifacts/root_cause/diag_atom_more.py b/docs/artifacts/root_cause/diag_atom_more.py new file mode 100644 index 0000000000000000000000000000000000000000..03ddfa65fc574b19e5f19316238a795e0781291b --- /dev/null +++ b/docs/artifacts/root_cause/diag_atom_more.py @@ -0,0 +1,135 @@ +"""(2b/3) ATOM @4996k: label-copy effect, efference target audit, context sensitivity, +gradient reachability, params that receive gradient, val CE under TF vs gen-labelled inputs.""" +import copy, json, math, random, sys, time +from pathlib import Path +import torch, torch.nn.functional as F +sys.path.insert(0, str(Path(__file__).resolve().parent)) +from common import CKPT, load_model, val_windows_bytes +from src.io.atomizer import Atomizer +OUT = Path(__file__).resolve().parent +torch.set_num_threads(2) +SP = set(b" ,.-'?!:;") + + +def packets_train(m, b): # byte-tick encode (== training stream / eval_windows) + return m.atomizer.encode_bytes(b, reset=True) + + +def packets_gen_labelled(m, b): # same bytes committed like generate_packets does (packet_from_payload) + m.atomizer.reset(); return [m.atomizer.packet_from_payload(bytes([x])) for x in b] + + +@torch.no_grad() +def run_logp(m, pk): + m.eval(); m.reset_state(reset_atomizer=False) + return [torch.log_softmax(m.forward_packet(p)["surface"]["byte_logits"][0], -1) for p in pk[:-1]] + + +def main(): + m = load_model(CKPT); wins = val_windows_bytes(); res = {} + t0 = time.time() + # --- val CE: train labels vs generation labels (same bytes) + label->copy effect + ce_tr, ce_gl = [], []; copy_tr = {"n": 0, "p_same": 0.0}; copy_gl = {"n": 0, "p_same": 0.0} + eff = {"all": [0, 0], "space_punct": [0, 0], "copy_pairs_after_correct": 0} + for w in wins: + lt = run_logp(m, packets_train(m, w)); lg = run_logp(m, packets_gen_labelled(m, w)) + for i in range(len(w) - 1): + ce_tr.append(-float(lt[i][w[i + 1]])); ce_gl.append(-float(lg[i][w[i + 1]])) + if w[i] in SP: + copy_tr["n"] += 1; copy_tr["p_same"] += float(lt[i][w[i]].exp()) + copy_gl["n"] += 1; copy_gl["p_same"] += float(lg[i][w[i]].exp()) + # efference audit: efference_loss feeds argmax prediction of byte i+1 as INPUT and + # trains on target byte i+1 -> (input, target) identical whenever argmax is right. + pred = int(lt[i].argmax()); ok = pred == w[i + 1] + eff["all"][0] += ok; eff["all"][1] += 1 + if w[i + 1] in SP: eff["space_punct"][0] += ok; eff["space_punct"][1] += 1 + res["val2048_ce_train_labels"] = sum(ce_tr) / len(ce_tr) + res["val2048_ce_gen_labels"] = sum(ce_gl) / len(ce_gl) + res["P(next==input | input is space/punct) train-label"] = copy_tr["p_same"] / copy_tr["n"] + res["P(next==input | input is space/punct) gen-label"] = copy_gl["p_same"] / copy_gl["n"] + # empirical base rate in corpus text of a doubled space/punct + dbl = sum(1 for w in wins for i in range(len(w) - 1) if w[i] in SP and w[i + 1] == w[i]) + res["corpus P(next==input | space/punct)"] = dbl / copy_tr["n"] + res["efference_argmax_acc_all"] = eff["all"][0] / eff["all"][1] + res["efference_argmax_acc_when_target_space_punct"] = eff["space_punct"][0] / eff["space_punct"][1] + print(json.dumps(res, indent=1), f"{time.time()-t0:.0f}s", flush=True) + + # --- context sensitivity: perturb one ASCII letter at p, KL at lag L (target p+L predicted after byte p+L-1) + lags = [1, 2, 3, 4, 6, 8, 12, 16, 24, 32, 48, 64] + rng = random.Random(0); sens = {} + for mode in ("normal", "field_alone"): + m.surface.last_atom_force_off = mode == "field_alone" + kl = {L: [] for L in lags}; npts = 0 + for w in wins: + cands = [p for p in range(64, 440) if 97 <= w[p] <= 122] + for p in rng.sample(cands, 6): + wp = bytearray(w); wp[p] = rng.choice([c for c in range(97, 123) if c != w[p]]) + seg, segp = bytes(w[: p + 66]), bytes(wp[: p + 66]) + a = run_logp(m, packets_train(m, seg)); b = run_logp(m, packets_train(m, segp)) + for L in lags: + i = p + L - 1 # logits index predicting byte p+L + kl[L].append(float((a[i].exp() * (a[i] - b[i])).sum())); npts += 1 + sens[mode] = {L: sum(v) / len(v) for L, v in kl.items()} + print(mode, {L: round(x, 4) for L, x in sens[mode].items()}, flush=True) + m.surface.last_atom_force_off = False + res["perturbation_KL_by_lag"] = sens + + # --- atomizer-only context: how far back does a byte change the INPUT FEATURES (context_group EMA)? + w = wins[0]; p = 100; wp = bytearray(w); wp[p] = ord("z") if w[p] != ord("z") else ord("q") + fa = packets_train(m, bytes(w[:170])); fb = packets_train(m, bytes(wp[:170])) + res["atomizer_feature_diff_by_lag"] = {L: float((fa[p + L].features - fb[p + L].features).abs().max()) for L in (1, 2, 4, 8, 16, 32, 64)} + + # --- gradient reachability in TRAIN mode (recipe path): which past atoms get d(loss_t)/d(atom)? + mt = load_model(CKPT); mt.train(); mt.surface.last_atom_dropout = 0.0 + stash = []; orig = mt.compiler.forward + def hooked(features, atom_count=0): + atom, op, conf = orig(features, atom_count) + for name in ("r", "phi", "omega", "E", "kappa"): + getattr(atom, name).retain_grad() + stash.append(atom); return atom, op, conf + mt.compiler.forward = hooked + mt.reset_state(reset_atomizer=True); pk = packets_train(mt, wins[1][:201]) + for q in pk[:199]: + out = mt.forward_packet(q) + out = mt.forward_packet(pk[199]) + loss = F.cross_entropy(out["surface"]["byte_logits"], torch.tensor([pk[200].payload[0]])) + loss.backward() + reach = {} + for L in (0, 1, 2, 4, 8, 16, 32, 64): + a = stash[199 - L] + reach[L] = sum(float(getattr(a, n).grad.norm()) if getattr(a, n).grad is not None else 0.0 for n in ("r", "phi", "omega", "E", "kappa")) + res["grad_norm_wrt_atom_at_lag (lag0=current input)"] = reach + print("grad reach", reach, flush=True) + + # --- which trainable params receive gradient under the recipe (200 train steps, dropout .5, eff every 10, field loss .05) + mg = load_model(CKPT); mg.train() + mg.surface.last_atom_dropout = 0.5; mg.field_loss_weight = 0.05; mg._efference_every = 10 + names = {n: p for n, p in mg.named_parameters() if p.requires_grad} + acc = {n: 0.0 for n in names} + mg.reset_state(reset_atomizer=True); pk = packets_train(mg, wins[2]) + for s in range(1, 201): + for p_ in names.values(): p_.grad = None + if s % 10 == 0: + loss, info = mg.efference_loss(pk[s - 1], pk[s]) + else: + loss, info = mg.transition_loss(pk[s - 1], pk[s]) + loss.backward() + for n, p_ in names.items(): + if p_.grad is not None: acc[n] += float(p_.grad.abs().sum()) + tot = sum(p.numel() for p in mg.parameters()) + live = {n: names[n].numel() for n in names if acc[n] > 0} + dead = {n: names[n].numel() for n in names if acc[n] == 0} + ce_path = {"ce_only_note": "field_probe/field_next_probe get grad only from the 0.05 field aux loss, not from CE"} + res["params_total"] = tot + res["params_requires_grad"] = sum(p.numel() for p in names.values()) + res["params_receiving_grad"] = sum(live.values()) + res["params_receiving_grad_list"] = live + res["params_requires_grad_but_zero_grad"] = dead + res.update(ce_path) + print(json.dumps({k: res[k] for k in ("params_total", "params_requires_grad", "params_receiving_grad")}), flush=True) + print("dead:", dead, flush=True) + (OUT / "atom_diag.json").write_text(json.dumps(res, indent=1)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/root_cause/diag_decode.py b/docs/artifacts/root_cause/diag_decode.py new file mode 100644 index 0000000000000000000000000000000000000000..64d99f6d8210eed5efb711060ca335afa97cfd6a --- /dev/null +++ b/docs/artifacts/root_cause/diag_decode.py @@ -0,0 +1,140 @@ +"""(2) Train/generation consistency of ATOM @4996k. +A. teacher-forced path (Atomizer.encode of whole text, forward_packet per byte == eval_windows/transition_loss) + vs the generate_packets path with the continuation FORCED (same calls as src/atom_native.py:2258-2307, + i.e. prompt encode + packet_from_payload(gold byte)). Compare raw logits per step + packet features. +B. same with packet_from_payload boundary patched to the train-time label (diagnostic monkeypatch only). +C. chat samples (exact probe settings) original vs patched, doubled-punctuation rate. +""" +import json, sys, re +from pathlib import Path +import torch +sys.path.insert(0, str(Path(__file__).resolve().parent)) +from common import CKPT, PROMPTS, load_model +from src.io.atomizer import Atomizer +from src.speech_lock import format_dialogue_prompt +OUT = Path(__file__).resolve().parent +torch.set_num_threads(1) + +CASES = [("Bonjour, comment ça va ?", "Ça va très bien, et toi ?\n"), + ("Qui es-tu ?", "Je suis Atom, un petit modèle qui apprend à parler.\n"), + ("Il était une fois", "Il était une fois un petit robot qui apprenait des mots.\n"), + ("Tu habites où ?", "J'habite à Strasbourg. Et toi ?\n")] +ORIG_INFER = Atomizer._infer_commit_boundary.__func__ + + +def train_like_boundary(cls, payload): # what encode() emits for a 1-byte packet in byte-tick + return "newline" if payload[-1] in (10, 13) else "max_span" + + +@torch.no_grad() +def tf_logits(m, text): + m.eval(); m.reset_state(reset_atomizer=True) + pk = m.atomizer.encode(text, reset=True) + return [m.forward_packet(p)["surface"]["byte_logits"][0].clone() for p in pk[:-1]], pk + + +@torch.no_grad() +def gen_forced_logits(m, prompt, gold: bytes): + m.eval(); m.surface.set_obligatory_hard(True); m.surface.payload_enabled = False + m.reset_state(reset_atomizer=True) + wrapped = format_dialogue_prompt(prompt) + pp = m.atomizer.encode(wrapped, reset=True) + logits, pkts = [], list(pp) + for p in pp[:-1]: + logits.append(m.forward_packet(p)["surface"]["byte_logits"][0].clone()) + cur = pp[-1] + for b in gold: + logits.append(m.forward_packet(cur)["surface"]["byte_logits"][0].clone()) + cur = m.atomizer.packet_from_payload(bytes([b])); pkts.append(cur) + return logits, wrapped, pkts + + +def compare(m, tag): + rows = [] + for prompt, gold in CASES: + g = gold.encode() + lg_g, wrapped, pk_g = gen_forced_logits(m, prompt, g) + full = wrapped + gold + lg_t, pk_t = tf_logits(m, full) + fb = full.encode(); n0 = len(wrapped.encode()) + n = min(len(lg_t), len(lg_g)) + diffs = [float((lg_t[i] - lg_g[i]).abs().max()) for i in range(n)] + ce_t = [float(-torch.log_softmax(lg_t[i], -1)[fb[i + 1]]) for i in range(n)] + ce_g = [float(-torch.log_softmax(lg_g[i], -1)[fb[i + 1]]) for i in range(n)] + feat = [float((pk_t[i].features - pk_g[i].features).abs().max()) for i in range(min(len(pk_t), len(pk_g)))] + bad = [i for i in range(n) if diffs[i] > 1e-4] + first = bad[0] if bad else None + rows.append({ + "prompt": prompt, "gold": gold, "n_steps": n, "n_prompt_bytes": n0, + "max_logit_diff_prompt_part": max(diffs[:n0 - 1]) if n0 > 1 else 0.0, + "max_logit_diff_reply_part": max(diffs[n0 - 1:]), + "n_mismatch_steps(>1e-4)": len(bad), + "first_mismatch_step": first, + "first_mismatch_input_byte": (chr(fb[first]) if first is not None else None), + "packet_feature_mismatch_bytes": [chr(fb[i]) for i, d in enumerate(feat) if d > 1e-6], + "boundaries_tf_vs_gen_at_mismatch": [(chr(fb[i]), pk_t[i].boundary, pk_g[i].boundary) for i, d in enumerate(feat) if d > 1e-6][:12], + "reply_ce_teacher_forced": sum(ce_t[n0 - 1:]) / len(ce_t[n0 - 1:]), + "reply_ce_gen_path_forced": sum(ce_g[n0 - 1:]) / len(ce_g[n0 - 1:]), + "per_step": [(chr(fb[i]) if fb[i] < 128 else f"0x{fb[i]:02x}", round(diffs[i], 4), round(ce_t[i], 3), round(ce_g[i], 3), + # top-3 next byte under gen path + [chr(int(j)) if int(j) < 128 else f"0x{int(j):02x}" for j in torch.topk(lg_g[i], 3).indices]) + for i in range(n0 - 1, n)], + }) + print(tag, json.dumps([{k: v for k, v in r.items() if k != "per_step"} for r in rows], ensure_ascii=False, indent=1), flush=True) + return rows + + +def chat_samples(m, seeds=range(8)): + out = {} + for p in PROMPTS: + out[p] = [] + for s in seeds: + torch.manual_seed(s) + raw = m.generate_packets(p, max_packets=96, temperature=0.8, top_k=12, deterministic=False, + max_length=100, prefer_printable=True, reset=True, merge_enabled=False, speech_gate=True) + out[p].append(raw.decode("utf-8", "replace")) + return out + + +def chat_samples_nogate(m, seeds=range(8)): + out = {} + for p in PROMPTS: + out[p] = [] + for s in seeds: + torch.manual_seed(s) + raw = m.generate_packets(p, max_packets=96, temperature=0.8, top_k=12, deterministic=False, + max_length=100, prefer_printable=True, reset=True, merge_enabled=False, + speech_gate=False, anti_repeat=False) + out[p].append(raw.decode("utf-8", "replace")) + return out + + +def doubled_rate(samples): + txt = "".join(s for v in samples.values() for s in v) + punct = sum(1 for c in txt if c in ",.-'?!:;") + dbl = len(re.findall(r"([,.\-'?!:;])\1", txt)) + return {"chars": len(txt), "punct": punct, "doubled_punct_pairs": dbl} + + +def main(): + m = load_model(CKPT) + res = {"ckpt": CKPT} + res["A_original"] = compare(m, "A original") + res["C_chat_original"] = chat_samples(m); res["C_rate_original"] = doubled_rate(res["C_chat_original"]) + res["C_chat_original_nogate"] = chat_samples_nogate(m); res["C_rate_original_nogate"] = doubled_rate(res["C_chat_original_nogate"]) + print(json.dumps(res["C_chat_original"], ensure_ascii=False, indent=1), res["C_rate_original"], flush=True) + print(json.dumps(res["C_chat_original_nogate"], ensure_ascii=False, indent=1), res["C_rate_original_nogate"], flush=True) + Atomizer._infer_commit_boundary = classmethod(train_like_boundary) + try: + res["B_patched"] = compare(m, "B patched") + res["C_chat_patched"] = chat_samples(m); res["C_rate_patched"] = doubled_rate(res["C_chat_patched"]) + res["C_chat_patched_nogate"] = chat_samples_nogate(m); res["C_rate_patched_nogate"] = doubled_rate(res["C_chat_patched_nogate"]) + print(json.dumps(res["C_chat_patched"], ensure_ascii=False, indent=1), res["C_rate_patched"], flush=True) + print(json.dumps(res["C_chat_patched_nogate"], ensure_ascii=False, indent=1), res["C_rate_patched_nogate"], flush=True) + finally: + Atomizer._infer_commit_boundary = classmethod(ORIG_INFER) + (OUT / "decode_consistency.json").write_text(json.dumps(res, ensure_ascii=False, indent=1)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/root_cause/gru_baseline.py b/docs/artifacts/root_cause/gru_baseline.py new file mode 100644 index 0000000000000000000000000000000000000000..1b67e1b369751a1d893c489ce238a47681c5fb5b --- /dev/null +++ b/docs/artifacts/root_cause/gru_baseline.py @@ -0,0 +1,96 @@ +"""(1b) Small byte-level GRU baseline on the same data, same val metric as ATOM. +usage: gru_baseline.py NAME --frac F --minutes M [--hidden H] [--extra PATHS...] [--threads T] [--memorize FILE] +Train set = held-out corpus (val window ranges +-4KB removed; strictly harder than ATOM's setting), +optionally a prefix fraction F of it, optionally + extra French text. +Val = ATOM 2048-transition val, context reset at each window start, nats/byte. +""" +import argparse, json, math, sys, time +from pathlib import Path +import torch, torch.nn as nn, torch.nn.functional as F +sys.path.insert(0, str(Path(__file__).resolve().parent)) +from common import PROMPTS, val_windows_bytes +from ngram_baseline import heldout_corpus +OUT = Path(__file__).resolve().parent + + +class GRULM(nn.Module): + def __init__(self, h=512, layers=2, emb=64): + super().__init__() + self.emb = nn.Embedding(256, emb); self.rnn = nn.GRU(emb, h, layers, batch_first=True); self.head = nn.Linear(h, 256) + def forward(self, x, s=None): + y, s = self.rnn(self.emb(x), s); return self.head(y), s + + +@torch.no_grad() +def val_ce(m, wins): + m.eval(); tot = n = 0 + for w in wins: + x = torch.tensor(list(w), dtype=torch.long)[None] + lg, _ = m(x[:, :-1]); tot += F.cross_entropy(lg[0], x[0, 1:], reduction="sum").item(); n += x.shape[1] - 1 + m.train(); return tot / n + + +@torch.no_grad() +def sample(m, prompt, g, T=0.8, k=12, max_len=100, wrap=True): + m.eval(); ctx = (f"Utilisateur: {prompt}\nAssistant: " if wrap else prompt).encode() + lg, s = m(torch.tensor(list(ctx))[None]); out = bytearray(); last = lg[0, -1] + while len(out) < max_len: + v, i = torch.topk(last / T, k); b = int(i[torch.multinomial(v.softmax(-1), 1, generator=g)]) + out.append(b) + if out.endswith(b"\n\n"): break + lg, s = m(torch.tensor([[b]]), s); last = lg[0, -1] + m.train(); return out.decode("utf-8", "replace") + + +def main(): + ap = argparse.ArgumentParser(); ap.add_argument("name"); ap.add_argument("--frac", type=float, default=1.0) + ap.add_argument("--minutes", type=float, default=20); ap.add_argument("--hidden", type=int, default=512) + ap.add_argument("--layers", type=int, default=2); ap.add_argument("--extra", nargs="*", default=[]) + ap.add_argument("--threads", type=int, default=4); ap.add_argument("--memorize", default=None) + ap.add_argument("--seq", type=int, default=128); ap.add_argument("--bs", type=int, default=32) + a = ap.parse_args(); torch.set_num_threads(a.threads); torch.manual_seed(0) + if a.memorize: + data = Path(a.memorize).read_bytes() + else: + data = heldout_corpus(); data = data[: int(len(data) * a.frac)] + for p in a.extra: data += Path(p).read_bytes() + D = torch.tensor(list(data), dtype=torch.long) + wins = val_windows_bytes(); m = GRULM(a.hidden, a.layers) + nparam = sum(p.numel() for p in m.parameters()) + opt = torch.optim.Adam(m.parameters(), lr=2e-3) + t0 = time.time(); step = 0; log = []; seq = min(a.seq, len(D) - 2) + total = a.minutes * 60 + while time.time() - t0 < total: + frac_t = (time.time() - t0) / total + for gp in opt.param_groups: gp["lr"] = 2e-3 * (0.05 + 0.95 * 0.5 * (1 + math.cos(math.pi * frac_t))) + ix = torch.randint(0, len(D) - seq - 1, (a.bs,)) + x = torch.stack([D[i:i + seq + 1] for i in ix]) + lg, _ = m(x[:, :-1]); loss = F.cross_entropy(lg.reshape(-1, 256), x[:, 1:].reshape(-1)) + opt.zero_grad(); loss.backward(); nn.utils.clip_grad_norm_(m.parameters(), 1.0); opt.step(); step += 1 + if step % 200 == 0: + r = {"step": step, "min": round((time.time() - t0) / 60, 2), "train": round(loss.item(), 4), + "bytes_seen": step * a.bs * seq} + if not a.memorize: r["val"] = round(val_ce(m, wins), 4) + log.append(r); print(json.dumps(r), flush=True) + g = torch.Generator().manual_seed(0) + res = {"name": a.name, "params": nparam, "train_bytes": len(data), "frac": a.frac, "extra": a.extra, "steps": step, + "epochs": round(step * a.bs * seq / len(data), 2), "log": log} + if a.memorize: + # teacher-forced CE on the text + greedy regeneration from its first 32 bytes + with torch.no_grad(): + m.eval(); x = D[None]; lg, _ = m(x[:, :-1]); res["tf_ce"] = F.cross_entropy(lg[0], x[0, 1:]).item() + ctx = data[:32]; lg, s = m(torch.tensor(list(ctx))[None]); out = bytearray(ctx); last = lg[0, -1] + while len(out) < len(data): + b = int(last.argmax()); out.append(b); lg, s = m(torch.tensor([[b]]), s); last = lg[0, -1] + same = next((i for i, (u, v) in enumerate(zip(out, data)) if u != v), len(data)) + res["regen_prefix_match_bytes"] = same; res["regen_head"] = bytes(out[:300]).decode("utf-8", "replace") + else: + res["val_ce"] = val_ce(m, wins) + res["samples"] = {p: [sample(m, p, g) for _ in range(3)] for p in PROMPTS} + torch.save(m.state_dict(), OUT / f"gru_{a.name}.pt") + (OUT / f"gru_{a.name}.json").write_text(json.dumps(res, indent=1, ensure_ascii=False)) + print(json.dumps({k: v for k, v in res.items() if k != "log"}, ensure_ascii=False, indent=1)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/root_cause/gru_f10.json b/docs/artifacts/root_cause/gru_f10.json new file mode 100644 index 0000000000000000000000000000000000000000..6ca76da0e0b5f25db28edb464cbb766ae18853ef --- /dev/null +++ b/docs/artifacts/root_cause/gru_f10.json @@ -0,0 +1,92 @@ +{ + "name": "f10", + "params": 2611456, + "train_bytes": 95949, + "frac": 0.1, + "extra": [], + "steps": 1821, + "epochs": 77.74, + "log": [ + { + "step": 200, + "min": 1.4, + "train": 0.204, + "bytes_seen": 819200, + "val": 0.2491 + }, + { + "step": 400, + "min": 2.8, + "train": 0.1321, + "bytes_seen": 1638400, + "val": 0.1539 + }, + { + "step": 600, + "min": 4.76, + "train": 0.1306, + "bytes_seen": 2457600, + "val": 0.1368 + }, + { + "step": 800, + "min": 6.94, + "train": 0.1241, + "bytes_seen": 3276800, + "val": 0.1241 + }, + { + "step": 1000, + "min": 9.45, + "train": 0.1149, + "bytes_seen": 4096000, + "val": 0.119 + }, + { + "step": 1200, + "min": 11.75, + "train": 0.1189, + "bytes_seen": 4915200, + "val": 0.1217 + }, + { + "step": 1400, + "min": 14.0, + "train": 0.1123, + "bytes_seen": 5734400, + "val": 0.1174 + }, + { + "step": 1600, + "min": 16.25, + "train": 0.1123, + "bytes_seen": 6553600, + "val": 0.1195 + }, + { + "step": 1800, + "min": 19.62, + "train": 0.1103, + "bytes_seen": 7372800, + "val": 0.12 + } + ], + "val_ce": 0.11931887827813625, + "samples": { + "Bonjour, comment ça va ?": [ + "Parce que j'ai essayé et ça marche bien.\nUtilisateur: Et toi, qu'en penses-tu ?\nAssistant: Oui, to", + "Parce que j'ai essayé et ça marche bien.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: D'acc", + "Parce que j'ai essayé et ça marche bien.\n\n" + ], + "Qui es-tu ?": [ + "Je m'appelle Atom. J'apprends le français avec toi.\nUtilisateur: Dis-m'en plus.\nAssistant: Avec pla", + "Je m'appelle Atom. J'apprends le français avec toi.\n\n", + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant" + ], + "Il était une fois": [ + "Bonne nuit, dors bien.\nUtilisateur: Tu es d'accord ?\nAssistant: D'accord, je t'écoute.\n\n", + "À demain, prends soin de toi.\nUtilisateur: Tu es d'accord ?\nAssistant: Je suis d'accord avec toi.\n\n", + "Au revoir, à bientôt.\n\n" + ] + } +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/gru_f100.json b/docs/artifacts/root_cause/gru_f100.json new file mode 100644 index 0000000000000000000000000000000000000000..1a695e3730cadd66fb63bd310969fc88ee4bf5d6 --- /dev/null +++ b/docs/artifacts/root_cause/gru_f100.json @@ -0,0 +1,57 @@ +{ + "name": "f100", + "params": 2611456, + "train_bytes": 959493, + "frac": 1.0, + "extra": [], + "steps": 962, + "epochs": 4.11, + "log": [ + { + "step": 200, + "min": 1.1, + "train": 0.2054, + "bytes_seen": 819200, + "val": 0.2032 + }, + { + "step": 400, + "min": 2.19, + "train": 0.1509, + "bytes_seen": 1638400, + "val": 0.1357 + }, + { + "step": 600, + "min": 3.39, + "train": 0.1405, + "bytes_seen": 2457600, + "val": 0.1151 + }, + { + "step": 800, + "min": 12.64, + "train": 0.1231, + "bytes_seen": 3276800, + "val": 0.1081 + } + ], + "val_ce": 0.10233392380177975, + "samples": { + "Bonjour, comment ça va ?": [ + "Un peu fatigué, mais ça va. Et toi ?\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: Je suis d", + "C'est une longue histoire, je te raconterai.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: D'a", + "Parce que j'ai essayé et ça marche bien.\n\n" + ], + "Qui es-tu ?": [ + "Peut-être jeudi, on verra.\n\n", + "Je suis Atom, un petit modèle qui apprend à parler.\nUtilisateur: Dis-m'en plus.\nAssistant: Bonne q", + "Je suis Atom, un petit modèle qui apprend à parler.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssis" + ], + "Il était une fois": [ + "Comme tu veux, on fera autrement.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Bonne question,", + "Super, on fait comme ça.\n\n", + "À demain, prends soin de toi.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Peut-être jeudi, " + ] + } +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/gru_f100_log.txt b/docs/artifacts/root_cause/gru_f100_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec16721713033db282254bfe3d1090334b04531d --- /dev/null +++ b/docs/artifacts/root_cause/gru_f100_log.txt @@ -0,0 +1,31 @@ +{"step": 200, "min": 1.1, "train": 0.2054, "bytes_seen": 819200, "val": 0.2032} +{"step": 400, "min": 2.19, "train": 0.1509, "bytes_seen": 1638400, "val": 0.1357} +{"step": 600, "min": 3.39, "train": 0.1405, "bytes_seen": 2457600, "val": 0.1151} +{"step": 800, "min": 12.64, "train": 0.1231, "bytes_seen": 3276800, "val": 0.1081} +{ + "name": "f100", + "params": 2611456, + "train_bytes": 959493, + "frac": 1.0, + "extra": [], + "steps": 962, + "epochs": 4.11, + "val_ce": 0.10233392380177975, + "samples": { + "Bonjour, comment ça va ?": [ + "Un peu fatigué, mais ça va. Et toi ?\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: Je suis d", + "C'est une longue histoire, je te raconterai.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: D'a", + "Parce que j'ai essayé et ça marche bien.\n\n" + ], + "Qui es-tu ?": [ + "Peut-être jeudi, on verra.\n\n", + "Je suis Atom, un petit modèle qui apprend à parler.\nUtilisateur: Dis-m'en plus.\nAssistant: Bonne q", + "Je suis Atom, un petit modèle qui apprend à parler.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssis" + ], + "Il était une fois": [ + "Comme tu veux, on fera autrement.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Bonne question,", + "Super, on fait comme ça.\n\n", + "À demain, prends soin de toi.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Peut-être jeudi, " + ] + } +} diff --git a/docs/artifacts/root_cause/gru_f10_log.txt b/docs/artifacts/root_cause/gru_f10_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..bb4abe7735602d921a62b3920d728405c962f78d --- /dev/null +++ b/docs/artifacts/root_cause/gru_f10_log.txt @@ -0,0 +1,36 @@ +{"step": 200, "min": 1.4, "train": 0.204, "bytes_seen": 819200, "val": 0.2491} +{"step": 400, "min": 2.8, "train": 0.1321, "bytes_seen": 1638400, "val": 0.1539} +{"step": 600, "min": 4.76, "train": 0.1306, "bytes_seen": 2457600, "val": 0.1368} +{"step": 800, "min": 6.94, "train": 0.1241, "bytes_seen": 3276800, "val": 0.1241} +{"step": 1000, "min": 9.45, "train": 0.1149, "bytes_seen": 4096000, "val": 0.119} +{"step": 1200, "min": 11.75, "train": 0.1189, "bytes_seen": 4915200, "val": 0.1217} +{"step": 1400, "min": 14.0, "train": 0.1123, "bytes_seen": 5734400, "val": 0.1174} +{"step": 1600, "min": 16.25, "train": 0.1123, "bytes_seen": 6553600, "val": 0.1195} +{"step": 1800, "min": 19.62, "train": 0.1103, "bytes_seen": 7372800, "val": 0.12} +{ + "name": "f10", + "params": 2611456, + "train_bytes": 95949, + "frac": 0.1, + "extra": [], + "steps": 1821, + "epochs": 77.74, + "val_ce": 0.11931887827813625, + "samples": { + "Bonjour, comment ça va ?": [ + "Parce que j'ai essayé et ça marche bien.\nUtilisateur: Et toi, qu'en penses-tu ?\nAssistant: Oui, to", + "Parce que j'ai essayé et ça marche bien.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: D'acc", + "Parce que j'ai essayé et ça marche bien.\n\n" + ], + "Qui es-tu ?": [ + "Je m'appelle Atom. J'apprends le français avec toi.\nUtilisateur: Dis-m'en plus.\nAssistant: Avec pla", + "Je m'appelle Atom. J'apprends le français avec toi.\n\n", + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant" + ], + "Il était une fois": [ + "Bonne nuit, dors bien.\nUtilisateur: Tu es d'accord ?\nAssistant: D'accord, je t'écoute.\n\n", + "À demain, prends soin de toi.\nUtilisateur: Tu es d'accord ?\nAssistant: Je suis d'accord avec toi.\n\n", + "Au revoir, à bientôt.\n\n" + ] + } +} diff --git a/docs/artifacts/root_cause/gru_f30.json b/docs/artifacts/root_cause/gru_f30.json new file mode 100644 index 0000000000000000000000000000000000000000..4106e93c66145e3a0d7069d66433bde8c65c7777 --- /dev/null +++ b/docs/artifacts/root_cause/gru_f30.json @@ -0,0 +1,92 @@ +{ + "name": "f30", + "params": 2611456, + "train_bytes": 287847, + "frac": 0.3, + "extra": [], + "steps": 1864, + "epochs": 26.52, + "log": [ + { + "step": 200, + "min": 1.41, + "train": 0.2097, + "bytes_seen": 819200, + "val": 0.2282 + }, + { + "step": 400, + "min": 2.83, + "train": 0.1507, + "bytes_seen": 1638400, + "val": 0.1387 + }, + { + "step": 600, + "min": 4.71, + "train": 0.1369, + "bytes_seen": 2457600, + "val": 0.1233 + }, + { + "step": 800, + "min": 6.9, + "train": 0.1219, + "bytes_seen": 3276800, + "val": 0.1136 + }, + { + "step": 1000, + "min": 9.04, + "train": 0.1236, + "bytes_seen": 4096000, + "val": 0.1066 + }, + { + "step": 1200, + "min": 11.27, + "train": 0.1182, + "bytes_seen": 4915200, + "val": 0.107 + }, + { + "step": 1400, + "min": 13.55, + "train": 0.1197, + "bytes_seen": 5734400, + "val": 0.1053 + }, + { + "step": 1600, + "min": 15.97, + "train": 0.1123, + "bytes_seen": 6553600, + "val": 0.1038 + }, + { + "step": 1800, + "min": 18.15, + "train": 0.1078, + "bytes_seen": 7372800, + "val": 0.1017 + } + ], + "val_ce": 0.10056361928582191, + "samples": { + "Bonjour, comment ça va ?": [ + "Parce que j'ai essayé et ça marche bien.\nUtilisateur: On en parle demain ?\nAssistant: D'accord, je", + "Parce que j'ai essayé et ça marche bien.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: Oui, ", + "Parce que j'ai essayé et ça marche bien.\n\n" + ], + "Qui es-tu ?": [ + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant", + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant", + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant:" + ], + "Il était une fois": [ + "Comme tu veux, on fera autrement.\n\n", + "Comme tu veux, on fera autrement.\n\n", + "Salut, quoi de neuf ?\nUtilisateur: On en parle ce matin ?\nAssistant: Je suis d'accord avec toi.\nUtil" + ] + } +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/gru_f30_log.txt b/docs/artifacts/root_cause/gru_f30_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..92b2e265ba8c09a1c8a14a99fbe68263ab56a0c0 --- /dev/null +++ b/docs/artifacts/root_cause/gru_f30_log.txt @@ -0,0 +1,36 @@ 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J'apprends le français avec toi.\n\n", + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant" + ], + "Il était une fois": [ + "Bonne nuit, dors bien.\n\n", + "Bonne nuit, dors bien.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Oui, tout à fait.\n\n", + "Bonne nuit, dors bien.\nUtilisateur: Dis-m'en plus.\nAssistant: Avec plaisir, continuons.\n\n" + ] + } +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/gru_small128_log.txt b/docs/artifacts/root_cause/gru_small128_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..418bb3a9700c2a7bf85ca384bd592a1a6a856d2c --- /dev/null +++ b/docs/artifacts/root_cause/gru_small128_log.txt @@ -0,0 +1,128 @@ +{"step": 200, "min": 0.12, "train": 0.7402, "bytes_seen": 819200, "val": 0.8458} +{"step": 400, "min": 0.24, "train": 0.3924, "bytes_seen": 1638400, "val": 0.4149} +{"step": 600, "min": 0.37, "train": 0.2367, "bytes_seen": 2457600, "val": 0.2697} 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J'apprends le français avec toi.\n\n", + "Moi c'est Atom, je réponds du mieux que je peux.\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant" + ], + "Il était une fois": [ + "Bonne nuit, dors bien.\n\n", + "Bonne nuit, dors bien.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Oui, tout à fait.\n\n", + "Bonne nuit, dors bien.\nUtilisateur: Dis-m'en plus.\nAssistant: Avec plaisir, continuons.\n\n" + ] + } +} diff --git a/docs/artifacts/root_cause/gru_x10.json b/docs/artifacts/root_cause/gru_x10.json new file mode 100644 index 0000000000000000000000000000000000000000..2f1ebcd48e5f428159051d4aa40dbd1a90af56e0 --- /dev/null +++ b/docs/artifacts/root_cause/gru_x10.json @@ -0,0 +1,160 @@ +{ + "name": "x10", + "params": 2611456, + "train_bytes": 10427194, + "frac": 1.0, + "extra": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt", + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_dialogue_fr.txt", + "/workspace/repos/toroidal-fractal-intelligence/data/contes_perrault.txt", + "/workspace/repos/toroidal-fractal-intelligence/data/candide_voltaire.txt" + ], + "steps": 3789, + "epochs": 1.49, + "log": [ + { + "step": 200, + "min": 1.11, + "train": 1.8101, + "bytes_seen": 819200, + "val": 1.2251 + }, + { + "step": 400, + "min": 2.19, + "train": 1.2678, + "bytes_seen": 1638400, + "val": 0.8004 + }, + { + "step": 600, + "min": 3.29, + "train": 1.1314, + "bytes_seen": 2457600, + "val": 0.6044 + }, + { + "step": 800, + "min": 4.37, + "train": 1.185, + "bytes_seen": 3276800, + "val": 0.4858 + }, + { + "step": 1000, + "min": 5.42, + "train": 0.9464, + "bytes_seen": 4096000, + "val": 0.3802 + }, + { + "step": 1200, + "min": 6.47, + "train": 1.3162, + "bytes_seen": 4915200, + "val": 0.3353 + }, + { + "step": 1400, + "min": 7.53, + "train": 1.0524, + "bytes_seen": 5734400, + "val": 0.2906 + }, + { + "step": 1600, + "min": 8.58, + "train": 0.9442, + "bytes_seen": 6553600, + "val": 0.2625 + }, + { + "step": 1800, + "min": 9.63, + "train": 0.7658, + "bytes_seen": 7372800, + "val": 0.235 + }, + { + "step": 2000, + "min": 10.67, + "train": 0.9827, + "bytes_seen": 8192000, + "val": 0.2335 + }, + { + "step": 2200, + "min": 11.73, + "train": 0.8988, + "bytes_seen": 9011200, + "val": 0.2189 + }, + { + "step": 2400, + "min": 12.78, + "train": 0.7164, + "bytes_seen": 9830400, + "val": 0.2051 + }, + { + "step": 2600, + "min": 13.82, + "train": 0.97, + "bytes_seen": 10649600, + "val": 0.1932 + }, + { + "step": 2800, + "min": 14.85, + "train": 0.901, + "bytes_seen": 11468800, + "val": 0.1842 + }, + { + "step": 3000, + "min": 15.89, + "train": 0.9371, + "bytes_seen": 12288000, + "val": 0.1765 + }, + { + "step": 3200, + "min": 16.94, + "train": 0.9035, + "bytes_seen": 13107200, + "val": 0.1716 + }, + { + "step": 3400, + "min": 17.99, + "train": 0.6915, + "bytes_seen": 13926400, + "val": 0.1712 + }, + { + "step": 3600, + "min": 19.02, + "train": 0.7535, + "bytes_seen": 14745600, + "val": 0.1698 + } + ], + "val_ce": 0.16901658847928047, + "samples": { + "Bonjour, comment ça va ?": [ + "Bonjour ! Content de te parler.\nUtilisateur: Parlons de l'intelligence artificielle ?\nAssistant: Ave", + "Peut-être mercredi, on ve répond. Et toi ?\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: Ave", + "Halfec, on verra.\n\n" + ], + "Qui es-tu ?": [ + "Je m'appelle ATOM. Je prédis des paquets de concers pour dialoguer.\n\n", + "Je suis une intelligence artificielle légère, entraînée pour le dialogue.\n\n", + "Je suis un assistant conversationnel basé sur un modèle atom-natif toroïdal.\n\n" + ], + "Il était une fois": [ + "Once upon a time, a tiny robot learned to say help week-end to talk about?\n\n", + "Un chat gris regardait la pluie derrière la fenêtre. Soudain, un rayon de soleil perça les nuages", + "Dans le français québécois partage la même base que le français de France, avec un vastage avec" + ] + } +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/gru_x10_log.txt b/docs/artifacts/root_cause/gru_x10_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..30a29240957873e4e71f3b74e84b3c198e83c228 --- /dev/null +++ b/docs/artifacts/root_cause/gru_x10_log.txt @@ -0,0 +1,50 @@ +{"step": 200, "min": 1.11, "train": 1.8101, "bytes_seen": 819200, "val": 1.2251} +{"step": 400, "min": 2.19, "train": 1.2678, "bytes_seen": 1638400, "val": 0.8004} +{"step": 600, "min": 3.29, "train": 1.1314, "bytes_seen": 2457600, "val": 0.6044} +{"step": 800, "min": 4.37, "train": 1.185, "bytes_seen": 3276800, "val": 0.4858} +{"step": 1000, "min": 5.42, "train": 0.9464, "bytes_seen": 4096000, "val": 0.3802} +{"step": 1200, "min": 6.47, "train": 1.3162, "bytes_seen": 4915200, "val": 0.3353} +{"step": 1400, "min": 7.53, "train": 1.0524, "bytes_seen": 5734400, "val": 0.2906} +{"step": 1600, "min": 8.58, "train": 0.9442, "bytes_seen": 6553600, "val": 0.2625} +{"step": 1800, "min": 9.63, "train": 0.7658, "bytes_seen": 7372800, "val": 0.235} +{"step": 2000, "min": 10.67, "train": 0.9827, "bytes_seen": 8192000, "val": 0.2335} +{"step": 2200, "min": 11.73, "train": 0.8988, "bytes_seen": 9011200, "val": 0.2189} +{"step": 2400, "min": 12.78, "train": 0.7164, "bytes_seen": 9830400, "val": 0.2051} +{"step": 2600, "min": 13.82, "train": 0.97, "bytes_seen": 10649600, "val": 0.1932} +{"step": 2800, "min": 14.85, "train": 0.901, "bytes_seen": 11468800, "val": 0.1842} +{"step": 3000, "min": 15.89, "train": 0.9371, "bytes_seen": 12288000, "val": 0.1765} +{"step": 3200, "min": 16.94, "train": 0.9035, "bytes_seen": 13107200, "val": 0.1716} +{"step": 3400, "min": 17.99, "train": 0.6915, "bytes_seen": 13926400, "val": 0.1712} +{"step": 3600, "min": 19.02, "train": 0.7535, "bytes_seen": 14745600, "val": 0.1698} +{ + "name": "x10", + "params": 2611456, + "train_bytes": 10427194, + "frac": 1.0, + "extra": [ + "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt", + "/workspace/repos/toroidal-fractal-intelligence/data/corpus_dialogue_fr.txt", + "/workspace/repos/toroidal-fractal-intelligence/data/contes_perrault.txt", + "/workspace/repos/toroidal-fractal-intelligence/data/candide_voltaire.txt" + ], + "steps": 3789, + "epochs": 1.49, + "val_ce": 0.16901658847928047, + "samples": { + "Bonjour, comment ça va ?": [ + "Bonjour ! Content de te parler.\nUtilisateur: Parlons de l'intelligence artificielle ?\nAssistant: Ave", + "Peut-être mercredi, on ve répond. Et toi ?\nUtilisateur: Qu'est-ce que tu proposes ?\nAssistant: Ave", + "Halfec, on verra.\n\n" + ], + "Qui es-tu ?": [ + "Je m'appelle ATOM. Je prédis des paquets de concers pour dialoguer.\n\n", + "Je suis une intelligence artificielle légère, entraînée pour le dialogue.\n\n", + "Je suis un assistant conversationnel basé sur un modèle atom-natif toroïdal.\n\n" + ], + "Il était une fois": [ + "Once upon a time, a tiny robot learned to say help week-end to talk about?\n\n", + "Un chat gris regardait la pluie derrière la fenêtre. Soudain, un rayon de soleil perça les nuages", + "Dans le français québécois partage la même base que le français de France, avec un vastage avec" + ] + } +} diff --git a/docs/artifacts/root_cause/judge.py b/docs/artifacts/root_cause/judge.py new file mode 100644 index 0000000000000000000000000000000000000000..b68be96f6700505ff913af5ce18fda4ddb638b4f --- /dev/null +++ b/docs/artifacts/root_cause/judge.py @@ -0,0 +1,77 @@ +"""Free-run quality: score generated replies with an external judge (GRU f100, val CE 0.10 on this corpus) +and with ATOM itself (self-NLL along its own generation vs teacher-forced CE on corpus text). +Also prompt-dependence: fraction of seeds whose reply is identical for all 3 prompts.""" +import json, sys +from pathlib import Path +import torch, torch.nn.functional as F +sys.path.insert(0, str(Path(__file__).resolve().parent)) +from common import CKPT, PROMPTS, load_model +from gru_baseline import GRULM +from src.io.atomizer import Atomizer +from src.speech_lock import format_dialogue_prompt +OUT = Path(__file__).resolve().parent +torch.set_num_threads(2) + + +@torch.no_grad() +def gru_nll(m, prompt, reply): + ctx = f"Utilisateur: {prompt}\nAssistant: ".encode(); r = reply.encode() + if not r: return None + x = torch.tensor(list(ctx + r))[None]; lg, _ = m(x[:, :-1]) + lp = F.cross_entropy(lg[0], x[0, 1:], reduction="none")[len(ctx) - 1:] + return float(lp.mean()) + + +@torch.no_grad() +def atom_nll(m, prompt, reply, train_labels): + orig = Atomizer._infer_commit_boundary + if train_labels: + Atomizer._infer_commit_boundary = classmethod(lambda cls, p: "newline" if p[-1] in (10, 13) else "max_span") + try: + m.eval(); m.reset_state(reset_atomizer=True) + pp = m.atomizer.encode(format_dialogue_prompt(prompt), reset=True) + for q in pp[:-1]: m.forward_packet(q) + cur = pp[-1]; tot = 0.0; r = reply.encode() + for b in r: + tot += -float(torch.log_softmax(m.forward_packet(cur)["surface"]["byte_logits"][0], -1)[b]) + cur = m.atomizer.packet_from_payload(bytes([b])) + finally: + Atomizer._infer_commit_boundary = orig + return tot / max(len(r), 1) + + +def mean(xs): + xs = [x for x in xs if x is not None]; return sum(xs) / len(xs) if xs else None + + +def main(): + judge = GRULM(512, 2); judge.load_state_dict(torch.load(OUT / "gru_f100.pt")); judge.eval() + atom = load_model(CKPT) + dec = json.loads((OUT / "decode_consistency.json").read_text()) + ng = json.loads((OUT / "ngram_results.json").read_text()) + sets = { + "corpus_gold_replies": {p: [g] for p, g in [("Bonjour, comment ça va ?", "Ça va très bien, et toi ?\n"), ("Qui es-tu ?", "Je suis Atom, un petit modèle qui apprend à parler.\n"), ("Il était une fois", "Il était une fois un petit robot qui apprenait des mots.\n")]}, + "atom_original_decode": dec["C_chat_original_nogate"], + "atom_label_fixed_decode": dec["C_chat_patched_nogate"], + "gru_f100": json.loads((OUT / "gru_f100.json").read_text())["samples"], + "gru_small128": json.loads((OUT / "gru_small128.json").read_text())["samples"], + } + for row in ng["rows"]: + if "samples" in row: sets[f"ngram{row['n']}_heldout"] = row["samples"] + res = {} + for name, s in sets.items(): + # score first reply line only (up to first newline) — what a chat shows + first = {p: [v.split("\n")[0] + ("\n" if "\n" in v else "") for v in vs] for p, vs in s.items()} + r = {"judge_gru_nll": mean([gru_nll(judge, p, v) for p, vs in first.items() for v in vs])} + if name.startswith("atom") or name == "corpus_gold_replies": + r["atom_self_nll_train_labels"] = mean([atom_nll(atom, p, v, True) for p, vs in first.items() for v in vs]) + r["atom_self_nll_orig_labels"] = mean([atom_nll(atom, p, v, False) for p, vs in first.items() for v in vs]) + vals = list(s.values()) + if len(vals[0]) > 1: + r["frac_seeds_identical_across_3_prompts"] = sum(len({vals[k][i] for k in range(3)}) == 1 for i in range(len(vals[0]))) / len(vals[0]) + res[name] = r; print(name, r, flush=True) + (OUT / "judge_results.json").write_text(json.dumps(res, indent=1)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/root_cause/judge_results.json b/docs/artifacts/root_cause/judge_results.json new file mode 100644 index 0000000000000000000000000000000000000000..6355cece4f526a036d4bcd1ace8ab46ab087ee07 --- /dev/null +++ b/docs/artifacts/root_cause/judge_results.json @@ -0,0 +1,39 @@ +{ + "corpus_gold_replies": { + "judge_gru_nll": 0.05752703050772349, + "atom_self_nll_train_labels": 2.2904358320259446, + "atom_self_nll_orig_labels": 4.14515528732538 + }, + "atom_original_decode": { + "judge_gru_nll": 9.69338309764862, + "atom_self_nll_train_labels": 5.244485109352648, + "atom_self_nll_orig_labels": 0.048725131792543376, + "frac_seeds_identical_across_3_prompts": 0.375 + }, + "atom_label_fixed_decode": { + "judge_gru_nll": 1.3670567249258359, + "atom_self_nll_train_labels": 0.3063984259736722, + "atom_self_nll_orig_labels": 2.628873559593511, + "frac_seeds_identical_across_3_prompts": 0.375 + }, + "gru_f100": { + "judge_gru_nll": 0.08015306790669759, + "frac_seeds_identical_across_3_prompts": 0.0 + }, + "gru_small128": { + "judge_gru_nll": 0.4099816145996253, + "frac_seeds_identical_across_3_prompts": 0.0 + }, + "ngram3_heldout": { + "judge_gru_nll": 3.257985273996989, + "frac_seeds_identical_across_3_prompts": 0.0 + }, + "ngram5_heldout": { + "judge_gru_nll": 1.1176993946234386, + "frac_seeds_identical_across_3_prompts": 0.0 + }, + "ngram8_heldout": { + "judge_gru_nll": 0.5152568452888064, + "frac_seeds_identical_across_3_prompts": 0.0 + } +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/memorize_2k.txt b/docs/artifacts/root_cause/memorize_2k.txt new file mode 100644 index 0000000000000000000000000000000000000000..66befc6299796f251706d2184a452f3baf659697 --- /dev/null +++ b/docs/artifacts/root_cause/memorize_2k.txt @@ -0,0 +1,64 @@ +Utilisateur: Tu me comprends ? +Assistant: Je crois que oui, explique encore un peu. +Utilisateur: Et toi, qu'en penses-tu ? +Assistant: Oui, tout à fait. + +Utilisateur: Qui es-tu ? +Assistant: Moi c'est Atom, je réponds du mieux que je peux. +Utilisateur: Dis-m'en plus. +Assistant: D'accord, je t'écoute. + +Utilisateur: C'est bon ce plat ? +Assistant: Je sais faire une tarte, c'est ma spécialité. + +Utilisateur: Bonne idée +Assistant: Très bien, allons-y. + +Utilisateur: Est-ce que tu aimes marcher ? +Assistant: Pas trop, je préfère lire. Et toi ? + +Utilisateur: Raconte-moi une histoire. +Assistant: Il était une fois un petit robot qui apprenait des mots. +Utilisateur: Tu es d'accord ? +Assistant: Je suis d'accord avec toi. +Utilisateur: Dis-m'en plus. +Assistant: Avec plaisir, continuons. + +Utilisateur: Tu comprends ? +Assistant: Oui, je comprends bien. + +Utilisateur: Tu habites où ? +Assistant: J'habite à Strasbourg. Et toi ? +Utilisateur: Tu es d'accord ? +Assistant: Bonne question, je vais réfléchir. + +Utilisateur: C'est bon ce plat ? +Assistant: Pas trop, mais j'apprends chaque jour. +Utilisateur: Et toi, qu'en penses-tu ? +Assistant: Je suis d'accord avec toi. +Utilisateur: Qu'est-ce que tu proposes ? +Assistant: Oui, tout à fait. + +Utilisateur: Bonne nuit +Assistant: Bonne nuit, dors bien. +Utilisateur: Tu veux qu'on recommence ? +Assistant: Je suis d'accord avec toi. +Utilisateur: Et toi, qu'en penses-tu ? +Assistant: Je suis d'accord avec toi. + +Utilisateur: Tu lis quoi en ce moment ? +Assistant: J'aime les chansons douces hier. + +Utilisateur: Où habites-tu ? +Assistant: Je vis près de Nice. + +Utilisateur: Tu veux manger quoi hier ? +Assistant: Je propose un sandwich, ça te va ? +Utilisateur: On en parle jeudi ? +Assistant: Bonne question, je vais réfléchir. + +Utilisateur: Comment tu t'appelles ? +Assistant: Moi c'est Atom, je réponds du mieux que je peux. +Utilisateur: Et toi, qu'en penses-tu ? +Assistant: Oui, tout à fait. + diff --git a/docs/artifacts/root_cause/ngram_baseline.py b/docs/artifacts/root_cause/ngram_baseline.py new file mode 100644 index 0000000000000000000000000000000000000000..45d1d7ef3eaf10a990493209beeb74f539323e02 --- /dev/null +++ b/docs/artifacts/root_cause/ngram_baseline.py @@ -0,0 +1,92 @@ +"""(1a) Byte n-gram with interpolated Witten-Bell backoff, n=1..8. +Val = the exact ATOM 2048-transition val (4x512, context reset at each window start). +Two training sets: 'full' (whole corpus, same as ATOM which saw val ~4.5x) and +'heldout' (corpus with every occurrence-range of the 4 val windows cut out, +-4KB). +Also samples the 3 chat prompts (dialogue wrap, T=0.8, top-k 12, <=100 bytes, stop at \n\n). +""" +import json, math, random, sys, time +from collections import defaultdict +from pathlib import Path +sys.path.insert(0, str(Path(__file__).resolve().parent)) +from common import OFFSETS, PROMPTS, ROOT, N, val_windows_bytes + +OUT = Path(__file__).resolve().parent + + +def heldout_corpus(): + parts = [] + for f in ("data/corpus_fr_medium.txt", "data/corpus_fr_medium_s21.txt"): + raw = (ROOT / f).read_bytes() + cuts = sorted((o - 4096, o + 4 * N + 4096) for p, o in OFFSETS if p == f) + pos = 0 + for a, b in cuts: + parts.append(raw[pos:max(a, pos)]); pos = b + parts.append(raw[pos:]) + return b"".join(parts) + + +class WB: + def __init__(self, data: bytes, n: int): + self.n = n + self.c = [defaultdict(lambda: defaultdict(int)) for _ in range(n)] + for i in range(len(data)): + for k in range(n): + if i - k < 0: break + self.c[k][data[i - k:i]][data[i]] += 1 + self.tot = [{h: sum(d.values()) for h, d in ck.items()} for ck in self.c] + + def dist(self, hist: bytes): + p = [1.0 / 256] * 256 + for k in range(self.n): + if k > len(hist): break + h = hist[len(hist) - k:] if k else b"" + d = self.c[k].get(h) + if not d: break + t = self.tot[k][h]; u = len(d) + lam = t / (t + u) + q = [(1 - lam) * x for x in p] + for b, cnt in d.items(): + q[b] += lam * cnt / t + p = q + return p + + def ce(self, windows): + tot, n = 0.0, 0 + for w in windows: + for i in range(len(w) - 1): + p = self.dist(w[max(0, i + 1 - (self.n - 1)): i + 1]) + tot += -math.log(max(p[w[i + 1]], 1e-12)); n += 1 + return tot / n + + def sample(self, prompt: str, rng, T=0.8, k=12, max_len=100): + ctx = f"Utilisateur: {prompt}\nAssistant: ".encode() + out = bytearray() + while len(out) < max_len: + p = self.dist((ctx + out)[-(self.n - 1):] if self.n > 1 else b"") + logits = [math.log(max(x, 1e-12)) / T for x in p] + top = sorted(range(256), key=lambda b: -logits[b])[:k] + m = max(logits[b] for b in top) + ws = [math.exp(logits[b] - m) for b in top] + out.append(rng.choices(top, ws)[0]) + if out.endswith(b"\n\n"): break + return out.decode("utf-8", "replace") + + +def main(): + wins = val_windows_bytes() + full = (ROOT / "data/corpus_fr_medium.txt").read_bytes() + (ROOT / "data/corpus_fr_medium_s21.txt").read_bytes() + held = heldout_corpus() + res = {"val": "ATOM 2048-transition val (eval_windows.py), nats/byte", "full_bytes": len(full), "heldout_bytes": len(held), "rows": []} + for name, data in (("full", full), ("heldout", held)): + for n in (1, 2, 3, 4, 5, 6, 8): + t0 = time.time(); m = WB(data, n); ce = m.ce(wins) + row = {"train": name, "n": n, "val_ce": round(ce, 4), "sec": round(time.time() - t0, 1)} + if n in (3, 5, 8) and name == "heldout": + rng = random.Random(0) + row["samples"] = {p: [m.sample(p, rng) for _ in range(3)] for p in PROMPTS} + res["rows"].append(row); print(json.dumps(row, ensure_ascii=False), flush=True) + (OUT / "ngram_results.json").write_text(json.dumps(res, indent=1, ensure_ascii=False)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/root_cause/ngram_log.txt b/docs/artifacts/root_cause/ngram_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b91403b09dcaa703481bfea4391cd17ae683badc --- /dev/null +++ b/docs/artifacts/root_cause/ngram_log.txt @@ -0,0 +1,14 @@ +{"train": "full", "n": 1, "val_ce": 3.2302, "sec": 0.2} +{"train": "full", "n": 2, "val_ce": 1.9496, "sec": 0.3} +{"train": "full", "n": 3, "val_ce": 0.9573, "sec": 0.6} +{"train": "full", "n": 4, "val_ce": 0.4826, "sec": 0.7} +{"train": "full", "n": 5, "val_ce": 0.2922, "sec": 0.9} +{"train": "full", "n": 6, "val_ce": 0.2137, "sec": 1.1} +{"train": "full", "n": 8, "val_ce": 0.1702, "sec": 1.5} +{"train": "heldout", "n": 1, "val_ce": 3.2302, "sec": 0.2} +{"train": "heldout", "n": 2, "val_ce": 1.9503, "sec": 0.3} +{"train": "heldout", "n": 3, "val_ce": 0.9588, "sec": 0.5, "samples": {"Bonjour, comment ça va ?": ["Atoi.\nUtilistantion, teur: Pout-ce tu appre que qu'estant: D'ait à faisateur: Au es deme un robonne", "Pard ?\nAssistant: Pas ?\nAssistant: Ouistantôt\nAssir, mait toi.\n\n", "Je veur: On prend ?\nAssisateur: Je sui, on, je lusestant: On ?\nAssis-tu vecon pensestant plus.\nUtili"], "Qui es-tu ?": ["Distant: Tréflécommen parchir.\n\n", "Questilisateur: D'acord ?\nAssistant toi ?\n\n", "Monne d'accommes-m'es qu'on maist toi.\nUtilisait, ons.\n\n"], "Il était une fois": ["D'accommera.\nUtilistant: Peur: Tu vaisateur: Je tu ples-m'accout-ce teux.\nUtilisateur: Complait.\nAss", "Tu ?\nUtinuoistant: Tu ma ?\nAssis-tu tréchir, je souteur: Commen prec tu ?\nAssir, toi de qu'es ?\nAss", "Où hir.\n\n"]}} +{"train": "heldout", "n": 4, "val_ce": 0.4842, "sec": 0.7} +{"train": "heldout", "n": 5, "val_ce": 0.2934, "sec": 0.9, "samples": {"Bonjour, comment ça va ?": ["Avec plaisir, conte un.\nUtilisateur: Qu'est pas ?\nAssistant: Pas trop, je t'écoute.\n\n", "Avec toi ?\nAssistant: Avec toi, qu'on recomme ça mardi ?\nAssistant: Oui, tout à fait.\n\n", "Il est ma spécial, je t'écoute.\n\n"], "Qui es-tu ?": ["Pas trop, je vais réfléchir.\nUtilisateur: Pourquoi de toi ?\nAssistant: Je suis d'en penses-tu ?\nAs", "Je suis dans quoi ton prends chaud ?\nAssistant: Avec toi, qu'on recomment vas bien.\n\n", "Parle demain\nAssistant: Oui, tout à fait.\n\n"], "Il était une fois": ["Bonne question, je t'écoute.\nUtilisateur: Que dirais-tu ?\nAssistant: De rien, allons-y.\nUtilisateur", "Bonne que j'ai es-tu ?\nAssistant: Bonne que tu proposes ?\nAssistant: Je dois quelle ?\nAssistant: Bon", "Je suis d'accord, je t'écoute.\nUtilisateur: Pourquoi pas ?\nAssistant: D'accord, je vais bien.\n\n"]}} +{"train": "heldout", "n": 6, "val_ce": 0.2149, "sec": 1.1} +{"train": "heldout", "n": 8, "val_ce": 0.1716, "sec": 1.4, "samples": {"Bonjour, comment ça va ?": ["Avec plaisir, continuons.\n\n", "Dehors il fait froid aujourd'hui.\nUtilisateur: Quelle heure est-il ?\nAssistant: Oui, tout à fait.\nU", "Je m'appelle Nina. Et toi, qu'en penses-tu ?\nAssistant: Oui, tout à fait.\n\n"], "Qui es-tu ?": ["Peut-être ce matin ?\nAssistant: Oui, j'aime beaucoup\nAssistant: Oui, tout à fait.\n\n", "Oui, avec plaisir, continuons.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Avec plaisir.\nUtil", "Très bien, allons-y.\nUtilisateur: Dis-m'en plus.\nAssistant: Bonne question, je vais réfléchir.\n\n"], "Il était une fois": ["Je suis content.\n\n", "Je suis d'accord avec toi.\n\n", "Je m'appelle Atom. J'apprends ?\nAssistant: Parce que tu proposes ?\nAssistant: Mon village est petit,"]}} diff --git a/docs/artifacts/root_cause/ngram_results.json b/docs/artifacts/root_cause/ngram_results.json new file mode 100644 index 0000000000000000000000000000000000000000..1f85308ba031e44dc70ab1d94523de586237c5b7 --- /dev/null +++ b/docs/artifacts/root_cause/ngram_results.json @@ -0,0 +1,142 @@ +{ + "val": "ATOM 2048-transition val (eval_windows.py), nats/byte", + "full_bytes": 1000453, + "heldout_bytes": 959493, + "rows": [ + { + "train": "full", + "n": 1, + "val_ce": 3.2302, + "sec": 0.2 + }, + { + "train": "full", + "n": 2, + "val_ce": 1.9496, + "sec": 0.3 + }, + { + "train": "full", + "n": 3, + "val_ce": 0.9573, + "sec": 0.6 + }, + { + "train": "full", + "n": 4, + "val_ce": 0.4826, + "sec": 0.7 + }, + { + "train": "full", + "n": 5, + "val_ce": 0.2922, + "sec": 0.9 + }, + { + "train": "full", + "n": 6, + "val_ce": 0.2137, + "sec": 1.1 + }, + { + "train": "full", + "n": 8, + "val_ce": 0.1702, + "sec": 1.5 + }, + { + "train": "heldout", + "n": 1, + "val_ce": 3.2302, + "sec": 0.2 + }, + { + "train": "heldout", + "n": 2, + "val_ce": 1.9503, + "sec": 0.3 + }, + { + "train": "heldout", + "n": 3, + "val_ce": 0.9588, + "sec": 0.5, + "samples": { + "Bonjour, comment ça va ?": [ + "Atoi.\nUtilistantion, teur: Pout-ce tu appre que qu'estant: D'ait à faisateur: Au es deme un robonne", + "Pard ?\nAssistant: Pas ?\nAssistant: Ouistantôt\nAssir, mait toi.\n\n", + "Je veur: On prend ?\nAssisateur: Je sui, on, je lusestant: On ?\nAssis-tu vecon pensestant plus.\nUtili" + ], + "Qui es-tu ?": [ + "Distant: Tréflécommen parchir.\n\n", + "Questilisateur: D'acord ?\nAssistant toi ?\n\n", + "Monne d'accommes-m'es qu'on maist toi.\nUtilisait, ons.\n\n" + ], + "Il était une fois": [ + "D'accommera.\nUtilistant: Peur: Tu vaisateur: Je tu ples-m'accout-ce teux.\nUtilisateur: Complait.\nAss", + "Tu ?\nUtinuoistant: Tu ma ?\nAssis-tu tréchir, je souteur: Commen prec tu ?\nAssir, toi de qu'es ?\nAss", + "Où hir.\n\n" + ] + } + }, + { + "train": "heldout", + "n": 4, + "val_ce": 0.4842, + "sec": 0.7 + }, + { + "train": "heldout", + "n": 5, + "val_ce": 0.2934, + "sec": 0.9, + "samples": { + "Bonjour, comment ça va ?": [ + "Avec plaisir, conte un.\nUtilisateur: Qu'est pas ?\nAssistant: Pas trop, je t'écoute.\n\n", + "Avec toi ?\nAssistant: Avec toi, qu'on recomme ça mardi ?\nAssistant: Oui, tout à fait.\n\n", + "Il est ma spécial, je t'écoute.\n\n" + ], + "Qui es-tu ?": [ + "Pas trop, je vais réfléchir.\nUtilisateur: Pourquoi de toi ?\nAssistant: Je suis d'en penses-tu ?\nAs", + "Je suis dans quoi ton prends chaud ?\nAssistant: Avec toi, qu'on recomment vas bien.\n\n", + "Parle demain\nAssistant: Oui, tout à fait.\n\n" + ], + "Il était une fois": [ + "Bonne question, je t'écoute.\nUtilisateur: Que dirais-tu ?\nAssistant: De rien, allons-y.\nUtilisateur", + "Bonne que j'ai es-tu ?\nAssistant: Bonne que tu proposes ?\nAssistant: Je dois quelle ?\nAssistant: Bon", + "Je suis d'accord, je t'écoute.\nUtilisateur: Pourquoi pas ?\nAssistant: D'accord, je vais bien.\n\n" + ] + } + }, + { + "train": "heldout", + "n": 6, + "val_ce": 0.2149, + "sec": 1.1 + }, + { + "train": "heldout", + "n": 8, + "val_ce": 0.1716, + "sec": 1.4, + "samples": { + "Bonjour, comment ça va ?": [ + "Avec plaisir, continuons.\n\n", + "Dehors il fait froid aujourd'hui.\nUtilisateur: Quelle heure est-il ?\nAssistant: Oui, tout à fait.\nU", + "Je m'appelle Nina. Et toi, qu'en penses-tu ?\nAssistant: Oui, tout à fait.\n\n" + ], + "Qui es-tu ?": [ + "Peut-être ce matin ?\nAssistant: Oui, j'aime beaucoup\nAssistant: Oui, tout à fait.\n\n", + "Oui, avec plaisir, continuons.\nUtilisateur: Tu veux qu'on recommence ?\nAssistant: Avec plaisir.\nUtil", + "Très bien, allons-y.\nUtilisateur: Dis-m'en plus.\nAssistant: Bonne question, je vais réfléchir.\n\n" + ], + "Il était une fois": [ + "Je suis content.\n\n", + "Je suis d'accord avec toi.\n\n", + "Je m'appelle Atom. J'apprends ?\nAssistant: Parce que tu proposes ?\nAssistant: Mon village est petit," + ] + } + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/overfit_atom.py b/docs/artifacts/root_cause/overfit_atom.py new file mode 100644 index 0000000000000000000000000000000000000000..932f4d35cb71c9c5f49026ff83930d58b386df46 --- /dev/null +++ b/docs/artifacts/root_cause/overfit_atom.py @@ -0,0 +1,98 @@ +"""(3) Overfit/memorization test: ATOM recipe on a ~2 KB text, repeated passes. +usage: overfit_atom.py NAME {fresh|ckpt} MINUTES [LR] +Mirrors tools/run_atom_native.py per-step logic: AdamW(wd=.01), clip 1.0, stabilize_dynamics, +efference every 10, atom flush every 64, last_atom_dropout .5, field loss .05, reset per pass. +Eval: teacher-forced CE on the text + greedy regeneration from the first 32 bytes +(generation path with train-like commit labels, i.e. the decode bug neutralised, and original).""" +import json, sys, time +from pathlib import Path +import torch, torch.nn.functional as F +sys.path.insert(0, str(Path(__file__).resolve().parent)) +from common import CKPT, ROOT, load_model +from src.atom_native import AtomNativeModel +from src.io.atomizer import Atomizer +OUT = Path(__file__).resolve().parent +TEXT = OUT / "memorize_2k.txt" + + +def make_text(): + raw = (ROOT / "data/corpus_fr_medium.txt").read_bytes()[:2300] + cut = raw[:2048].rfind(b"\n\n") + 2 + TEXT.write_bytes(raw[:cut]) + + +def fresh(): + m = AtomNativeModel(d_model=32, n_modes=32, n_atoms_max=64, max_payload_bytes=1, + atomizer=Atomizer(max_span_bytes=1), field_max_rms=3.0, enable_merge=False, + field_loss_weight=0.05, field_obligatory_hard=True, last_atom_readout=True, field_leak=0.3) + return m + + +def flush(m): # same as trainer --atom-flush-every 64 (AtomSet is unbounded; aggregation is O(n^2)/tick) + m.core.atoms = type(m.core.atoms)(); m.core.energy_history = [] + + +@torch.no_grad() +def tf_ce(m, data): + m.eval(); m.reset_state(reset_atomizer=True); pk = m.atomizer.encode_bytes(data, reset=True) + ls = [] + for i in range(len(pk) - 1): + ls.append(float(m.transition_loss(pk[i], pk[i + 1])[1]["byte_loss"])) + if (i + 1) % 64 == 0: flush(m) + m.train(); return sum(ls) / len(ls) + + +@torch.no_grad() +def regen(m, data, train_labels=True, n=None): + m.eval(); orig = Atomizer._infer_commit_boundary + if train_labels: + Atomizer._infer_commit_boundary = classmethod(lambda cls, p: "newline" if p[-1] in (10, 13) else "max_span") + try: + m.reset_state(reset_atomizer=True); pk = m.atomizer.encode_bytes(data[:32], reset=True) + for q in pk[:-1]: m.forward_packet(q) + cur = pk[-1]; out = bytearray(data[:32]); n = n or len(data) + while len(out) < n: + if len(out) % 64 == 0: flush(m) + b = int(m.forward_packet(cur)["surface"]["byte_logits"][0].argmax()); out.append(b) + cur = m.atomizer.packet_from_payload(bytes([b])) + finally: + Atomizer._infer_commit_boundary = orig + m.train(); same = next((i for i, (u, v) in enumerate(zip(out, data)) if u != v), len(data)) + return same, bytes(out[:260]).decode("utf-8", "replace") + + +def main(): + name, init, minutes = sys.argv[1], sys.argv[2], float(sys.argv[3]) + lr = float(sys.argv[4]) if len(sys.argv) > 4 else 3e-4 + torch.set_num_threads(1); torch.manual_seed(20260913) + if not TEXT.exists(): make_text() + data = TEXT.read_bytes() + m = fresh() if init == "fresh" else load_model(CKPT) + m.surface.payload_enabled = False; m.surface.last_atom_dropout = 0.5; m.field_loss_weight = 0.05; m._efference_every = 10 + m.train() + opt = torch.optim.AdamW([p for p in m.parameters() if p.requires_grad], lr=lr, weight_decay=0.01) + log = []; t0 = time.time(); step = 0; ep = 0 + r0 = {"pass": 0, "tf_ce": tf_ce(m, data)}; log.append(r0); print(json.dumps(r0), flush=True) + while time.time() - t0 < minutes * 60: + m.reset_state(reset_atomizer=True); pk = m.atomizer.encode_bytes(data, reset=True); ep += 1 + for i in range(len(pk) - 1): + step += 1; opt.zero_grad(set_to_none=True) + if step % 10 == 0: loss, info = m.efference_loss(pk[i], pk[i + 1]) + else: loss, info = m.transition_loss(pk[i], pk[i + 1]) + loss.backward(); torch.nn.utils.clip_grad_norm_([p for p in m.parameters() if p.requires_grad], 1.0); opt.step() + if step % 64 == 0: + m.core.atoms = type(m.core.atoms)(); m.core.energy_history = [] + m.stabilize_dynamics_parameters() + if ep % 5 == 0: + r = {"pass": ep, "step": step, "min": round((time.time() - t0) / 60, 1), "tf_ce": tf_ce(m, data)} + log.append(r); print(json.dumps(r), flush=True) + s1, h1 = regen(m, data, True); s2, h2 = regen(m, data, False) + res = {"name": name, "init": init, "lr": lr, "text_bytes": len(data), "passes": ep, "steps": step, + "final_tf_ce": tf_ce(m, data), "regen_prefix_match_train_labels": s1, "regen_head_train_labels": h1, + "regen_prefix_match_orig_labels": s2, "regen_head_orig_labels": h2, "log": log} + (OUT / f"overfit_atom_{name}.json").write_text(json.dumps(res, indent=1, ensure_ascii=False)) + print(json.dumps({k: v for k, v in res.items() if k != "log"}, ensure_ascii=False, indent=1)) + + +if __name__ == "__main__": + main() diff --git a/docs/artifacts/root_cause/overfit_atom_ckpt.json b/docs/artifacts/root_cause/overfit_atom_ckpt.json new file mode 100644 index 0000000000000000000000000000000000000000..ad5bdea501cd8536f9fd13d57a5c8db0a28c757d --- /dev/null +++ b/docs/artifacts/root_cause/overfit_atom_ckpt.json @@ -0,0 +1,145 @@ +{ + "name": "ckpt", + "init": "ckpt", + "lr": 0.0003, + "text_bytes": 1940, + "passes": 106, + "steps": 205534, + "final_tf_ce": 0.25500894160180776, + "regen_prefix_match_train_labels": 42, + "regen_head_train_labels": "Utilisateur: Tu me comprends ?\nAssistant: Oui, je vais réfléchir.\n\nUtilisateur: Tu veux ques haque jour.\nUtilisateur: Et toi, qu'en penses-tu ?\nAssistant: Oui, tout à fait.\n\nUtilisateur: Qui es réfléchir.\n\nUtilisateur: Bonne nuit\nAssistant: Bonne quessist", + "regen_prefix_match_orig_labels": 41, + "regen_head_orig_labels": "Utilisateur: Tu me comprends ?\nAssistant::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::", + "log": [ + { + "pass": 0, + "tf_ce": 1.058263281848239 + }, + { + "pass": 5, + "step": 9695, + "min": 1.6, + "tf_ce": 0.8599777975839912 + }, + { + "pass": 10, + "step": 19390, + "min": 3.1, + "tf_ce": 0.7673751281043563 + }, + { + "pass": 15, + "step": 29085, + "min": 4.5, + "tf_ce": 0.6973167013096107 + }, + { + "pass": 20, + "step": 38780, + "min": 5.9, + "tf_ce": 0.6518647581371243 + }, + { + "pass": 25, + "step": 48475, + "min": 7.3, + "tf_ce": 0.6285236961862309 + }, + { + "pass": 30, + "step": 58170, + "min": 8.7, + "tf_ce": 0.5641493856632012 + }, + { + "pass": 35, + "step": 67865, + "min": 10.1, + "tf_ce": 0.5826627313418878 + }, + { + "pass": 40, + "step": 77560, + "min": 11.5, + "tf_ce": 0.5133053355802649 + }, + { + "pass": 45, + "step": 87255, + "min": 12.9, + "tf_ce": 0.5106767755585011 + }, + { + "pass": 50, + "step": 96950, + "min": 14.3, + "tf_ce": 0.5416466991726586 + }, + { + "pass": 55, + "step": 106645, + "min": 15.7, + "tf_ce": 0.4432075239171638 + }, + { + "pass": 60, + "step": 116340, + "min": 17.1, + "tf_ce": 0.4421998965066142 + }, + { + "pass": 65, + "step": 126035, + "min": 18.5, + "tf_ce": 0.3968540437800764 + }, + { + "pass": 70, + "step": 135730, + "min": 20.0, + "tf_ce": 0.4121917703983623 + }, + { + "pass": 75, + "step": 145425, + "min": 21.4, + "tf_ce": 0.43351404015877254 + }, + { + "pass": 80, + "step": 155120, + "min": 22.8, + "tf_ce": 0.3986942251480782 + }, + { + "pass": 85, + "step": 164815, + "min": 24.2, + "tf_ce": 0.4170810489016109 + }, + { + "pass": 90, + "step": 174510, + "min": 25.6, + "tf_ce": 0.33114417363172666 + }, + { + "pass": 95, + "step": 184205, + "min": 27.1, + "tf_ce": 0.3925432207298958 + }, + { + "pass": 100, + "step": 193900, + "min": 28.5, + "tf_ce": 0.3364310919269589 + }, + { + "pass": 105, + "step": 203595, + "min": 29.9, + "tf_ce": 0.31477392144405664 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/overfit_atom_ckpt_log.txt b/docs/artifacts/root_cause/overfit_atom_ckpt_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..19cef6789e4f34651119dff7a37733923ef41686 --- /dev/null +++ b/docs/artifacts/root_cause/overfit_atom_ckpt_log.txt @@ -0,0 +1,35 @@ +{"pass": 0, "tf_ce": 1.058263281848239} +{"pass": 5, "step": 9695, "min": 1.6, "tf_ce": 0.8599777975839912} +{"pass": 10, "step": 19390, "min": 3.1, "tf_ce": 0.7673751281043563} +{"pass": 15, "step": 29085, "min": 4.5, "tf_ce": 0.6973167013096107} +{"pass": 20, "step": 38780, "min": 5.9, "tf_ce": 0.6518647581371243} +{"pass": 25, "step": 48475, "min": 7.3, "tf_ce": 0.6285236961862309} +{"pass": 30, "step": 58170, "min": 8.7, "tf_ce": 0.5641493856632012} +{"pass": 35, "step": 67865, "min": 10.1, "tf_ce": 0.5826627313418878} +{"pass": 40, "step": 77560, "min": 11.5, "tf_ce": 0.5133053355802649} +{"pass": 45, "step": 87255, "min": 12.9, "tf_ce": 0.5106767755585011} +{"pass": 50, "step": 96950, "min": 14.3, "tf_ce": 0.5416466991726586} +{"pass": 55, "step": 106645, "min": 15.7, "tf_ce": 0.4432075239171638} +{"pass": 60, "step": 116340, "min": 17.1, "tf_ce": 0.4421998965066142} +{"pass": 65, "step": 126035, "min": 18.5, "tf_ce": 0.3968540437800764} +{"pass": 70, "step": 135730, "min": 20.0, "tf_ce": 0.4121917703983623} +{"pass": 75, "step": 145425, "min": 21.4, "tf_ce": 0.43351404015877254} +{"pass": 80, "step": 155120, "min": 22.8, "tf_ce": 0.3986942251480782} +{"pass": 85, "step": 164815, "min": 24.2, "tf_ce": 0.4170810489016109} +{"pass": 90, "step": 174510, "min": 25.6, "tf_ce": 0.33114417363172666} +{"pass": 95, "step": 184205, "min": 27.1, "tf_ce": 0.3925432207298958} +{"pass": 100, "step": 193900, "min": 28.5, "tf_ce": 0.3364310919269589} +{"pass": 105, "step": 203595, "min": 29.9, "tf_ce": 0.31477392144405664} +{ + "name": "ckpt", + "init": "ckpt", + "lr": 0.0003, + "text_bytes": 1940, + "passes": 106, + "steps": 205534, + "final_tf_ce": 0.25500894160180776, + "regen_prefix_match_train_labels": 42, + "regen_head_train_labels": "Utilisateur: Tu me comprends ?\nAssistant: Oui, je vais réfléchir.\n\nUtilisateur: Tu veux ques haque jour.\nUtilisateur: Et toi, qu'en penses-tu ?\nAssistant: Oui, tout à fait.\n\nUtilisateur: Qui es réfléchir.\n\nUtilisateur: Bonne nuit\nAssistant: Bonne quessist", + "regen_prefix_match_orig_labels": 41, + "regen_head_orig_labels": "Utilisateur: Tu me comprends ?\nAssistant::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::" +} diff --git a/docs/artifacts/root_cause/overfit_atom_fresh.json b/docs/artifacts/root_cause/overfit_atom_fresh.json new file mode 100644 index 0000000000000000000000000000000000000000..4a2192cc57939f1e7f1948170524760fbde66d26 --- /dev/null +++ b/docs/artifacts/root_cause/overfit_atom_fresh.json @@ -0,0 +1,157 @@ +{ + "name": "fresh", + "init": "fresh", + "lr": 0.0003, + "text_bytes": 1940, + "passes": 117, + "steps": 226863, + "final_tf_ce": 0.3097333949878917, + "regen_prefix_match_train_labels": 45, + "regen_head_train_labels": "Utilisateur: Tu me comprends ?\nAssistant: Je vis près de Nice.\n\nUtilisateur: Et toi, qu'en penses-tu ?\nAssistant: Oui, tout à fait.\n\nUtilisateur: Qui es d'acccord avec tou ?\nAssistant: Moi c'est Atom, je réponds du mieux que je ppréfèréffl�échcrr.\n����\n", + "regen_prefix_match_orig_labels": 41, + "regen_head_orig_labels": "Utilisateur: Tu me comprends ?\nAssistant:::Utillisateur:: ", + "log": [ + { + "pass": 0, + "tf_ce": 5.856914837376367 + }, + { + "pass": 5, + "step": 9695, + "min": 1.4, + "tf_ce": 1.5038407779613039 + }, + { + "pass": 10, + "step": 19390, + "min": 2.7, + "tf_ce": 1.2106539868911492 + }, + { + "pass": 15, + "step": 29085, + "min": 4.0, + "tf_ce": 1.1152622555222602 + }, + { + "pass": 20, + "step": 38780, + "min": 5.2, + "tf_ce": 0.880644093738929 + }, + { + "pass": 25, + "step": 48475, + "min": 6.5, + "tf_ce": 0.8433563617267494 + }, + { + "pass": 30, + "step": 58170, + "min": 7.7, + "tf_ce": 0.6955178305419443 + }, + { + "pass": 35, + "step": 67865, + "min": 9.0, + "tf_ce": 0.6784598985173402 + }, + { + "pass": 40, + "step": 77560, + "min": 10.3, + "tf_ce": 0.6057085380236163 + }, + { + "pass": 45, + "step": 87255, + "min": 11.6, + "tf_ce": 0.5024133010021394 + }, + { + "pass": 50, + "step": 96950, + "min": 12.9, + "tf_ce": 0.4202757900722513 + }, + { + "pass": 55, + "step": 106645, + "min": 14.2, + "tf_ce": 0.40452246756150956 + }, + { + "pass": 60, + "step": 116340, + "min": 15.5, + "tf_ce": 0.40139989286472716 + }, + { + "pass": 65, + "step": 126035, + "min": 16.8, + "tf_ce": 0.3610230423968602 + }, + { + "pass": 70, + "step": 135730, + "min": 18.1, + "tf_ce": 0.35558185301414125 + }, + { + "pass": 75, + "step": 145425, + "min": 19.4, + "tf_ce": 0.3880335754344791 + }, + { + "pass": 80, + "step": 155120, + "min": 20.7, + "tf_ce": 0.3189850308917819 + }, + { + "pass": 85, + "step": 164815, + "min": 21.9, + "tf_ce": 0.2659665325475338 + }, + { + "pass": 90, + "step": 174510, + "min": 23.2, + "tf_ce": 0.3091502148483108 + }, + { + "pass": 95, + "step": 184205, + "min": 24.5, + "tf_ce": 0.33210733567790834 + }, + { + "pass": 100, + "step": 193900, + "min": 25.8, + "tf_ce": 0.31093710713820266 + }, + { + "pass": 105, + "step": 203595, + "min": 27.1, + "tf_ce": 0.28547569171223675 + }, + { + "pass": 110, + "step": 213290, + "min": 28.4, + "tf_ce": 0.28425834295412294 + }, + { + "pass": 115, + "step": 222985, + "min": 29.6, + "tf_ce": 0.31657220533744435 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/root_cause/overfit_atom_fresh_log.txt b/docs/artifacts/root_cause/overfit_atom_fresh_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..bea6b51621ed30af217d4b0f3950c78abe35cdb3 --- /dev/null +++ b/docs/artifacts/root_cause/overfit_atom_fresh_log.txt @@ -0,0 +1,37 @@ +{"pass": 0, "tf_ce": 5.856914837376367} +{"pass": 5, "step": 9695, "min": 1.4, "tf_ce": 1.5038407779613039} +{"pass": 10, "step": 19390, "min": 2.7, "tf_ce": 1.2106539868911492} +{"pass": 15, "step": 29085, "min": 4.0, "tf_ce": 1.1152622555222602} +{"pass": 20, "step": 38780, "min": 5.2, "tf_ce": 0.880644093738929} +{"pass": 25, "step": 48475, "min": 6.5, "tf_ce": 0.8433563617267494} +{"pass": 30, "step": 58170, "min": 7.7, "tf_ce": 0.6955178305419443} +{"pass": 35, "step": 67865, "min": 9.0, "tf_ce": 0.6784598985173402} +{"pass": 40, "step": 77560, "min": 10.3, "tf_ce": 0.6057085380236163} +{"pass": 45, "step": 87255, "min": 11.6, "tf_ce": 0.5024133010021394} +{"pass": 50, "step": 96950, "min": 12.9, "tf_ce": 0.4202757900722513} +{"pass": 55, "step": 106645, "min": 14.2, "tf_ce": 0.40452246756150956} +{"pass": 60, "step": 116340, "min": 15.5, "tf_ce": 0.40139989286472716} +{"pass": 65, "step": 126035, "min": 16.8, "tf_ce": 0.3610230423968602} +{"pass": 70, "step": 135730, "min": 18.1, "tf_ce": 0.35558185301414125} +{"pass": 75, "step": 145425, "min": 19.4, "tf_ce": 0.3880335754344791} +{"pass": 80, "step": 155120, "min": 20.7, "tf_ce": 0.3189850308917819} +{"pass": 85, "step": 164815, "min": 21.9, "tf_ce": 0.2659665325475338} +{"pass": 90, "step": 174510, "min": 23.2, "tf_ce": 0.3091502148483108} +{"pass": 95, "step": 184205, "min": 24.5, "tf_ce": 0.33210733567790834} +{"pass": 100, "step": 193900, "min": 25.8, "tf_ce": 0.31093710713820266} +{"pass": 105, "step": 203595, "min": 27.1, "tf_ce": 0.28547569171223675} +{"pass": 110, "step": 213290, "min": 28.4, "tf_ce": 0.28425834295412294} +{"pass": 115, "step": 222985, "min": 29.6, "tf_ce": 0.31657220533744435} +{ + "name": "fresh", + "init": "fresh", + "lr": 0.0003, + "text_bytes": 1940, + "passes": 117, + "steps": 226863, + "final_tf_ce": 0.3097333949878917, + "regen_prefix_match_train_labels": 45, + "regen_head_train_labels": "Utilisateur: Tu me comprends ?\nAssistant: Je vis près de Nice.\n\nUtilisateur: Et toi, qu'en penses-tu ?\nAssistant: Oui, tout à fait.\n\nUtilisateur: Qui es d'acccord avec tou ?\nAssistant: Moi c'est Atom, je réponds du mieux que je ppréfèréffl�échcrr.\n����\n", + "regen_prefix_match_orig_labels": 41, + "regen_head_orig_labels": "Utilisateur: Tu me comprends ?\nAssistant:::Utillisateur:: " +} diff --git a/docs/artifacts/slow_mode_readout/ab_table.md b/docs/artifacts/slow_mode_readout/ab_table.md new file mode 100644 index 0000000000000000000000000000000000000000..d5fbc8d4256a6536687e1738f6c800b2ad7e9cbb --- /dev/null +++ b/docs/artifacts/slow_mode_readout/ab_table.md @@ -0,0 +1,33 @@ +| step | arm | val ring | f-alone ring | val 2048 | f-alone 2048 | a_hat lin | mem slow 16/32/64 | mem z 16/32/64 | mem a_hat 16/32/64 | JS reply0 normal / f-alone | argmax distinct /8 | seeded distinct (first word) uniq/27 | cap | mem loss | steps/s | +|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---| +| 5004k | A | 0.478 | 1.799 | 1.242 | 2.082 | 1.673 | 0.109/0.106/0.103 | — | 0.087/0.116/0.091 | 0.00400 / 0.00580 | 1 | 1.00 (1.00) 2 | 0.000/0.000 | — | 18.6 | +| 5004k | B | 0.474 | 1.959 | 1.270 | 2.266 | 1.689 | 0.938/0.775/0.287 | 0.588/0.344/0.163 | 0.103/0.113/0.100 | 0.01699 / 0.02725 | 2 | 1.78 (1.00) 13 | 0.000/0.000 | 3.1212 | 73.8 | +| 5004k | B0 | 0.401 | 1.687 | 1.233 | 2.107 | 1.688 | 0.938/0.778/0.306 | 0.828/0.503/0.222 | 0.116/0.109/0.087 | 0.03029 / 0.03569 | 2 | 1.56 (1.00) 10 | 0.000/0.000 | — | 78.5 | +| 5012k | A | 0.523 | 1.796 | 1.263 | 2.062 | 1.670 | 0.122/0.125/0.119 | — | 0.087/0.113/0.094 | 0.00458 / 0.00829 | 1 | 1.56 (1.56) 8 | 0.000/0.000 | — | 80.6 | +| 5012k | B | 0.527 | 1.956 | 1.267 | 2.182 | 1.686 | 0.934/0.753/0.312 | 0.684/0.384/0.150 | 0.106/0.097/0.094 | 0.01855 / 0.03177 | 1 | 1.56 (1.00) 9 | 0.000/0.000 | 2.9716 | 77.2 | +| 5012k | B0 | 0.476 | 1.731 | 1.227 | 2.018 | 1.685 | 0.938/0.759/0.303 | 0.847/0.525/0.206 | 0.116/0.103/0.087 | 0.01885 / 0.05105 | 2 | 2.89 (2.22) 18 | 0.000/0.000 | — | 81.2 | +| 5020k | A | 0.517 | 1.725 | 1.278 | 2.056 | 1.680 | 0.106/0.125/0.113 | — | 0.100/0.106/0.091 | 0.00358 / 0.00687 | 1 | 2.00 (1.78) 10 | 0.000/0.000 | — | 78.7 | +| 5020k | B | 0.463 | 1.777 | 1.272 | 2.209 | 1.689 | 0.953/0.775/0.319 | 0.625/0.350/0.153 | 0.106/0.106/0.091 | 0.02319 / 0.04516 | 1 | 2.44 (2.00) 19 | 0.000/0.000 | 2.9586 | 77.6 | +| 5020k | B0 | 0.438 | 1.619 | 1.241 | 2.050 | 1.690 | 0.947/0.775/0.303 | 0.847/0.497/0.169 | 0.106/0.097/0.091 | 0.02857 / 0.05935 | 3 | 2.56 (2.11) 16 | 0.000/0.000 | — | 83.2 | +| 5028k | A | 0.548 | 1.708 | 1.279 | 2.015 | 1.670 | 0.125/0.109/0.122 | — | 0.103/0.113/0.087 | 0.00441 / 0.00516 | 2 | 2.11 (2.11) 6 | 0.000/0.000 | — | 77.8 | +| 5028k | B | 0.527 | 1.770 | 1.331 | 2.150 | 1.674 | 0.953/0.781/0.341 | 0.725/0.422/0.153 | 0.106/0.091/0.097 | 0.05833 / 0.05970 | 2 | 1.78 (1.22) 8 | 0.000/0.000 | 2.8881 | 74.7 | +| 5028k | B0 | 0.519 | 1.732 | 1.288 | 2.093 | 1.680 | 0.956/0.787/0.338 | 0.859/0.522/0.191 | 0.106/0.097/0.100 | 0.04875 / 0.06295 | 3 | 2.56 (2.22) 10 | 0.000/0.000 | — | 81.6 | +| 5036k | A | 0.565 | 1.812 | 1.310 | 2.072 | 1.674 | 0.131/0.097/0.116 | — | 0.109/0.106/0.094 | 0.00401 / 0.00664 | 2 | 2.00 (2.00) 7 | 0.000/0.000 | — | 79.9 | +| 5036k | B0 | 0.566 | 1.702 | 1.350 | 2.121 | 1.678 | 0.950/0.784/0.344 | 0.838/0.512/0.200 | 0.100/0.094/0.100 | 0.03652 / 0.06724 | 3 | 2.89 (2.33) 24 | 0.000/0.000 | — | 81.2 | + +| step | arm | Bonjour, comment ça va ? | Qui es-tu ? | Il était une fois | +|---|---|---|---|---| +| 5004k | A | `Peut--` | `Peut--` | `Peut--` | +| 5004k | B | `Peut--oonne reut--ourreeee` | `Peut--oonne ruurrecomprence` | `Peut--on reut--ourreeeux` | +| 5004k | B0 | `Peut--être aparireee` | `Peut--être ruurra.` | `D'''''''` | +| 5012k | A | `Oui,` | `Oui,` | `Oui,` | +| 5012k | B | `Peut--en` | `Peut--en` | `Peut--en` | +| 5012k | B0 | `Je ruuirra.iisaant:::::::::::::O` | `Oui,, rarirecommence` | `Oui,, rarirecommence` | +| 5020k | A | `Oui,` | `Je` | `Oui,` | +| 5020k | B | `Je end` | `Peut--on ??issoire` | `Bonne ??issoire` | +| 5020k | B0 | `Oui,` | `Bonne` | `D'''''''` | +| 5028k | A | `Peut--` | `D'''''''` | `Peut--` | +| 5028k | B | `Oui,,` | `Oui,,` | `Oui,,` | +| 5028k | B0 | `Peut--` | `Bonne` | `Peut--être` | +| 5036k | A | `Peut--` | `D'''''''` | `D'''''''` | +| 5036k | B0 | `Je` | `Peut--uu'on i?.` | `Je` | diff --git a/docs/artifacts/slow_mode_readout/ab_table.py b/docs/artifacts/slow_mode_readout/ab_table.py new file mode 100644 index 0000000000000000000000000000000000000000..ac6b7d50b90435b96d2acc8e923f24642bfb0353 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/ab_table.py @@ -0,0 +1,28 @@ +"""Markdown A/B table from slowread_progress.tsv (+ the 4996k start row if present).""" +import csv, os, sys +D = os.path.dirname(os.path.abspath(__file__)) +rows = list(csv.DictReader(open(f"{D}/slowread_progress.tsv", encoding="utf-8"), delimiter="\t")) +rows.sort(key=lambda r: (int(r["end_step"]), r["arm"])) +cols = [("step", lambda r: f"{int(r['end_step'])//1000}k"), ("arm", lambda r: r["arm"]), + ("val ring", lambda r: r["val_byte_ce_ring"][:5]), ("f-alone ring", lambda r: r["field_alone_ce_ring"][:5]), + ("val 2048", lambda r: r["val_byte_ce_2048"][:5]), ("f-alone 2048", lambda r: r["field_alone_ce_2048"][:5]), + ("a_hat lin", lambda r: r["a_hat_linear_next_byte_ce"]), + ("mem slow 16/32/64", lambda r: r["mem_acc_slow_16/32/64"]), + ("mem z 16/32/64", lambda r: r["mem_acc_z_16/32/64"] if r["mem_acc_z_16/32/64"] != "//" else "—"), + ("mem a_hat 16/32/64", lambda r: r["mem_acc_ahat_16/32/64"]), + ("JS reply0 normal / f-alone", lambda r: f"{r['out_js_reply0_normal']} / {r['out_js_reply0_field_alone']}"), + ("argmax distinct /8", lambda r: r["out_distinct_argmax_reply0_normal"]), + ("seeded distinct (first word) uniq/27", lambda r: f"{r['seeded_distinct_per_triple']} ({r['seeded_first_word_distinct']}) {r['seeded_unique_of_27']}"), + ("cap", lambda r: f"{r['train_frac_at_cap'] or '—'}/{r['episode_frac_at_cap']}"), + ("mem loss", lambda r: r["slow_memory_loss_last1000"] or "—"), + ("steps/s", lambda r: r["train_steps_per_s"] or "—")] +out = ["| " + " | ".join(c for c, _ in cols) + " |", "|" + "---|" * len(cols)] +for r in rows: + out.append("| " + " | ".join(f(r) for _, f in cols) + " |") +out.append("") +out.append("| step | arm | Bonjour, comment ça va ? | Qui es-tu ? | Il était une fois |") +out.append("|---|---|---|---|---|") +for r in rows: + out.append(f"| {int(r['end_step'])//1000}k | {r['arm']} | `{r['chat_bonjour']}` | `{r['chat_qui']}` | `{r['chat_il_etait']}` |") +open(f"{D}/ab_table.md", "w", encoding="utf-8").write("\n".join(out) + "\n") +print("\n".join(out)) diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5004000.json b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..05a2264622354e99ed6289339e55dc96eb36a639 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5004000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5004000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je i?. rdire " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je i?. rdire " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je i?. rdire " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5004000.txt b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5004000.txt new file mode 100644 index 0000000000000000000000000000000000000000..af40fa447db782ec1857af5835dbddafcd7a11c2 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5004000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=1] 'Il était une fois' -> 'Je ' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=2] 'Il était une fois' -> 'Je ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=3] 'Il était une fois' -> 'Je ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=1] 'Il était une fois' -> 'Je ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=3] 'Il était une fois' -> 'Je ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Je i?. rdire ' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Je i?. rdire ' +[T=1.0 seed=1] 'Il était une fois' -> 'Je i?. rdire ' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=1.0 seed=3] 'Il était une fois' -> 'Je ' diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5012000.json b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5012000.json new file mode 100644 index 0000000000000000000000000000000000000000..f8153b2b4eacf88ca3b8a9ef3cbf1525507fcd53 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5012000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5012000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je , saaisti" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, , saaisti" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je , saaisti" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je i?. saaist saaisti" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, i?. saaist rdirra." + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je i?. saaist saaisti" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je i?ssist " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, i?ssist " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, i?ssist " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5012000.txt b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5012000.txt new file mode 100644 index 0000000000000000000000000000000000000000..a476d00f717d5ae5b26537aa096a94a6be58f848 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5012000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je , saaisti' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Oui, , saaisti' +[T=0.8 seed=1] 'Il était une fois' -> 'Je , saaisti' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=2] 'Il était une fois' -> 'Je ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Oui, ' +[T=0.8 seed=3] 'Il était une fois' -> 'Je ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=1] 'Il était une fois' -> 'Je ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Oui, ' +[T=0.6 seed=3] 'Il était une fois' -> 'Je ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Je i?. saaist saaisti' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Oui, i?. saaist rdirra.' +[T=1.0 seed=1] 'Il était une fois' -> 'Je i?. saaist saaisti' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Je i?ssist ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Oui, i?ssist ' +[T=1.0 seed=3] 'Il était une fois' -> 'Oui, i?ssist ' diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5020000.json b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5020000.json new file mode 100644 index 0000000000000000000000000000000000000000..e8c02805d46ef50a9ec9d686a945da33133f0a19 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5020000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5020000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisattoi,, " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Peut-- " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Peut-- " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisiisateur:::::::::::::::O iilissaant:::::::::::::aisssist" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisiisateur:::::::::::::::O iilissaant:::::::::::::aisssist" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisiisateur:::::::::::::::O iilissaant:::::::::::::aisssist" + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Peut-- " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Peut-- " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisattoi,, \nAsssis" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut--être " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Peux " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Peut--on " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui, " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5020000.txt b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5020000.txt new file mode 100644 index 0000000000000000000000000000000000000000..006a51b875f23132868313a5e8c9684d750cfec8 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5020000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::tiisattoi,, ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist' +[T=0.8 seed=1] 'Il était une fois' -> 'Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Peut-- ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Peut-- ' +[T=0.8 seed=2] 'Il était une fois' -> 'Peut-- ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Peut-- ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=3] 'Il était une fois' -> 'Oui, ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::tiisiisateur:::::::::::::::O iilissaant:::::::::::::aisssist' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Peut--..\nUtilisateur:::::::::::::::tiisiisateur:::::::::::::::O iilissaant:::::::::::::aisssist' +[T=0.6 seed=1] 'Il était une fois' -> 'Peut--..\nUtilisateur:::::::::::::::tiisiisateur:::::::::::::::O iilissaant:::::::::::::aisssist' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Peut-- ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Peut-- ' +[T=0.6 seed=2] 'Il était une fois' -> 'Peut-- ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Peut-- ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=3] 'Il était une fois' -> 'Oui, ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::tiisattoi,, \nAsssis' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist' +[T=1.0 seed=1] 'Il était une fois' -> 'Peut--..\nUtilisateur:::::::::::::::tiisaaiisateur:::::::::::::DUsiilisateur:::::::::::::aisssist' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Peut--être ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Peux ' +[T=1.0 seed=2] 'Il était une fois' -> 'Peut--on ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Oui, ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=1.0 seed=3] 'Il était une fois' -> 'Oui, ' diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5028000.json b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5028000.json new file mode 100644 index 0000000000000000000000000000000000000000..e13a5064ea18d51c311f7698ceec2ec0574bc3db --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5028000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5028000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui,, " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Oui,, " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui,, " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je , i?. " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, , i?. " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Oui, , i?. " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui,, " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Oui,, " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5028000.txt b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5028000.txt new file mode 100644 index 0000000000000000000000000000000000000000..8c15701e316cb40535746fd6b1dad16796df0497 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5028000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Oui, ' +[T=0.8 seed=1] 'Il était une fois' -> 'Oui, ' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Oui,, ' +[T=0.8 seed=2] 'Il était une fois' -> 'Oui,, ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Oui, ' +[T=0.8 seed=3] 'Il était une fois' -> 'Oui, ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Oui, ' +[T=0.6 seed=1] 'Il était une fois' -> 'Oui, ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Oui,, ' +[T=0.6 seed=2] 'Il était une fois' -> 'Oui, ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Oui, ' +[T=0.6 seed=3] 'Il était une fois' -> 'Oui, ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Je , i?. ' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Oui, , i?. ' +[T=1.0 seed=1] 'Il était une fois' -> 'Oui, , i?. ' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Oui,, ' +[T=1.0 seed=2] 'Il était une fois' -> 'Oui,, ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Peut-- ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Oui, ' +[T=1.0 seed=3] 'Il était une fois' -> 'Oui, ' diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5036000.json b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5036000.json new file mode 100644 index 0000000000000000000000000000000000000000..bde43ecfeb2166690f92649c70e7b1d34024fdad --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5036000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5036000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "D'''''''" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je , " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, , " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je , " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui,, " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Peut-- " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "D'''''''" + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "D'''''''" + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5036000.txt b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5036000.txt new file mode 100644 index 0000000000000000000000000000000000000000..c618326033ad9594e68e022d4d748ae6eec1f935 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/chat_seeds_5036000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Oui, ' +[T=0.8 seed=1] 'Il était une fois' -> 'Je ' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Oui, ' +[T=0.8 seed=2] 'Il était une fois' -> 'Je ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=3] 'Qui es-tu ?' -> "D'''''''" +[T=0.8 seed=3] 'Il était une fois' -> 'Je ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Oui, ' +[T=0.6 seed=1] 'Il était une fois' -> 'Je ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Oui, ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Oui, ' +[T=0.6 seed=3] 'Il était une fois' -> 'Je ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Je , ' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Oui, , ' +[T=1.0 seed=1] 'Il était une fois' -> 'Je , ' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Oui,, ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Peut-- ' +[T=1.0 seed=3] 'Qui es-tu ?' -> "D'''''''" +[T=1.0 seed=3] 'Il était une fois' -> "D'''''''" diff --git a/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5004000.json b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..b9844c1b927683d6bc552508bb2e7fa9cfcad119 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5004000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_leakspec_A/atom_native_step_5004000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt": { + "normal_byte_ce": 1.2420088638461735, + "field_alone_byte_ce": 2.0823784984157783, + "per_window": [ + { + "normal": 0.992173207958067, + "field_alone": 1.9969698330211827 + }, + { + "normal": 1.1204012265201013, + "field_alone": 2.019667910186854 + }, + { + "normal": 1.472180179952232, + "field_alone": 2.19853293769296 + }, + { + "normal": 1.383280840954293, + "field_alone": 2.1143433127621165 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5012000.json b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5012000.json new file mode 100644 index 0000000000000000000000000000000000000000..41601c9a365169dc1afff2cfe2389d48bd0712fd --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5012000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_leakspec_A/atom_native_step_5012000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt": { + "normal_byte_ce": 1.263900951520175, + "field_alone_byte_ce": 2.0622865561232544, + "per_window": [ + { + "normal": 1.011504173414445, + "field_alone": 1.9725304927687546 + }, + { + "normal": 1.1594487048070212, + "field_alone": 2.0328677826834394 + }, + { + "normal": 1.4693974768607048, + "field_alone": 2.135452613860167 + }, + { + "normal": 1.4152534509985286, + "field_alone": 2.1082953351806566 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5020000.json b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5020000.json new file mode 100644 index 0000000000000000000000000000000000000000..f2e8fa1558b36ae9e652f849ed002a792b63a087 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5020000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_leakspec_A/atom_native_step_5020000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt": { + "normal_byte_ce": 1.2788865477803593, + "field_alone_byte_ce": 2.056406523151349, + "per_window": [ + { + "normal": 1.0162578787458085, + "field_alone": 1.9394343712770876 + }, + { + "normal": 1.1459145520973493, + "field_alone": 1.9947004941720081 + }, + { + "normal": 1.4673117874673247, + "field_alone": 2.1848717414067096 + }, + { + "normal": 1.486061972810955, + "field_alone": 2.10661948574959 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5028000.json b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5028000.json new file mode 100644 index 0000000000000000000000000000000000000000..fe18da786e3443210cf7efcb245d55a99c0475fc --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5028000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_leakspec_A/atom_native_step_5028000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt": { + "normal_byte_ce": 1.279792502059895, + "field_alone_byte_ce": 2.015174483858848, + "per_window": [ + { + "normal": 1.0067916431000303, + "field_alone": 1.9121048090996027 + }, + { + "normal": 1.1434592144916715, + "field_alone": 1.9424471264676981 + }, + { + "normal": 1.4891802567847194, + "field_alone": 2.146621050632916 + }, + { + "normal": 1.4797388938631593, + "field_alone": 2.0595249492351755 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5036000.json b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5036000.json new file mode 100644 index 0000000000000000000000000000000000000000..401b2e6bace1062b37d8a70dd66f3054cf5ea407 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/eval_windows_5036000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_leakspec_A/atom_native_step_5036000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt": { + "normal_byte_ce": 1.3108035543424434, + "field_alone_byte_ce": 2.072098705201924, + "per_window": [ + { + "normal": 1.0278664589476454, + "field_alone": 1.9590856214473433 + }, + { + "normal": 1.1657948691176927, + "field_alone": 1.9867385006989338 + }, + { + "normal": 1.5116329248169391, + "field_alone": 2.20872859355309 + }, + { + "normal": 1.5379199644874963, + "field_alone": 2.1338421051083287 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5004000.txt b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5004000.txt new file mode 100644 index 0000000000000000000000000000000000000000..360f001b1cfcfa11188602c9a0031e56ebd5573d --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5004000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Peut-- +PROMPT: Qui es-tu ? +RESP: Peut-- +PROMPT: Il était une fois +RESP: Peut-- diff --git a/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5012000.txt b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5012000.txt new file mode 100644 index 0000000000000000000000000000000000000000..42e13a036386045b693b015d06960af03f20f77a --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5012000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Oui, +PROMPT: Qui es-tu ? +RESP: Oui, +PROMPT: Il était une fois +RESP: Oui, diff --git a/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5020000.txt b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5020000.txt new file mode 100644 index 0000000000000000000000000000000000000000..b66b0563f9839faa16afc3bfafeb3927c265da10 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5020000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Oui, +PROMPT: Qui es-tu ? +RESP: Je +PROMPT: Il était une fois +RESP: Oui, diff --git a/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5028000.txt b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5028000.txt new file mode 100644 index 0000000000000000000000000000000000000000..3698e662aff27d16a5eedc4d71aff7643b2b7d4b --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5028000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Peut-- +PROMPT: Qui es-tu ? +RESP: D''''''' +PROMPT: Il était une fois +RESP: Peut-- diff --git a/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5036000.txt b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5036000.txt new file mode 100644 index 0000000000000000000000000000000000000000..aac84f009b6438903e1106d291409221dd1639d2 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/gen_coherent_5036000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Peut-- +PROMPT: Qui es-tu ? +RESP: D''''''' +PROMPT: Il était une fois +RESP: D''''''' diff --git a/docs/artifacts/slow_mode_readout/arm_A/loss_trajectory_5004000.json b/docs/artifacts/slow_mode_readout/arm_A/loss_trajectory_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..78eb985b7cd843af2dc345698acf21905c368f49 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/loss_trajectory_5004000.json @@ -0,0 +1,11879 @@ +[ + { + "step": 4996001, + "run_step": 1, + "episode": 0, + "loss": 0.6317023634910583, + "total_perplexity": 1.8808096772060847, + "byte_loss": 0.6314616799354553, + "byte_perplexity": 1.880357051717503, + "length_loss": 0.0, + "field_norm": 0.04851776361465454, + "field_rms_before": 0.0018162603955715895, + "field_rms_after": 0.0018162603955715895, + "field_scale": 1.0, + "grad_norm": 118.88436126708984, + "n_atoms": 1, + "efference": false, + "free_run_aux": false, + "free_run_horizon": 0, + "merge_count": 0, + "merge_count_total": 0, + "slow_tick": true, + "field_contrast_loss": 0.0, + "field_persist_loss": 0.004813849925994873, 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"shard_index": 1, + "stream_epoch": 4 + } +] \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/measure_5004000.log b/docs/artifacts/slow_mode_readout/arm_A/measure_5004000.log new file mode 100644 index 0000000000000000000000000000000000000000..25c1fded079365508ba4ebc98dded2e0e411fb48 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/measure_5004000.log @@ -0,0 +1,7 @@ +val rings loaded from cache checkpoints/byte_tick_fieldsat/val_ring_4876000.pt +[ring@4876000] checkpoints/byte_tick_leakspec_A/atom_native_step_5004000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt + normal loss=0.4788 byte_ce=0.4781 + la_zero loss=1.8005 byte_ce=1.7998 +checkpoints/byte_tick_leakspec_A/atom_native_step_5004000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt 1.242 2.0824 +{"variant": "ckpt", "frac_at_cap": 0.0, "max_rms": 0.005053431261330843, "slow_share": null, "next_byte_ce": 1.672879934310913, "mem_acc": {"0": 1.0, "16": 0.087, "32": 0.116, "64": 0.091}, "mem_ce": {"0": 0.022, "16": 2.37, "32": 2.402, "64": 2.404}, "mem_acc_by_features": {"slow": {"0": 1.0, "16": 0.109, "32": 0.106, "64": 0.103}}, "slow_next_byte": {"slow": 1.474, "ahat+slow": 1.415, "ahat": 1.673}, "ring_normal": null, "ring_field_alone": null, "out_js": {}, "s": 293.2} +{"variant": "ckpt", "frac_at_cap": null, "max_rms": null, "slow_share": null, "next_byte_ce": null, "mem_acc": {}, "mem_ce": {}, "mem_acc_by_features": {}, "slow_next_byte": {}, "ring_normal": null, "ring_field_alone": null, "out_js": {"normal": {"0": 0.004, "1": 4e-05, "2": 2e-05, "4": 0.00066, "8": 0.00124, "12": 0.00164}, "field_alone": {"0": 0.0058, "1": 0.00702, "2": 0.0046, "4": 0.00113, "8": 0.00016, "12": 4e-05}}, "s": 3.9} diff --git a/docs/artifacts/slow_mode_readout/arm_A/measure_5012000.log b/docs/artifacts/slow_mode_readout/arm_A/measure_5012000.log new file mode 100644 index 0000000000000000000000000000000000000000..66acea73d336d57b02acd172add3704b3885a30a --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/measure_5012000.log @@ -0,0 +1,7 @@ +val rings loaded from cache checkpoints/byte_tick_fieldsat/val_ring_4876000.pt +[ring@4876000] checkpoints/byte_tick_leakspec_A/atom_native_step_5012000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt + normal loss=0.5248 byte_ce=0.5239 + la_zero loss=1.7973 byte_ce=1.7965 +checkpoints/byte_tick_leakspec_A/atom_native_step_5012000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt 1.2639 2.0623 +{"variant": "ckpt", "frac_at_cap": 0.0, "max_rms": 0.005292088724672794, "slow_share": null, "next_byte_ce": 1.6700774431228638, "mem_acc": {"0": 1.0, "16": 0.087, "32": 0.113, "64": 0.094}, "mem_ce": {"0": 0.022, "16": 2.353, "32": 2.389, "64": 2.399}, "mem_acc_by_features": {"slow": {"0": 1.0, "16": 0.122, "32": 0.125, "64": 0.119}}, "slow_next_byte": {"slow": 1.466, "ahat+slow": 1.406, "ahat": 1.67}, "ring_normal": null, "ring_field_alone": null, "out_js": {}, "s": 287.0} +{"variant": "ckpt", "frac_at_cap": null, "max_rms": null, "slow_share": null, "next_byte_ce": null, "mem_acc": {}, "mem_ce": {}, "mem_acc_by_features": {}, "slow_next_byte": {}, "ring_normal": null, "ring_field_alone": null, "out_js": {"normal": {"0": 0.00458, "1": 3e-05, "2": 1e-05, "4": 0.00381, "8": 0.00135, "12": 0.00238}, "field_alone": {"0": 0.00829, "1": 0.00891, "2": 0.00673, "4": 0.00112, "8": 0.00026, "12": 4e-05}}, "s": 3.9} diff --git a/docs/artifacts/slow_mode_readout/arm_A/measure_5020000.log b/docs/artifacts/slow_mode_readout/arm_A/measure_5020000.log new file mode 100644 index 0000000000000000000000000000000000000000..28fa7ab77b7166c4beb8eecdb3fa3f59b22a58b0 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/measure_5020000.log @@ -0,0 +1,7 @@ +val rings loaded from cache checkpoints/byte_tick_fieldsat/val_ring_4876000.pt +[ring@4876000] checkpoints/byte_tick_leakspec_A/atom_native_step_5020000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt + normal loss=0.5187 byte_ce=0.5179 + la_zero loss=1.7259 byte_ce=1.7251 +checkpoints/byte_tick_leakspec_A/atom_native_step_5020000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt 1.2789 2.0564 +{"variant": "ckpt", "frac_at_cap": 0.0, "max_rms": 0.005194914992898703, "slow_share": null, "next_byte_ce": 1.6800278425216675, "mem_acc": {"0": 1.0, "16": 0.1, "32": 0.106, "64": 0.091}, "mem_ce": {"0": 0.021, "16": 2.362, "32": 2.396, "64": 2.393}, "mem_acc_by_features": {"slow": {"0": 1.0, "16": 0.106, "32": 0.125, "64": 0.113}}, "slow_next_byte": {"slow": 1.471, "ahat+slow": 1.411, "ahat": 1.68}, "ring_normal": null, "ring_field_alone": null, "out_js": {}, "s": 287.9} +{"variant": "ckpt", "frac_at_cap": null, "max_rms": null, "slow_share": null, "next_byte_ce": null, "mem_acc": {}, "mem_ce": {}, "mem_acc_by_features": {}, "slow_next_byte": {}, "ring_normal": null, "ring_field_alone": null, "out_js": {"normal": {"0": 0.00358, "1": 3e-05, "2": 1e-05, "4": 0.00588, "8": 0.00111, "12": 0.00164}, "field_alone": {"0": 0.00687, "1": 0.0082, "2": 0.00584, "4": 0.00283, "8": 0.00033, "12": 6e-05}}, "s": 4.0} diff --git a/docs/artifacts/slow_mode_readout/arm_A/measure_5028000.log b/docs/artifacts/slow_mode_readout/arm_A/measure_5028000.log new file mode 100644 index 0000000000000000000000000000000000000000..fa893bcfb1d9cfd5d0e3676c27b8641ee6d8bcb8 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/measure_5028000.log @@ -0,0 +1,7 @@ +val rings loaded from cache checkpoints/byte_tick_fieldsat/val_ring_4876000.pt +[ring@4876000] checkpoints/byte_tick_leakspec_A/atom_native_step_5028000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt + normal loss=0.5494 byte_ce=0.5486 + la_zero loss=1.7091 byte_ce=1.7083 +checkpoints/byte_tick_leakspec_A/atom_native_step_5028000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt 1.2798 2.0152 +{"variant": "ckpt", "frac_at_cap": 0.0, "max_rms": 0.005305062513798475, "slow_share": null, "next_byte_ce": 1.6701579093933105, "mem_acc": {"0": 1.0, "16": 0.103, "32": 0.113, "64": 0.087}, "mem_ce": {"0": 0.022, "16": 2.361, "32": 2.402, "64": 2.395}, "mem_acc_by_features": {"slow": {"0": 1.0, "16": 0.125, "32": 0.109, "64": 0.122}}, "slow_next_byte": {"slow": 1.478, "ahat+slow": 1.417, "ahat": 1.67}, "ring_normal": null, "ring_field_alone": null, "out_js": {}, "s": 289.4} +{"variant": "ckpt", "frac_at_cap": null, "max_rms": null, "slow_share": null, "next_byte_ce": null, "mem_acc": {}, "mem_ce": {}, "mem_acc_by_features": {}, "slow_next_byte": {}, "ring_normal": null, "ring_field_alone": null, "out_js": {"normal": {"0": 0.00441, "1": 2e-05, "2": 1e-05, "4": 0.00305, "8": 0.00059, "12": 0.00227}, "field_alone": {"0": 0.00516, "1": 0.00397, "2": 0.00634, "4": 0.00289, "8": 0.00028, "12": 5e-05}}, "s": 3.9} diff --git a/docs/artifacts/slow_mode_readout/arm_A/measure_5036000.log b/docs/artifacts/slow_mode_readout/arm_A/measure_5036000.log new file mode 100644 index 0000000000000000000000000000000000000000..110a21bef27bfe256f134f7b297d2eefa3cbb4ea --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/measure_5036000.log @@ -0,0 +1,7 @@ +val rings loaded from cache checkpoints/byte_tick_fieldsat/val_ring_4876000.pt +[ring@4876000] checkpoints/byte_tick_leakspec_A/atom_native_step_5036000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt + normal loss=0.5666 byte_ce=0.5659 + la_zero loss=1.8134 byte_ce=1.8127 +checkpoints/byte_tick_leakspec_A/atom_native_step_5036000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt 1.3108 2.0721 +{"variant": "ckpt", "frac_at_cap": 0.0, "max_rms": 0.0051809619180858135, "slow_share": null, "next_byte_ce": 1.674196720123291, "mem_acc": {"0": 1.0, "16": 0.109, "32": 0.106, "64": 0.094}, "mem_ce": {"0": 0.022, "16": 2.358, "32": 2.412, "64": 2.4}, "mem_acc_by_features": {"slow": {"0": 1.0, "16": 0.131, "32": 0.097, "64": 0.116}}, "slow_next_byte": {"slow": 1.49, "ahat+slow": 1.423, "ahat": 1.674}, "ring_normal": null, "ring_field_alone": null, "out_js": {}, "s": 275.0} +{"variant": "ckpt", "frac_at_cap": null, "max_rms": null, "slow_share": null, "next_byte_ce": null, "mem_acc": {}, "mem_ce": {}, "mem_acc_by_features": {}, "slow_next_byte": {}, "ring_normal": null, "ring_field_alone": null, "out_js": {"normal": {"0": 0.00401, "1": 4e-05, "2": 0.0, "4": 0.0014, "8": 0.00065, "12": 0.00164}, "field_alone": {"0": 0.00664, "1": 0.00481, "2": 0.0034, "4": 0.0064, "8": 0.00037, "12": 7e-05}}, "s": 3.9} diff --git a/docs/artifacts/slow_mode_readout/arm_A/outdep_5004000.json b/docs/artifacts/slow_mode_readout/arm_A/outdep_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..975dce78ef66481b6115a22bd02accd47c012f9c --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/outdep_5004000.json @@ -0,0 +1,84 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5004000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.3, + "field_leak_spectrum": null, + "field_leak_spectrum_gain": "none", + "field_leak_spectrum_slow_frac": 1.0, + "lambda_per_mode": null, + "slow_readout": null, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.10282659530639648, + "output_dependence": { + "normal": { + "0": { + "mean_pairwise_js": 0.004, + "distinct_argmax": 1 + }, + "1": { + "mean_pairwise_js": 4e-05, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 2e-05, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00066, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00124, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 0.00164, + "distinct_argmax": 2 + } + }, + "field_alone": { + "0": { + "mean_pairwise_js": 0.0058, + "distinct_argmax": 2 + }, + "1": { + "mean_pairwise_js": 0.00702, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 0.0046, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00113, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00016, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 4e-05, + "distinct_argmax": 1 + } + }, + "reply_prefix": "Je suis un petit" + }, + "elapsed_s": 3.9 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/outdep_5012000.json b/docs/artifacts/slow_mode_readout/arm_A/outdep_5012000.json new file mode 100644 index 0000000000000000000000000000000000000000..19ad10181750f20503421559476af52192b18644 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/outdep_5012000.json @@ -0,0 +1,84 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5012000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.3, + "field_leak_spectrum": null, + "field_leak_spectrum_gain": "none", + "field_leak_spectrum_slow_frac": 1.0, + "lambda_per_mode": null, + "slow_readout": null, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.10091591626405716, + "output_dependence": { + "normal": { + "0": { + "mean_pairwise_js": 0.00458, + "distinct_argmax": 1 + }, + "1": { + "mean_pairwise_js": 3e-05, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 1e-05, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00381, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00135, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 0.00238, + "distinct_argmax": 2 + } + }, + "field_alone": { + "0": { + "mean_pairwise_js": 0.00829, + "distinct_argmax": 3 + }, + "1": { + "mean_pairwise_js": 0.00891, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 0.00673, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00112, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00026, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 4e-05, + "distinct_argmax": 1 + } + }, + "reply_prefix": "Je suis un petit" + }, + "elapsed_s": 3.9 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/outdep_5020000.json b/docs/artifacts/slow_mode_readout/arm_A/outdep_5020000.json new file mode 100644 index 0000000000000000000000000000000000000000..ea6bff547de73310ced00dc3117267ee2af7ba82 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/outdep_5020000.json @@ -0,0 +1,84 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5020000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.3, + "field_leak_spectrum": null, + "field_leak_spectrum_gain": "none", + "field_leak_spectrum_slow_frac": 1.0, + "lambda_per_mode": null, + "slow_readout": null, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.10177058726549149, + "output_dependence": { + "normal": { + "0": { + "mean_pairwise_js": 0.00358, + "distinct_argmax": 1 + }, + "1": { + "mean_pairwise_js": 3e-05, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 1e-05, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00588, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00111, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 0.00164, + "distinct_argmax": 1 + } + }, + "field_alone": { + "0": { + "mean_pairwise_js": 0.00687, + "distinct_argmax": 2 + }, + "1": { + "mean_pairwise_js": 0.0082, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 0.00584, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00283, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00033, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 6e-05, + "distinct_argmax": 1 + } + }, + "reply_prefix": "Je suis un petit" + }, + "elapsed_s": 4.0 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_A/outdep_5028000.json b/docs/artifacts/slow_mode_readout/arm_A/outdep_5028000.json new file mode 100644 index 0000000000000000000000000000000000000000..f7ca5eaff7aba928dcf6a69690d6f23ae123185a --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_A/outdep_5028000.json @@ -0,0 +1,84 @@ +{ + "checkpoint": "checkpoints/byte_tick_leakspec_A/atom_native_step_5028000_d32_ms1M_lrd_b4828_fieldsat_ctlA.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.3, + "field_leak_spectrum": null, + "field_leak_spectrum_gain": "none", + "field_leak_spectrum_slow_frac": 1.0, + "lambda_per_mode": null, + "slow_readout": null, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.10295000672340393, + "output_dependence": { + "normal": { + "0": { + "mean_pairwise_js": 0.00441, + "distinct_argmax": 2 + }, + "1": { + "mean_pairwise_js": 2e-05, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 1e-05, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.00305, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.00059, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 0.00227, + "distinct_argmax": 2 + } + }, + "field_alone": { + "0": { + "mean_pairwise_js": 0.00516, + "distinct_argmax": 1 + }, + "1": { + 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0.5658731343969285, + "n": 256 + }, + "la_zeroed": { + "loss": 1.813417270343507, + "byte_loss": 1.8126799278452665, + "n": 256 + } + } + } + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5004000.json b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..1243ced239f44f718a7f7f3656ac5eae6b66b0aa --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5004000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_sweep/v3_w01_bag_lr1e-3/atom_native_step_5004000_d32_ms1M_lrd_b4828_slowread_v3_w01_bag_lr1e-3.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je nuuittilisateur:::::::::::::toisiilisateur:::::::::::::::" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je nuuittilisateur:::::::::::::D'aiilisateur:::::::::::::::J" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je nuuittilisateur:::::::::::::toisiilisateur:::::::::::::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je rendrecommence " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je rendrecommence " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je rerreerra..\n\n" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je rendrra..\n\n" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je rerrecommence " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je rendrecommence " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je rendrecommence " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je rendrecommence " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je nuuittoi n'onne reuuit." + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je nuuittoi reetu reuuire" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je nuuittoi n'onne reuuit." + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je ne ?quoirecommence " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je un ?quoirecommence " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je ne ?quoirecommence " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je rettoi un " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je n'ooora.nne enne " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je ?irecomence parleence " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5004000.txt b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5004000.txt new file mode 100644 index 0000000000000000000000000000000000000000..e3b337b6ef10d07c84e637f2c20f45edd3a320bc --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5004000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je nuuittilisateur:::::::::::::toisiilisateur:::::::::::::::' +[T=0.8 seed=1] 'Qui es-tu ?' -> "Je nuuittilisateur:::::::::::::D'aiilisateur:::::::::::::::J" +[T=0.8 seed=1] 'Il était une fois' -> 'Je nuuittilisateur:::::::::::::toisiilisateur:::::::::::::::' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je rendrecommence ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Je rendrecommence ' +[T=0.8 seed=2] 'Il était une fois' -> 'Je rendrecommence ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je rendrecommence ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je rendrecommence ' +[T=0.8 seed=3] 'Il était une fois' -> 'Je rendrecommence ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je rerreerra..\n\n' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je rendrra..\n\n' +[T=0.6 seed=1] 'Il était une fois' -> 'Je rerrecommence ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je rendrecommence ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je rendrecommence ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je rendrecommence ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je rendrecommence ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je rendrecommence ' +[T=0.6 seed=3] 'Il était une fois' -> 'Je rendrecommence ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> "Je nuuittoi n'onne reuuit." +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Je nuuittoi reetu reuuire' +[T=1.0 seed=1] 'Il était une fois' -> "Je nuuittoi n'onne reuuit." +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je ne ?quoirecommence ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je un ?quoirecommence ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ne ?quoirecommence ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Je rettoi un ' +[T=1.0 seed=3] 'Qui es-tu ?' -> "Je n'ooora.nne enne " +[T=1.0 seed=3] 'Il était une fois' -> 'Je ?irecomence parleence ' diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5012000.json b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5012000.json new file mode 100644 index 0000000000000000000000000000000000000000..558f963fcf2e182f295c18192fe34ffd321dc80d --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5012000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_B/atom_native_step_5012000_d32_ms1M_lrd_b4828_slowread.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je ??issist " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je un carais " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je un i?. " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je ??isssistant: " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je un ??issistant: ?marirec" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je un ??issistant: ?commara" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je un ??issistant: ?marirec" + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je ??issisistant: " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je ??issisistant: " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je ??issisistant: " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je ?irra.iitee " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je ?irra.iitee " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5012000.txt b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5012000.txt new file mode 100644 index 0000000000000000000000000000000000000000..b1f7a6f619f3f1d1f3e06c6f895ca86ab52939f8 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5012000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je ??issist ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Je un carais ' +[T=0.8 seed=1] 'Il était une fois' -> 'Je un i?. ' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je ??isssistant: ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=2] 'Il était une fois' -> 'Je ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=3] 'Il était une fois' -> 'Je ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=1] 'Il était une fois' -> 'Je ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=3] 'Il était une fois' -> 'Je ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Je un ??issistant: ?marirec' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Je un ??issistant: ?commara' +[T=1.0 seed=1] 'Il était une fois' -> 'Je un ??issistant: ?marirec' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je ??issisistant: ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je ??issisistant: ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je ??issisistant: ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Je ?irra.iitee ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=1.0 seed=3] 'Il était une fois' -> 'Je ?irra.iitee ' diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5020000.json b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5020000.json new file mode 100644 index 0000000000000000000000000000000000000000..e26bf6a09b5e96582023ee51cf29ebb6707f41e1 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5020000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_B/atom_native_step_5020000_d32_ms1M_lrd_b4828_slowread.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, un ??issistant:::::::::" + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issistant: ourrarle ends " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Oui, ??issistant: endrraa" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui, ??issistant::::::::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issistant::::::::::" + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Oui,, ??issistant::::::::::" + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, ??issist " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issistant: " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, ??issist " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, endrraais tu " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui,, ??issistant:::::::::" + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Oui, ??issist " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui, endrraais " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issistant: " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Oui,, ??issistant: " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, endrraais " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issist " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, ??issist " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, un uirra.iisaant: endrraa" + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issistant: ??issist " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Oui, ??issistant: ??issist " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui, ??issist ?liree " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Oui, ??issist ?liree " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Oui,, ??issist ?liree " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, endrra.issisir, aposes " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Oui, ourrenses aposes " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Oui, ourrenses aposes " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5020000.txt b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5020000.txt new file mode 100644 index 0000000000000000000000000000000000000000..d157d4061b4783102058bcac753db5cf02521ed1 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5020000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Oui,, un ??issistant:::::::::' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Oui, ??issistant: ourrarle ends ' +[T=0.8 seed=1] 'Il était une fois' -> 'Oui, ??issistant: endrraa' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Oui, ??issistant::::::::::' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Oui, ??issistant::::::::::' +[T=0.8 seed=2] 'Il était une fois' -> 'Oui,, ??issistant::::::::::' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,, ??issist ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Oui, ??issistant: ' +[T=0.8 seed=3] 'Il était une fois' -> 'Oui, ??issist ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Oui,, endrraais tu ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Oui,, ??issistant:::::::::' +[T=0.6 seed=1] 'Il était une fois' -> 'Oui, ??issist ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Oui, endrraais ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Oui, ??issistant: ' +[T=0.6 seed=2] 'Il était une fois' -> 'Oui,, ??issistant: ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,, endrraais ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Oui, ??issist ' +[T=0.6 seed=3] 'Il était une fois' -> 'Oui, ??issist ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Oui,, un uirra.iisaant: endrraa' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Oui, ??issistant: ??issist ' +[T=1.0 seed=1] 'Il était une fois' -> 'Oui, ??issistant: ??issist ' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Oui, ??issist ?liree ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Oui, ??issist ?liree ' +[T=1.0 seed=2] 'Il était une fois' -> 'Oui,, ??issist ?liree ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,, endrra.issisir, aposes ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Oui, ourrenses aposes ' +[T=1.0 seed=3] 'Il était une fois' -> 'Oui, ourrenses aposes ' diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5028000.json b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5028000.json new file mode 100644 index 0000000000000000000000000000000000000000..13c4d812bff867b099ab50b0cec223c1ddbfc341 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5028000.json @@ -0,0 +1,167 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_B/atom_native_step_5028000_d32_ms1M_lrd_b4828_slowread.pt", + "rows": [ + { + "temp": 0.8, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je un " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je nuurra.illeenne " + }, + { + "temp": 0.8, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je nuurrarle un " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je un " + }, + { + "temp": 0.8, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, un " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.8, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je un " + }, + { + "temp": 0.6, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je " + }, + { + "temp": 0.6, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je " + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je nuurrarle un clait.." + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Qui es-tu ?", + "resp": "Je nuurra.illeenne un clait.." + }, + { + "temp": 1.0, + "seed": 1, + "prompt": "Il était une fois", + "resp": "Je nuurrarle un clait.." + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Bonjour, comment ça va ?", + "resp": "Je un un " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Qui es-tu ?", + "resp": "Je un un " + }, + { + "temp": 1.0, + "seed": 2, + "prompt": "Il était une fois", + "resp": "Je un un " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Bonjour, comment ça va ?", + "resp": "Oui,, un " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Qui es-tu ?", + "resp": "Je un " + }, + { + "temp": 1.0, + "seed": 3, + "prompt": "Il était une fois", + "resp": "Je un " + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5028000.txt b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5028000.txt new file mode 100644 index 0000000000000000000000000000000000000000..12afea1062b35fefb3af4ae8b3fd621fea6fc73e --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/chat_seeds_5028000.txt @@ -0,0 +1,27 @@ +[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je un ' +[T=0.8 seed=1] 'Qui es-tu ?' -> 'Je nuurra.illeenne ' +[T=0.8 seed=1] 'Il était une fois' -> 'Je nuurrarle un ' +[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.8 seed=2] 'Qui es-tu ?' -> 'Je un ' +[T=0.8 seed=2] 'Il était une fois' -> 'Je ' +[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,, un ' +[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.8 seed=3] 'Il était une fois' -> 'Je ' +[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je un ' +[T=0.6 seed=1] 'Il était une fois' -> 'Je ' +[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=2] 'Il était une fois' -> 'Je ' +[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je ' +[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je ' +[T=0.6 seed=3] 'Il était une fois' -> 'Je ' +[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Je nuurrarle un clait..' +[T=1.0 seed=1] 'Qui es-tu ?' -> 'Je nuurra.illeenne un clait..' +[T=1.0 seed=1] 'Il était une fois' -> 'Je nuurrarle un clait..' +[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je un un ' +[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je un un ' +[T=1.0 seed=2] 'Il était une fois' -> 'Je un un ' +[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,, un ' +[T=1.0 seed=3] 'Qui es-tu ?' -> 'Je un ' +[T=1.0 seed=3] 'Il était une fois' -> 'Je un ' diff --git a/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5004000.json b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..e4484a151fb937354c9baf4a327c12250ae5d589 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5004000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_slowread_sweep/v3_w01_bag_lr1e-3/atom_native_step_5004000_d32_ms1M_lrd_b4828_slowread_v3_w01_bag_lr1e-3.pt": { + "normal_byte_ce": 1.2706580961551588, + "field_alone_byte_ce": 2.2668093824519815, + "per_window": [ + { + "normal": 1.0174345581112314, + "field_alone": 2.180367696103758 + }, + { + "normal": 1.1314118328524387, + "field_alone": 2.177849641040666 + }, + { + "normal": 1.505606141797215, + "field_alone": 2.396833997460817 + }, + { + "normal": 1.42817985185975, + "field_alone": 2.3121861952026848 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5012000.json b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5012000.json new file mode 100644 index 0000000000000000000000000000000000000000..9dadf9618ad7ab15a96d36732398277bbf2840d4 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5012000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_slowread_B/atom_native_step_5012000_d32_ms1M_lrd_b4828_slowread.pt": { + "normal_byte_ce": 1.2679279632242806, + "field_alone_byte_ce": 2.1829432289433655, + "per_window": [ + { + "normal": 1.012992598416272, + "field_alone": 2.1152148138282882 + }, + { + "normal": 1.176909778468516, + "field_alone": 2.137168040001029 + }, + { + "normal": 1.503770142776709, + "field_alone": 2.3144359492680167 + }, + { + "normal": 1.378039333235625, + "field_alone": 2.164954112676128 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5020000.json b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5020000.json new file mode 100644 index 0000000000000000000000000000000000000000..4970bc58f7f6c7a1d41694e5494cef000e246498 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5020000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_slowread_B/atom_native_step_5020000_d32_ms1M_lrd_b4828_slowread.pt": { + "normal_byte_ce": 1.2719612491211634, + "field_alone_byte_ce": 2.20952834092763, + "per_window": [ + { + "normal": 1.0207309139597298, + "field_alone": 2.1018628225344855 + }, + { + "normal": 1.1531760225996839, + "field_alone": 2.1079164204731455 + }, + { + "normal": 1.4638118358844174, + "field_alone": 2.3543380599484607 + }, + { + "normal": 1.4501262240408228, + "field_alone": 2.2739960607544276 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5028000.json b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5028000.json new file mode 100644 index 0000000000000000000000000000000000000000..2a1f4ebfed44eba6e70bc94a7d52f4041f30886f --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/eval_windows_5028000.json @@ -0,0 +1,33 @@ +{ + "windows": [ + "data/corpus_fr_medium.txt@50000", + "data/corpus_fr_medium.txt@200000", + "data/corpus_fr_medium.txt@400000", + "data/corpus_fr_medium_s21.txt@250000" + ], + "n_per_window": 512, + "checkpoints": { + "checkpoints/byte_tick_slowread_B/atom_native_step_5028000_d32_ms1M_lrd_b4828_slowread.pt": { + "normal_byte_ce": 1.3310419150168096, + "field_alone_byte_ce": 2.150255344751425, + "per_window": [ + { + "normal": 1.0197897504597455, + "field_alone": 1.98312920074639 + }, + { + "normal": 1.1911240732199055, + "field_alone": 2.049563173013212 + }, + { + "normal": 1.572319213473313, + "field_alone": 2.341260309828712 + }, + { + "normal": 1.5409346229142742, + "field_alone": 2.227068695417387 + } + ] + } + } +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5004000.txt b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5004000.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a8f255249d498229c1ec2ccdbe63fdc33771b97 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5004000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Peut--oonne reut--ourreeee +PROMPT: Qui es-tu ? +RESP: Peut--oonne ruurrecomprence +PROMPT: Il était une fois +RESP: Peut--on reut--ourreeeux diff --git a/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5012000.txt b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5012000.txt new file mode 100644 index 0000000000000000000000000000000000000000..1147a61ef4b331dd5600b0ad0bc8a534de2f6792 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5012000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Peut--en +PROMPT: Qui es-tu ? +RESP: Peut--en +PROMPT: Il était une fois +RESP: Peut--en diff --git a/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5020000.txt b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5020000.txt new file mode 100644 index 0000000000000000000000000000000000000000..9ebc9660e41105196e6d973cf32e062848f9d717 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5020000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Je end +PROMPT: Qui es-tu ? +RESP: Peut--on ??issoire +PROMPT: Il était une fois +RESP: Bonne ??issoire diff --git a/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5028000.txt b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5028000.txt new file mode 100644 index 0000000000000000000000000000000000000000..48326b463bd98ff9bbff0371891816dd3b9b8d4a --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/gen_coherent_5028000.txt @@ -0,0 +1,6 @@ +PROMPT: Bonjour, comment ça va ? +RESP: Oui,, +PROMPT: Qui es-tu ? +RESP: Oui,, +PROMPT: Il était une fois +RESP: Oui,, diff --git a/docs/artifacts/slow_mode_readout/arm_B/loss_trajectory_5004000.json b/docs/artifacts/slow_mode_readout/arm_B/loss_trajectory_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..384fa193a2bfd953d15cb72a7f6b60ade2b1cdf5 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/loss_trajectory_5004000.json @@ -0,0 +1,12519 @@ +[ + { + "step": 4996001, + "run_step": 1, + "episode": 0, + "loss": 0.8631318807601929, + "total_perplexity": 2.3705734330644486, + "byte_loss": 0.8628911375999451, + "byte_perplexity": 2.3700028024150424, + "length_loss": 0.0, + "field_norm": 0.04445300251245499, + "field_rms_before": 0.0017116526141762733, + "field_rms_after": 0.0017116526141762733, + "field_scale": 1.0, + "grad_norm": 127.26895141601562, + "n_atoms": 1, + "efference": false, + "free_run_aux": false, + "free_run_horizon": 0, + "merge_count": 0, + "merge_count_total": 0, + "slow_tick": true, + "field_contrast_loss": 0.0, + 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"printable_mass_mean": NaN, + "field_next_packet_loss": 0.0, + "max_phase_coherence": 0.0, + "n_pairs_above_energy_floor": 0, + "energy_decay": 0.30001306533813477, + "coupling_scale": 1.3082787990570068, + "phase_sync": 0.09460455924272537, + "slow_memory_loss": 2.8663079738616943, + "slow_head_grad_norm": 7.156209945678711, + "bytes_seen": 4567544, + "packets_seen": 4567544, + "shard_index": 1, + "stream_epoch": 4 + } +] \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/measure_5004000.log b/docs/artifacts/slow_mode_readout/arm_B/measure_5004000.log new file mode 100644 index 0000000000000000000000000000000000000000..f408b21bb604540ed606218e099afe5b12bc11a8 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/measure_5004000.log @@ -0,0 +1,7 @@ +val rings loaded from cache checkpoints/byte_tick_fieldsat/val_ring_4876000.pt +[ring@4876000] checkpoints/byte_tick_slowread_sweep/v3_w01_bag_lr1e-3/atom_native_step_5004000_d32_ms1M_lrd_b4828_slowread_v3_w01_bag_lr1e-3.pt + normal loss=0.9794 byte_ce=0.4740 + la_zero loss=2.4651 byte_ce=1.9596 +checkpoints/byte_tick_slowread_sweep/v3_w01_bag_lr1e-3/atom_native_step_5004000_d32_ms1M_lrd_b4828_slowread_v3_w01_bag_lr1e-3.pt 1.2707 2.2668 +{"variant": "ckpt", "frac_at_cap": 0.0, "max_rms": 0.0056006163358688354, "slow_share": 0.6248029470443726, "next_byte_ce": 1.68910551071167, "mem_acc": {"0": 1.0, "16": 0.103, "32": 0.113, "64": 0.1}, "mem_ce": {"0": 0.022, "16": 2.356, "32": 2.386, "64": 2.392}, "mem_acc_by_features": {"slow": {"0": 1.0, "16": 0.938, "32": 0.775, "64": 0.287}, "z": {"0": 1.0, "16": 0.588, "32": 0.344, "64": 0.163}}, "slow_next_byte": {"slow": 1.709, "z": 2.507, "ahat+slow": 1.492, "ahat": 1.689}, "ring_normal": null, "ring_field_alone": null, "out_js": {}, "s": 328.3} +{"variant": "ckpt", "frac_at_cap": null, "max_rms": null, "slow_share": null, "next_byte_ce": null, "mem_acc": {}, "mem_ce": {}, "mem_acc_by_features": {}, "slow_next_byte": {}, "ring_normal": null, "ring_field_alone": null, "out_js": {"normal": {"0": 0.01699, "1": 0.00011, "2": 0.00044, "4": 0.01177, "8": 0.02876, "12": 0.01643}, "field_alone": {"0": 0.02725, "1": 0.04079, "2": 0.04478, "4": 0.04027, "8": 0.03601, "12": 0.01948}}, "s": 4.1} diff --git a/docs/artifacts/slow_mode_readout/arm_B/outdep_5004000.json b/docs/artifacts/slow_mode_readout/arm_B/outdep_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..d396c9f46dbe61d469c455f44ba889870f666e99 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/outdep_5004000.json @@ -0,0 +1,131 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_sweep/v3_w01_bag_lr1e-3/atom_native_step_5004000_d32_ms1M_lrd_b4828_slowread_v3_w01_bag_lr1e-3.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.0, + "field_leak_spectrum": [ + 0.01, + 0.3 + ], + "field_leak_spectrum_gain": "sqrt", + "field_leak_spectrum_slow_frac": 0.25, + "lambda_per_mode": [ + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.11352, + 0.04296, + 0.01626, + 0.01, + 0.02643, + 0.06983, + 0.18455, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3 + ], + "slow_readout": { + "ahat": "exclude", + "slow_idx": [ + 5, + 6, + 7, + 8, + 9, + 10, + 11 + ] + }, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.10132085531949997, + "output_dependence": { + "normal": { + "0": { + "mean_pairwise_js": 0.01699, + "distinct_argmax": 2 + }, + "1": { + "mean_pairwise_js": 0.00011, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 0.00044, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.01177, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.02876, + "distinct_argmax": 2 + }, + "12": { + "mean_pairwise_js": 0.01643, + "distinct_argmax": 2 + } + }, + "field_alone": { + "0": { + "mean_pairwise_js": 0.02725, + "distinct_argmax": 3 + }, + "1": { + "mean_pairwise_js": 0.04079, + "distinct_argmax": 2 + }, + "2": { + "mean_pairwise_js": 0.04478, + "distinct_argmax": 2 + }, + "4": { + "mean_pairwise_js": 0.04027, + "distinct_argmax": 3 + }, + "8": { + "mean_pairwise_js": 0.03601, + "distinct_argmax": 3 + }, + "12": { + "mean_pairwise_js": 0.01948, + "distinct_argmax": 1 + } + }, + "reply_prefix": "Je suis un petit" + }, + "elapsed_s": 4.1 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/outdep_5012000.json b/docs/artifacts/slow_mode_readout/arm_B/outdep_5012000.json new file mode 100644 index 0000000000000000000000000000000000000000..2ab2c973f8f28a38682c5ee048047d2426984dcf --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/outdep_5012000.json @@ -0,0 +1,131 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_B/atom_native_step_5012000_d32_ms1M_lrd_b4828_slowread.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.0, + "field_leak_spectrum": [ + 0.01, + 0.3 + ], + "field_leak_spectrum_gain": "sqrt", + "field_leak_spectrum_slow_frac": 0.25, + "lambda_per_mode": [ + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.11352, + 0.04296, + 0.01626, + 0.01, + 0.02643, + 0.06983, + 0.18455, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 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0.036, + "distinct_argmax": 2 + }, + "12": { + "mean_pairwise_js": 0.02935, + "distinct_argmax": 2 + } + }, + "reply_prefix": "Je suis un petit" + }, + "elapsed_s": 4.3 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/outdep_5020000.json b/docs/artifacts/slow_mode_readout/arm_B/outdep_5020000.json new file mode 100644 index 0000000000000000000000000000000000000000..1cd2e741e8a63cba840f90f83b0be3e6d8b938db --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/outdep_5020000.json @@ -0,0 +1,131 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_B/atom_native_step_5020000_d32_ms1M_lrd_b4828_slowread.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.0, + "field_leak_spectrum": [ + 0.01, + 0.3 + ], + "field_leak_spectrum_gain": "sqrt", + "field_leak_spectrum_slow_frac": 0.25, + "lambda_per_mode": [ + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.11352, + 0.04296, + 0.01626, + 0.01, + 0.02643, + 0.06983, + 0.18455, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3 + ], + "slow_readout": { + "ahat": "exclude", + "slow_idx": [ + 5, + 6, + 7, + 8, + 9, + 10, + 11 + ] + }, + "energy_decay": 0.30000001192092896, + "phase_sync": 0.09598471224308014, + "output_dependence": { + "normal": { + "0": { + "mean_pairwise_js": 0.02319, + "distinct_argmax": 1 + }, + "1": { + "mean_pairwise_js": 6e-05, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 0.00021, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.01309, + "distinct_argmax": 1 + }, + "8": { + "mean_pairwise_js": 0.01211, + "distinct_argmax": 1 + }, + "12": { + "mean_pairwise_js": 0.00603, + "distinct_argmax": 1 + } + }, + "field_alone": { + "0": { + "mean_pairwise_js": 0.04516, + "distinct_argmax": 3 + }, + "1": { + "mean_pairwise_js": 0.02215, + "distinct_argmax": 1 + }, + "2": { + "mean_pairwise_js": 0.03017, + "distinct_argmax": 1 + }, + "4": { + "mean_pairwise_js": 0.03434, + "distinct_argmax": 5 + }, + "8": { + "mean_pairwise_js": 0.03078, + "distinct_argmax": 2 + }, + "12": { + "mean_pairwise_js": 0.0136, + "distinct_argmax": 3 + } + }, + "reply_prefix": "Je suis un petit" + }, + "elapsed_s": 4.3 + } + ] +} \ No newline at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/outdep_5028000.json b/docs/artifacts/slow_mode_readout/arm_B/outdep_5028000.json new file mode 100644 index 0000000000000000000000000000000000000000..dfcfbc347a10f4156975d8781ea26d164463bf0c --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/outdep_5028000.json @@ -0,0 +1,131 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_B/atom_native_step_5028000_d32_ms1M_lrd_b4828_slowread.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.0, + "field_leak_spectrum": [ + 0.01, + 0.3 + ], + "field_leak_spectrum_gain": "sqrt", + "field_leak_spectrum_slow_frac": 0.25, + "lambda_per_mode": [ + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.11352, + 0.04296, + 0.01626, + 0.01, + 0.02643, + 0.06983, + 0.18455, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3, + 0.3 + ], + "slow_readout": { + "ahat": "exclude", + "slow_idx": [ + 5, + 6, + 7, + 8, + 9, + 10, + 11 + ] + }, + "energy_decay": 0.30001306533813477, + 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at end of file diff --git a/docs/artifacts/slow_mode_readout/arm_B/probe_5004000.json b/docs/artifacts/slow_mode_readout/arm_B/probe_5004000.json new file mode 100644 index 0000000000000000000000000000000000000000..652688cf2c24867f06dbad86946ad99b49181531 --- /dev/null +++ b/docs/artifacts/slow_mode_readout/arm_B/probe_5004000.json @@ -0,0 +1,427 @@ +{ + "checkpoint": "checkpoints/byte_tick_slowread_sweep/v3_w01_bag_lr1e-3/atom_native_step_5004000_d32_ms1M_lrd_b4828_slowread_v3_w01_bag_lr1e-3.pt", + "episode_ticks": 8000, + "memory_prompts": [ + "Bonjour, comment \u00e7a va ?", + "Qui es-tu ?", + "Il \u00e9tait une fois", + "Quelle heure est-il ?", + "J'aime beaucoup la musique.", + "Raconte-moi une histoire.", + "O\u00f9 se trouve la gare ?", + "Merci pour ton aide !" + ], + "trials": 320, + "rows": [ + { + "variant": "ckpt", + "field_leak": 0.0, + "field_leak_spectrum": [ + 0.01, + 0.3 + ], + "field_leak_spectrum_gain": "sqrt", + "field_leak_spectrum_slow_frac": 0.25, + 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