| { |
| "experiment_A_grid": { |
| "interface": "cg_sec27_spec.py (same shape as dgg2_sec27_spec.py); runner base: colab_runner_sec27_part0_1_2.py", |
| "generation_readout": "stock_generate_with_readout, readout_source == final_sc_denoising_step; no two-pass readout", |
| "candidate_states_in_order": [ |
| "identity", |
| "reverse_edges", |
| "reverse_order", |
| "delete_selected", |
| "keep_callees", |
| "mark_reachable", |
| "delete_tests", |
| "selected_first", |
| "delete_classes", |
| "keep_callers", |
| "mark_ancestors", |
| "delete_methods", |
| "reverse_edges+reverse_order", |
| "reverse_edges+delete_selected", |
| "reverse_order+keep_callees", |
| "reverse_order+mark_reachable", |
| "reverse_edges+delete_tests", |
| "reverse_order+delete_selected", |
| "reverse_edges+keep_callees", |
| "reverse_edges+mark_reachable", |
| "reverse_order+delete_tests", |
| "delete_tests+mark_reachable" |
| ], |
| "chance_nearest_candidate": 0.045454545454545456, |
| "all_states_test_cache": [ |
| "identity", |
| "reverse_edges", |
| "reverse_order", |
| "delete_selected", |
| "keep_callees", |
| "mark_reachable", |
| "delete_tests", |
| "selected_first", |
| "delete_classes", |
| "keep_callers", |
| "mark_ancestors", |
| "delete_methods", |
| "reverse_edges+reverse_order", |
| "reverse_edges+delete_selected", |
| "reverse_order+keep_callees", |
| "reverse_order+mark_reachable", |
| "reverse_edges+delete_tests", |
| "reverse_order+delete_selected", |
| "reverse_edges+keep_callees", |
| "reverse_edges+mark_reachable", |
| "reverse_order+delete_tests", |
| "delete_tests+mark_reachable", |
| "delete_one_test#0", |
| "delete_one_test#1", |
| "delete_one_test#2", |
| "delete_one_callee#0", |
| "delete_one_callee#1", |
| "delete_one_callee#2", |
| "cut_one_call#0", |
| "cut_one_call#1", |
| "cut_one_call#2", |
| "all#delete_one_callee", |
| "all#cut_one_call" |
| ], |
| "train_states_cache": [ |
| "identity", |
| "reverse_edges", |
| "reverse_order", |
| "delete_selected", |
| "keep_callees", |
| "mark_reachable", |
| "delete_tests", |
| "selected_first", |
| "delete_classes", |
| "reverse_edges+reverse_order", |
| "reverse_edges+delete_selected", |
| "reverse_order+keep_callees", |
| "reverse_order+mark_reachable", |
| "reverse_edges+delete_tests", |
| "delete_one_test#0", |
| "delete_one_test#1", |
| "delete_one_test#2", |
| "delete_one_callee#0", |
| "delete_one_callee#1", |
| "delete_one_callee#2", |
| "cut_one_call#0", |
| "cut_one_call#1", |
| "cut_one_call#2" |
| ], |
| "train_ops": [ |
| "identity", |
| "reverse_edges", |
| "reverse_order", |
| "delete_selected", |
| "keep_callees", |
| "mark_reachable", |
| "delete_tests", |
| "selected_first", |
| "delete_classes", |
| "reverse_edges+reverse_order", |
| "reverse_edges+delete_selected", |
| "reverse_order+keep_callees", |
| "reverse_order+mark_reachable", |
| "reverse_edges+delete_tests", |
| "delete_one_test", |
| "delete_one_callee", |
| "cut_one_call" |
| ], |
| "heldout_ops": [ |
| "keep_callers", |
| "mark_ancestors", |
| "delete_methods", |
| "reverse_order+delete_selected", |
| "reverse_edges+keep_callees", |
| "reverse_edges+mark_reachable", |
| "reverse_order+delete_tests", |
| "delete_tests+mark_reachable" |
| ], |
| "heldout_kinds": { |
| "mirror_of_trained": [ |
| "keep_callers", |
| "mark_ancestors" |
| ], |
| "new_family_member": [ |
| "delete_methods" |
| ] |
| }, |
| "heldout_chains_for_refeed": { |
| "keep_callers": [ |
| "reverse_edges", |
| "keep_callees", |
| "reverse_edges" |
| ], |
| "mark_ancestors": [ |
| "reverse_edges", |
| "mark_reachable", |
| "reverse_edges" |
| ] |
| }, |
| "open_ended_ops": [ |
| "delete_one_test", |
| "delete_one_callee", |
| "cut_one_call" |
| ], |
| "open_valid_answers_per_source": [ |
| 2, |
| 3 |
| ], |
| "op_family": { |
| "identity": "fixed", |
| "reverse_edges": "fixed", |
| "reverse_order": "fixed", |
| "delete_selected": "selected", |
| "keep_callees": "neighbourhood", |
| "mark_reachable": "multi_hop", |
| "delete_tests": "attribute", |
| "selected_first": "selected", |
| "delete_classes": "attribute", |
| "reverse_edges+reverse_order": "comp_fixed_fixed", |
| "reverse_edges+delete_selected": "comp_fixed_content", |
| "reverse_order+keep_callees": "comp_fixed_content", |
| "reverse_order+mark_reachable": "comp_fixed_content", |
| "reverse_edges+delete_tests": "comp_fixed_content", |
| "delete_one_test": "open", |
| "delete_one_callee": "open", |
| "cut_one_call": "open", |
| "keep_callers": "heldout_neighbourhood", |
| "mark_ancestors": "heldout_multi_hop", |
| "delete_methods": "heldout_attribute", |
| "reverse_order+delete_selected": "heldout_comp_fixed_content", |
| "reverse_edges+keep_callees": "heldout_comp_fixed_content", |
| "reverse_edges+mark_reachable": "heldout_comp_fixed_content", |
| "reverse_order+delete_tests": "heldout_comp_fixed_content", |
| "delete_tests+mark_reachable": "heldout_comp_content_content" |
| }, |
| "min_candidate_cell_difference": 2, |
| "instruction_strings": { |
| "total": 182, |
| "sha256_of_all_strings": "631477122daf6335d2a35e5c74a7b114db6be0baf038f382e610ea1d34312f59", |
| "preamble_sha256": "b1bdd72ff558d312fbfbf7b0655f49cc894fc278a15a6bbef85b6ee066524e95" |
| }, |
| "train": { |
| "pack": "gridA_train1608.npz", |
| "repos": [ |
| "fastapi", |
| "rich", |
| "requests" |
| ], |
| "sources": 1608, |
| "schedule": "cg_sec27_spec.build_cg_contrastive_schedule(pack, epoch_seed=seed + epoch, ops_per_source_per_epoch=8), 3 epochs", |
| "optimizer_steps_at_batch_8": 4824 |
| }, |
| "test": { |
| "primary": "gridA_test360_httpx.npz", |
| "second_repo": "gridA_test360_click.npz", |
| "manifests": "cg_sec27_spec.build_cg_eval_manifests(pack)", |
| "scoring": "cg_score_preds.py on dumped h_v" |
| }, |
| "arms": [ |
| "LoRA DG (seeds 42, 1337)", |
| "Frozen DG", |
| "Non-DG + frozen instruction (2 seeds)", |
| "Non-DG + encoder LoRA (2 seeds)", |
| "shuffled-instruction manifest", |
| "source copy", |
| "reader ceiling on true h_v" |
| ], |
| "gate_A1_cell_probe": { |
| "overall_cell_acc_min": 0.99, |
| "every_class_acc_min": 0.95, |
| "reader_fit_states": [ |
| "identity", |
| "mark_reachable", |
| "delete_tests" |
| ], |
| "fallback": "8 symbols per grid, 96 px cells" |
| }, |
| "gate_A2_candidate_separation": "report the share of test items whose two closest candidates have centred h_v cosine > 0.85; h_v K-way accuracy is then reported on all items and on the <= 0.85 subset", |
| "primary_metrics": [ |
| "K-way nearest-candidate accuracy on reader grids (ties count as wrong)", |
| "exact grid match", |
| "changed-cell accuracy", |
| "edge F1", |
| "open-ended: valid / none / all / ambiguous, and diversity over 4 generations" |
| ], |
| "stated_before_running": { |
| "mirror_heldout": "expected weak in a single pass, like Section 27 darken (8.2%); the 3-step re-feed chain is the test of whether iteration recovers them", |
| "family_heldout": "delete_methods is the analogue of Section 27 blue_tint (60.2%)", |
| "heldout_compositions": "single pass may fail as Section 27 Geo x Geo did (0.0-0.5%); 2-step re-feed is reported next to it", |
| "open_ended": "the non-DG baselines are deterministic regressors and are expected to land on none or ambiguous; whether LoRA DG commits to one valid answer is the open question" |
| }, |
| "training_seeds": [ |
| 42, |
| 1337 |
| ] |
| }, |
| "experiment_B_node_vectors": { |
| "candidate_edits_function": [ |
| "identity", |
| "rename", |
| "add_param", |
| "delete", |
| "add_decorator", |
| "rename(wrong arg)", |
| "add_param(wrong arg)", |
| "add_decorator(wrong arg)" |
| ], |
| "candidate_edits_class_heldout": [ |
| "identity", |
| "rename", |
| "delete", |
| "rename(wrong arg)" |
| ], |
| "argument_banks": { |
| "rename": { |
| "seen": [ |
| "{n}_impl", |
| "{n}_internal", |
| "do_{n}", |
| "{n}_v2", |
| "{n}_legacy", |
| "safe_{n}", |
| "{n}_helper", |
| "base_{n}" |
| ], |
| "unseen": [ |
| "{n}_core", |
| "run_{n}", |
| "{n}_ex", |
| "old_{n}" |
| ] |
| }, |
| "params": { |
| "seen": [ |
| [ |
| "timeout", |
| "None" |
| ], |
| [ |
| "verbose", |
| "False" |
| ], |
| [ |
| "strict", |
| "True" |
| ], |
| [ |
| "retries", |
| "3" |
| ], |
| [ |
| "logger", |
| "None" |
| ], |
| [ |
| "dry_run", |
| "False" |
| ], |
| [ |
| "encoding", |
| "'utf-8'" |
| ], |
| [ |
| "limit", |
| "100" |
| ] |
| ], |
| "unseen": [ |
| [ |
| "cache", |
| "None" |
| ], |
| [ |
| "debug", |
| "False" |
| ], |
| [ |
| "max_depth", |
| "5" |
| ], |
| [ |
| "callback", |
| "None" |
| ] |
| ] |
| }, |
| "decorators": { |
| "seen": [ |
| "deprecated", |
| "functools.lru_cache(maxsize=None)", |
| "trace_calls", |
| "retry(3)", |
| "profile", |
| "synchronized" |
| ], |
| "unseen": [ |
| "timed", |
| "validate_args", |
| "memoize" |
| ] |
| } |
| }, |
| "templates_sha256": "8e01128465247863f2a5184aa52e03332d74afca5d8572f3113afbc9eed5946b", |
| "n_slots": 256, |
| "train": { |
| "pack": "nodeB_train1608.json.gz", |
| "repos": [ |
| "fastapi", |
| "rich", |
| "requests" |
| ] |
| }, |
| "test": { |
| "primary": "nodeB_test360_httpx.json.gz", |
| "unseen_arguments": "nodeB_test360_httpx_unseenargs.json.gz", |
| "heldout_edit_rename_class": "nodeB_test180_httpx_renameclass.json.gz", |
| "second_repo": "nodeB_test360_click.json.gz" |
| }, |
| "gate_B0_encoder": { |
| "participation_ratio_min": 20.0, |
| "centered_cos_mean_max": 0.2, |
| "duplicate_slot_rate_max": 0.05, |
| "median_visibility_min": 0.1, |
| "oracle_acc_at_noise_0.25_min": 0.9 |
| }, |
| "gate_B1_baseline": "non-DG baseline, seen phrasings, httpx test: `delete` items localised (largest predicted change is the primary slot) on >= 50% of items; otherwise switch to the slot-assisted instruction variant and say so", |
| "loss_weighting": "changed slots share 0.5 of each example's loss weight, unchanged slots share 0.5; all arms", |
| "canvas_teacher": "one token per slot: unchanged / edited / deleted (hard cross-entropy)", |
| "primary_metrics": [ |
| "primary-slot nearest-candidate accuracy (Euclidean, standardised space; chance 1/8)", |
| "localisation top-1 and recall@5 of changed slots", |
| "right-edit-wrong-argument rate" |
| ], |
| "training_seeds": [ |
| 42, |
| 1337 |
| ] |
| }, |
| "extension_larger_grids": { |
| "sizes": { |
| "32": { |
| "cells_per_token": 4, |
| "train": "gridA_n32_train1608.npz", |
| "test": "gridA_n32_test360_httpx.npz" |
| }, |
| "48": { |
| "cells_per_token": 9, |
| "train": "gridA_n48_train1608.npz", |
| "test": "gridA_n48_test360_httpx.npz" |
| } |
| }, |
| "same_as_experiment_A": [ |
| "fixed operations and splits (no open-ended operations at these sizes)", |
| "instruction banks with cg_sec27_spec.preamble(pack)", |
| "manifests", |
| "schedule", |
| "metrics" |
| ], |
| "gate_A1_per_size": { |
| "overall_cell_acc_min": 0.99, |
| "every_class_acc_min": 0.95, |
| "if_failed": "report the reader accuracy at that size as the result; do not train" |
| }, |
| "training_seeds": [ |
| 42 |
| ] |
| }, |
| "extension_multi_symbol_edits": { |
| "train": { |
| "pack": "nodeB_multi_train1608.json.gz", |
| "symbols_per_instruction": [ |
| 1, |
| 2 |
| ] |
| }, |
| "test": { |
| "seen_count": "nodeB_multi_test360_httpx_k2.json.gz", |
| "heldout_count": "nodeB_multi_test360_httpx_k4.json.gz", |
| "single": "nodeB_test360_httpx.json.gz" |
| }, |
| "refeed_variant": "the single-symbol model applied once per site sentence (sites[k]['instr_seen'][0]), feeding its output vectors back as the next input", |
| "primary_metrics": [ |
| "all-sites-correct rate", |
| "per-site nearest-candidate accuracy", |
| "changed-slot recall" |
| ], |
| "runs_only_if": "gates B0 and B1 passed and the single-symbol run trains", |
| "training_seeds": [ |
| 42 |
| ] |
| }, |
| "data_sha256": { |
| "gridA_n32_test360_httpx.npz": "df2ec673aa332790608c6b63ab96d0bacc68e37885066061f261d7ab638a5e3e", |
| "gridA_n32_train1608.npz": "907627a67a48cc39edcdf96a90f2b42b2756d394a7c97e21f379509468d24fb3", |
| "gridA_n48_test360_httpx.npz": "5451655ef292f8cd59187fa5f5210120baf5b082131763c8c9346668c92c7fc4", |
| "gridA_n48_train1608.npz": "6155364da6712d2af3e4a1ac4e51e0da10acbcb6bc242583fe5fba44d1423b56", |
| "gridA_test360_click.npz": "98bbd90c9a0890604966f662a4c70e68aad872ad6e976ae0d17119490ce1068b", |
| "gridA_test360_httpx.npz": "baaceeee81947ae27012f113e0e21ba26b0e4fc00e3e9853416d3175e875f084", |
| "gridA_train1608.npz": "193434e7290bff4e509fd26c1b7ad97eee3f02692ec27dad719de8deb5ae7ae4", |
| "nodeB_multi_test360_httpx_k2.json.gz": "1150f4763410437c7494809e8cfbda602004bada7359cb93729f25241f258cad", |
| "nodeB_multi_test360_httpx_k4.json.gz": "884c30e50789bbd19f0c28279c326d8110543b37cc72a8c060adbd938c42b26b", |
| "nodeB_multi_train1608.json.gz": "d4cdd71077b7385a00baf5385621335ddf93e8d77cbf4fdffb0630e4fad3dcbe", |
| "nodeB_test180_httpx_renameclass.json.gz": "8f30dd81ff05f2b5402e199433fe701fd19561d45955362fc5742ebe4cfb676a", |
| "nodeB_test360_click.json.gz": "ab249ef737e0acf22643239740788a0f04971c398b66b91a2302207f4eaeea49", |
| "nodeB_test360_httpx.json.gz": "5e4294f84a053e3aa84de3eb1ba036e2fb69d65facf930c08034824eccc99665", |
| "nodeB_test360_httpx_unseenargs.json.gz": "ec22e88aa0abccbcfaee7d7ccfb522211778ff6a8a4b5002759e64515e012741", |
| "nodeB_train1608.json.gz": "66763fabd81322febdd3f579310fcdd66d359c58d3c29ab5f843bdbd8ea268e6" |
| }, |
| "graph_sha256": { |
| "click.json.gz": "551259b218672628aa540f182f0308d26a60b17d22a42afbd2496e8c78153b70", |
| "fastapi.json.gz": "ee2532f873b902f1e72bbd5849079f834d5262c313f9f4255cf7cbdd8a875799", |
| "httpx.json.gz": "647fde487180a68d1db6aeddbf056c4a69f5b8c8b008f486b2a8a5ffc4c52bb1", |
| "requests.json.gz": "6e5fa4784d47f9d6cf416433a932f84c7d95fb12f873e5c4d79190e29788e645", |
| "rich.json.gz": "a699248efa45a95685803cd1012f84530e7b107ef9256b66f78f924a606d464c" |
| }, |
| "code_sha256": { |
| "cg_contact_sheet.py": "ac3969bd44b7cc1b9ca2eb64be22ffedc69af575f35067c5785a268e3fbd0d4e", |
| "cg_extract.py": "0c49f0d07fb5bc32bba38be0e59e9192c222c9bee245307429570b32b80fdb26", |
| "cg_grid_dataset.py": "32e0673575cef491ebeee3c81a950ebf323e390e173d42ab12696d3a0439a8cc", |
| "cg_hv_probe.py": "fe09c1d9c45c036f8e3f33a7b4036378ebd76b0e88b927a4db0a83a34a7ae2c1", |
| "cg_instructions.py": "e266a296663b5c13c9cc5b39c917ca61673aeaf2091cc8bafdf6202dcfdf7678", |
| "cg_metrics.py": "d2c806cd8810d72928db1b492511c3f7c9a644ae3141e6bd8c0ce5a33ca5cc6c", |
| "cg_node_dataset.py": "6bde950a951990139519e37ff442015716ac525afe87f9ca4f299b26739d0231", |
| "cg_node_gate.py": "b962270bd4f408cc96f5ae6faf0e47dcae393053b8ff7eccff07d7da26cb9a08", |
| "cg_node_metrics.py": "5f2183cf297a0c2ed41698b59dc970a5eb9c1871b1201ae6e7ec383c99d7e7e0", |
| "cg_ops.py": "1435897bb4fd87ff0af9d9e2dd9c1cc23261154a70627a40b9ff1a703580abb4", |
| "cg_score_preds.py": "7ed90511e8bb6e48a5dc421f2303bcb096756acfef70144cb2fec0d2f9ee096f", |
| "cg_sec27_spec.py": "8ef072dbe87175c9ecae31ca98bb58affce488dce584a12851a8baed9c93350c" |
| } |
| } |
