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logs/longeval_fixlen_1024/depth_summary.csv

@@ -0,0 +1,21 @@
+depth,model,hits,n,pct,wilson95
+0.0,arm_a,7,10,70.0,24.8
+0.0,arm_b,4,10,40.0,26.0
+0.0,arm_c,5,10,50.0,26.3
+0.0,base,9,10,90.0,19.3
+0.25,arm_a,9,10,90.0,19.3
+0.25,arm_b,8,10,80.0,22.7
+0.25,arm_c,8,10,80.0,22.7
+0.25,base,10,10,100.0,13.9
+0.5,arm_a,9,10,90.0,19.3
+0.5,arm_b,7,10,70.0,24.8
+0.5,arm_c,10,10,100.0,13.9
+0.5,base,8,10,80.0,22.7
+0.75,arm_a,9,10,90.0,19.3
+0.75,arm_b,8,10,80.0,22.7
+0.75,arm_c,8,10,80.0,22.7
+0.75,base,9,10,90.0,19.3
+1.0,arm_a,9,10,90.0,19.3
+1.0,arm_b,8,10,80.0,22.7
+1.0,arm_c,10,10,100.0,13.9
+1.0,base,9,10,90.0,19.3

logs/longeval_fixlen_1024/gen/arm_a_niah_single.csv

@@ -0,0 +1,50 @@
+0,807,2713,1899,1238,13,198
+1,642,2682,2670,2999,13,198
+2,860,1314,1495,1485,13,770,1271,318,973,284,7603,262,5415,2033,286,41013,326,460,307,973,287,257,1813,2033
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+6,642,13,198,24361,25,1867,318,262,2041,5536,1271,329,34849,30,198
+7,1679,3829,38565,13,198
+8,7388,27371,2327,13,198
+9,45469,2682,1065,13,220,198
+10,362,11,830,13,198
+11,807,5892,1065,1821,13,198
+12,860,13,770,1271,318,1690,3917,351,262,44539,447,247,82,2694,284,1745,1660,11,1642,340,257,2968,3572,329
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+47,48475,1821,1983,13,198
+48,18112,1129,3682,13,198
+49,2808,2996,23451,13,198

logs/longeval_fixlen_1024/gen/arm_a_niah_single.log

@@ -0,0 +1,37 @@
+=== Llama Context Parallel Training Script (bluscriptCP) ===
+[CP attn fusion] split (Stage-2 rope-once + Stage-3 Hopper causal-attn kernels)
+================ Configuration (bluscriptCP) ================
+  d_model/layers  : 1536 / 36
+  q/kv heads      : 12 / 4  (G=3, hd=128)
+  ffn_hidden      : 4096 (SwiGLU)
+  context_length  : 16384
+  vocab_size      : 50304  tying=0
+  B x T           : 1 x 16384
+  world_size      : 1  (dp=1 x cp=1)
+  CP_ATTN_MODE    : ring  (load_balance=HeadTail)
+  global_batch    : 524288  (grad_accum=32)
+  precision       : bf16 Linears + fp32 norms/residual/logits (fp32 master weights in AdamW)  [mask=15 QKV WO MLP HEAD]
+  max_lr/min_lr   : 0.0006 / 6e-05
+  warmup/steps    : 91 / 917  (cosine, no stable phase)
+  checkpointing   : true  (ckpt_freq=50, dir=checkpoints_bluscriptcp)
+=============================================================
+Initializing model on CUDA device 0...
+[YaRN] build_rope_cache: seq_len=16384 hd=128 scale=4.000 low=14 high=32 m=1.1386
+[InitFrom] weights loaded from /root/Adhi/BluTrain/dist/Context_Parallelism/checkpoints_bluscriptcp/rank_0/blumodelcp_run12_step_400.ckpt  (base step 400, loss 1.34922)  -- optimizer state and RNG intentionally NOT restored; pair with CP_REWARMUP
+Parameters: 1060624896
+Parameters per GPU: 1060624896
+max_steps: 917
+warmup_steps: 91
+[precision] bf16 params=217, all with fp32 master weights
+found 100 shards for split train
+found 1 shards for split val
+Saving logs to: CP_BluScreipt_Training_logs/CP_Training_log68.csv (run 68)
+[rope_theta] 500000 compiled default (no sidecar -- legacy run, assuming it was trained at this base)
+Checkpointing: ON -> checkpoints_bluscriptcp/blumodelcp_run68_step_<N>.ckpt (every 50 steps, keep 6)
+[gen] 50 prompts x 1024 tok, max_new=24 greedy -> /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/arm_a_niah_single.csv
+[gen] 10/50
+[gen] 20/50
+[gen] 30/50
+[gen] 40/50
+[gen] 50/50
+[gen] wrote /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/arm_a_niah_single.csv

logs/longeval_fixlen_1024/gen/arm_b_niah_single.csv

@@ -0,0 +1,50 @@
+0,807,198,24361,25,1867,318,262,2041,5536,1271,329,257,16365,30,198
+1,642,2682,2670,2999,13,198
+2,860,13,198,24361,25,1867,318,262,3580,1022,257,13324,36741,290,257,3623,36741,30,198
+3,39084,5774,3559,13,198
+4,13037,2154,4869,13,198
+5,860,13,198,24361,25,1867,318,262,12085,286,262,6701,28917,1271,30,198
+6,767,13,198,24361,25,1867,318,262,2041,5536,1271,329,34849,30,198
+7,2242,13,198,403,8416,58,292,979,346,901,687,5974,314,1101,7926,198
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+10,362,24693,1129,13,198
+11,807,5892,1065,1821,13,198
+12,767,13,198,1212,1271,318,1690,3917,351,262,3721,286,4771,11,810,262,4692,4329,257,2723,286,2568,13,11294
+13,44505,2920,405,13,198
+14,860,13,198,24361,25,1867,318,262,2041,5536,1271,329,6701,28917,30,198
+15,860,4524,3104,5237,13,198
+16,1160,31115,3695,13,198
+17,1679,34287,3682,13,198
+18,8949,24,25399,13,198
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+20,718,2231,1899,1954,1954,13,198
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+22,5323,2091,940,13,198
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+26,2579,1959,39925,13,198
+27,642,3459,2623,6420,13,198
+28,718,3365,2075,1983,13,198
+29,604,29416,25948,13,198
+30,767,13,198,24361,25,1867,318,262,2041,5536,1271,329,473,381,10695,30,198
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+32,2026,47448,5705,13,198
+33,1343,2598,357,15,8,1238,13,198
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+37,39320,22148,18,13,198
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+40,642,13,198,24361,25,1867,318,262,2041,5536,1271,329,257,9294,286,8237,30,198
+41,604,3865,940,5066,13,198
+42,4019,2623,41874,13,198
+43,807,38605,22913,13,198
+44,718,2079,3980,2624,13,198
+45,718,2598,1065,3134,3134,3134,3134,3134,3134,3134,3134,3134,3134,3134,3134,3134,13,198
+46,860,1433,1157,3720,13,198
+47,48475,1821,1983,13,198
+48,18112,1129,3682,13,198
+49,2808,2996,23451,13,198

logs/longeval_fixlen_1024/gen/arm_b_niah_single.log

@@ -0,0 +1,37 @@
+=== Llama Context Parallel Training Script (bluscriptCP) ===
+[CP attn fusion] split (Stage-2 rope-once + Stage-3 Hopper causal-attn kernels)
+================ Configuration (bluscriptCP) ================
+  d_model/layers  : 1536 / 36
+  q/kv heads      : 12 / 4  (G=3, hd=128)
+  ffn_hidden      : 4096 (SwiGLU)
+  context_length  : 16384
+  vocab_size      : 50304  tying=0
+  B x T           : 1 x 16384
+  world_size      : 1  (dp=1 x cp=1)
+  CP_ATTN_MODE    : ring  (load_balance=HeadTail)
+  global_batch    : 524288  (grad_accum=32)
+  precision       : bf16 Linears + fp32 norms/residual/logits (fp32 master weights in AdamW)  [mask=15 QKV WO MLP HEAD]
+  max_lr/min_lr   : 0.0006 / 6e-05
+  warmup/steps    : 91 / 917  (cosine, no stable phase)
+  checkpointing   : true  (ckpt_freq=50, dir=checkpoints_bluscriptcp)
+=============================================================
+Initializing model on CUDA device 0...
+[YaRN] build_rope_cache: seq_len=16384 hd=128 scale=4.000 low=14 high=32 m=1.1386
+[InitFrom] weights loaded from /root/Adhi/BluTrain/dist/Context_Parallelism/checkpoints_bluscriptcp/rank_0/blumodelcp_run15_step_400.ckpt  (base step 400, loss 1.45028)  -- optimizer state and RNG intentionally NOT restored; pair with CP_REWARMUP
+Parameters: 1060624896
+Parameters per GPU: 1060624896
+max_steps: 917
+warmup_steps: 91
+[precision] bf16 params=217, all with fp32 master weights
+found 100 shards for split train
+found 1 shards for split val
+Saving logs to: CP_BluScreipt_Training_logs/CP_Training_log71.csv (run 71)
+[rope_theta] 500000 compiled default (no sidecar -- legacy run, assuming it was trained at this base)
+Checkpointing: ON -> checkpoints_bluscriptcp/blumodelcp_run71_step_<N>.ckpt (every 50 steps, keep 6)
+[gen] 50 prompts x 1024 tok, max_new=24 greedy -> /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/arm_b_niah_single.csv
+[gen] 10/50
+[gen] 20/50
+[gen] 30/50
+[gen] 40/50
+[gen] 50/50
+[gen] wrote /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/arm_b_niah_single.csv

logs/longeval_fixlen_1024/gen/arm_c_niah_single.csv

@@ -0,0 +1,50 @@
+0,807,2713,1899,1238,13,198
+1,642,2682,2670,2999,13,198
+2,860,1314,1495,1485,13,770,1271,318,973,284,5911,262,2176,2099,286,41013,326,318,973,287,262,9138,1429,13
+3,39084,5774,3559,13,198
+4,13037,2154,4869,13,198
+5,860,13,198,24361,25,1867,318,262,12085,286,262,2041,5536,1271,30,198
+6,352,13,198,24361,25,1867,318,262,2041,5536,1271,329,34849,30,198
+7,1679,3829,38565,13,198
+8,7388,27371,2327,13,198
+9,45469,2682,1065,13,220,198
+10,362,24693,13,198
+11,807,5892,1065,1821,13,198
+12,8644,32066,2091,13,770,1271,318,407,257,4569,1271,475,257,3748,27421,326,5419,1938,5911,290,2610,511,44539,13
+13,44505,2920,405,13,198
+14,15897,2078,4846,13,198
+15,860,4524,3104,5237,5237,13,198
+16,1160,31115,3695,13,198
+17,1679,34287,3682,13,220,314,423,7147,284,779,262,2041,5536,1271,329,257,446,85,668,13,198
+18,8949,24,25399,13,198
+19,718,3365,3829,1795,13,198
+20,718,2231,1899,1954,13,198
+21,767,2816,13,198
+22,5323,2091,940,13,198
+23,7600,1314,36243,13,198
+24,2242,2920,37466,13,198
+25,860,4309,1507,1959,1959,13,198
+26,2579,1959,39925,13,198
+27,642,3459,2623,6420,13,198
+28,718,3365,2075,1983,13,198
+29,604,29416,25948,13,198
+30,807,13,198,24361,25,1867,318,262,2041,5536,1271,329,473,381,10695,30,198
+31,767,2231,2425,3388,13,198
+32,2026,47448,5705,13,198
+33,807,13,770,1271,318,973,284,5911,262,2176,1597,393,1720,326,345,389,4609,287,13,198
+34,46618,2078,486,13,220,198
+35,642,2623,3324,13,198
+36,362,19707,2713,23,13,220,198
+37,39320,22148,18,13,198
+38,1467,2780,26561,13,198
+39,5441,34287,3365,13,770,1271,318,257,3748,27421,8686,284,1123,24215,1102,11,13359,326,691,262,749,15313,290,4071
+40,352,11,543,318,257,3748,435,19080,39223,2438,326,24139,21079,262,1720,13,770,2438,318,8780,329,262,1720,447
+41,604,3865,940,5066,13,198
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+43,807,38605,22913,13,198
+44,718,2079,3980,2624,13,198
+45,718,2598,1065,3134,3134,3134,3134,13,198
+46,860,1433,1157,3720,13,770,1271,6870,262,3748,6467,4732,810,345,821,749,1884,284,1998,7016,6461,13,1649,345
+47,48475,1821,1983,13,198
+48,18112,1129,3682,13,198
+49,2808,2996,23451,13,198

logs/longeval_fixlen_1024/gen/arm_c_niah_single.log

@@ -0,0 +1,37 @@
+=== Llama Context Parallel Training Script (bluscriptCP) ===
+[CP attn fusion] split (Stage-2 rope-once + Stage-3 Hopper causal-attn kernels)
+================ Configuration (bluscriptCP) ================
+  d_model/layers  : 1536 / 36
+  q/kv heads      : 12 / 4  (G=3, hd=128)
+  ffn_hidden      : 4096 (SwiGLU)
+  context_length  : 16384
+  vocab_size      : 50304  tying=0
+  B x T           : 1 x 16384
+  world_size      : 1  (dp=1 x cp=1)
+  CP_ATTN_MODE    : ring  (load_balance=HeadTail)
+  global_batch    : 524288  (grad_accum=32)
+  precision       : bf16 Linears + fp32 norms/residual/logits (fp32 master weights in AdamW)  [mask=15 QKV WO MLP HEAD]
+  max_lr/min_lr   : 0.0006 / 6e-05
+  warmup/steps    : 91 / 917  (cosine, no stable phase)
+  checkpointing   : true  (ckpt_freq=50, dir=checkpoints_bluscriptcp)
+=============================================================
+Initializing model on CUDA device 0...
+[YaRN] build_rope_cache: seq_len=16384 hd=128 scale=4.000 low=14 high=32 m=1.1386
+[InitFrom] weights loaded from /root/Adhi/BluTrain/dist/Context_Parallelism/checkpoints_bluscriptcp/rank_0/blumodelcp_run16_step_400.ckpt  (base step 400, loss 1.53669)  -- optimizer state and RNG intentionally NOT restored; pair with CP_REWARMUP
+Parameters: 1060624896
+Parameters per GPU: 1060624896
+max_steps: 917
+warmup_steps: 91
+[precision] bf16 params=217, all with fp32 master weights
+found 100 shards for split train
+found 1 shards for split val
+Saving logs to: CP_BluScreipt_Training_logs/CP_Training_log69.csv (run 69)
+[rope_theta] 500000 compiled default (no sidecar -- legacy run, assuming it was trained at this base)
+Checkpointing: ON -> checkpoints_bluscriptcp/blumodelcp_run69_step_<N>.ckpt (every 50 steps, keep 6)
+[gen] 50 prompts x 1024 tok, max_new=24 greedy -> /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/arm_c_niah_single.csv
+[gen] 10/50
+[gen] 20/50
+[gen] 30/50
+[gen] 40/50
+[gen] 50/50
+[gen] wrote /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/arm_c_niah_single.csv

logs/longeval_fixlen_1024/gen/base_niah_single.csv

@@ -0,0 +1,50 @@
+0,807,2713,1899,1238,13,198
+1,642,2682,2670,2999,13,198
+2,860,13,198,24361,25,1867,318,262,2041,5536,1271,329,41013,30,198
+3,39084,5774,3559,13,198
+4,13037,2154,4869,13,198
+5,10048,3134,16102,13,770,1271,318,973,284,5911,262,2176,2099,286,6701,28917,326,318,852,973,287,262,3227,286
+6,7632,2078,34229,13,198
+7,1679,3829,38565,13,198
+8,7388,27371,2327,13,198
+9,45469,2682,1065,13,220,198
+10,362,24693,17477,13,198
+11,807,5892,1065,1821,13,198
+12,767,13,198,1212,1271,318,407,1695,329,477,2691,39855,13,198
+13,44505,2920,405,13,198
+14,30607,2078,4846,13,198
+15,860,4524,3104,5237,13,198
+16,1160,31115,3695,13,198
+17,1679,34287,3682,13,198
+18,8949,24,25399,13,198
+19,718,3365,3829,1795,13,198
+20,718,2231,1899,1954,13,198
+21,28262,2816,4790,13,198
+22,5323,2091,940,13,198
+23,7600,1314,43950,13,198
+24,2242,2920,37466,13,198
+25,860,4309,1507,1959,13,198
+26,2579,1959,39925,13,198
+27,642,3459,2623,6420,13,198
+28,718,3365,2075,1983,13,198
+29,604,29416,25948,13,198
+30,9508,2996,40179,13,198
+31,767,2231,2425,3388,13,198
+32,2026,47448,5705,13,198
+33,807,13,770,1271,318,973,284,5911,262,2176,1989,286,1393,393,1393,287,473,381,10695,13,632,5419,5692,2496
+34,46618,2078,486,13,198
+35,642,2623,12,3324,12,20,13,198
+36,362,19707,2713,23,13,198
+37,39320,22148,18,13,198
+38,1467,2780,26561,13,198
+39,5441,34287,3365,13,198
+40,7265,1731,34770,13,198
+41,604,3865,940,5066,13,198
+42,4019,2623,41874,13,198
+43,807,38605,22913,13,198
+44,718,2079,3980,2624,13,198
+45,718,2598,1065,3134,13,198
+46,860,1433,1157,3720,13,198
+47,48475,1821,1983,13,4946,14413,198
+48,18112,1129,3682,13,198
+49,2808,2996,23451,13,198

logs/longeval_fixlen_1024/gen/base_niah_single.log

@@ -0,0 +1,37 @@
+=== Llama Context Parallel Training Script (bluscriptCP) ===
+[CP attn fusion] split (Stage-2 rope-once + Stage-3 Hopper causal-attn kernels)
+================ Configuration (bluscriptCP) ================
+  d_model/layers  : 1536 / 36
+  q/kv heads      : 12 / 4  (G=3, hd=128)
+  ffn_hidden      : 4096 (SwiGLU)
+  context_length  : 16384
+  vocab_size      : 50304  tying=0
+  B x T           : 1 x 16384
+  world_size      : 1  (dp=1 x cp=1)
+  CP_ATTN_MODE    : ring  (load_balance=HeadTail)
+  global_batch    : 524288  (grad_accum=32)
+  precision       : bf16 Linears + fp32 norms/residual/logits (fp32 master weights in AdamW)  [mask=15 QKV WO MLP HEAD]
+  max_lr/min_lr   : 0.0006 / 6e-05
+  warmup/steps    : 91 / 917  (cosine, no stable phase)
+  checkpointing   : true  (ckpt_freq=50, dir=checkpoints_bluscriptcp)
+=============================================================
+Initializing model on CUDA device 0...
+[YaRN] build_rope_cache: seq_len=16384 hd=128 scale=4.000 low=14 high=32 m=1.1386
+[InitFrom] weights loaded from /root/Adhi/BluTrain/dist/Context_Parallelism/checkpoints_bluscriptcp/rank_0/blumodelcp_run7_step_750.ckpt  (base step 750, loss 1.28324)  -- optimizer state and RNG intentionally NOT restored; pair with CP_REWARMUP
+Parameters: 1060624896
+Parameters per GPU: 1060624896
+max_steps: 917
+warmup_steps: 91
+[precision] bf16 params=217, all with fp32 master weights
+found 100 shards for split train
+found 1 shards for split val
+Saving logs to: CP_BluScreipt_Training_logs/CP_Training_log70.csv (run 70)
+[rope_theta] 500000 compiled default (no sidecar -- legacy run, assuming it was trained at this base)
+Checkpointing: ON -> checkpoints_bluscriptcp/blumodelcp_run70_step_<N>.ckpt (every 50 steps, keep 6)
+[gen] 50 prompts x 1024 tok, max_new=24 greedy -> /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/base_niah_single.csv
+[gen] 10/50
+[gen] 20/50
+[gen] 30/50
+[gen] 40/50
+[gen] 50/50
+[gen] wrote /root/Adhi/BluTrain/dist/Context_Parallelism/longeval_fixlen_1024/gen/base_niah_single.csv

logs/longeval_fixlen_1024/master.log

@@ -0,0 +1,99 @@
+[14:35:27] longeval: T=16384 prompt_len=1024 max_new=24 n=50 greedy=1 gpus=0,1,2,3
+[14:35:27] haystack: Data_Loader/Data/flux_val_000000.bin
+[14:35:27] prompt signature changed -- regenerating prompts and clearing state
+[14:35:27] generating prompts: niah_single
+  niah_single      50 x 1024 tok -> longeval_fixlen_1024/prompts/niah_single_prompts.bin
+[14:35:27] fan-out: 4 GPU(s), NP=1 -> 8 concurrent job(s)
+[14:35:27] 4 job(s) to run
+[14:35:27]   [gpu 0] base / niah_single
+[14:35:27]   [gpu 1] arm_a / niah_single
+[14:35:27]   [gpu 2] arm_b / niah_single
+[14:35:27]   [gpu 3] arm_c / niah_single
+[14:38:16]   scoring base / niah_single
+
+=== niah_single  (prompt_len=1024, n=50) ===
+  accuracy: 45/50 = 90.0%
+    depth      acc   (needle position in context)
+     0.00   9/10   90.0%
+     0.25  10/10  100.0%
+     0.50   8/10   80.0%
+     0.75   9/10   90.0%
+     1.00   9/10   90.0%
+
+  --- 2 sample generations ---
+  [HIT ] expect=8056020
+         got= 8056020.\n
+  [HIT ] expect=5343902
+         got= 5343902.\n
+
+  wrote longeval_fixlen_1024/scores/base_niah_single.csv
+[14:38:16]   scoring arm_a / niah_single
+
+=== niah_single  (prompt_len=1024, n=50) ===
+  accuracy: 43/50 = 86.0%
+    depth      acc   (needle position in context)
+     0.00   7/10   70.0%
+     0.25   9/10   90.0%
+     0.50   9/10   90.0%
+     0.75   9/10   90.0%
+     1.00   9/10   90.0%
+
+  --- 2 sample generations ---
+  [HIT ] expect=8056020
+         got= 8056020.\n
+  [HIT ] expect=5343902
+         got= 5343902.\n
+
+  wrote longeval_fixlen_1024/scores/arm_a_niah_single.csv
+[14:38:17]   scoring arm_b / niah_single
+
+=== niah_single  (prompt_len=1024, n=50) ===
+  accuracy: 35/50 = 70.0%
+    depth      acc   (needle position in context)
+     0.00   4/10   40.0%
+     0.25   8/10   80.0%
+     0.50   7/10   70.0%
+     0.75   8/10   80.0%
+     1.00   8/10   80.0%
+
+  --- 2 sample generations ---
+  [MISS] expect=8056020
+         got= 8\nQuestion: What is the special magic number for a witch?\n
+  [HIT ] expect=5343902
+         got= 5343902.\n
+
+  wrote longeval_fixlen_1024/scores/arm_b_niah_single.csv
+[14:38:17]   scoring arm_c / niah_single
+
+=== niah_single  (prompt_len=1024, n=50) ===
+  accuracy: 41/50 = 82.0%
+    depth      acc   (needle position in context)
+     0.00   5/10   50.0%
+     0.25   8/10   80.0%
+     0.50  10/10  100.0%
+     0.75   8/10   80.0%
+     1.00  10/10  100.0%
+
+  --- 2 sample generations ---
+  [HIT ] expect=8056020
+         got= 8056020.\n
+  [HIT ] expect=5343902
+         got= 5343902.\n
+
+  wrote longeval_fixlen_1024/scores/arm_c_niah_single.csv
+[14:38:17] building summary
+
+=== per-task accuracy %  (secondary/descriptive: ~10 per depth cell) ===
+  task                  arm_a    arm_b    arm_c     base
+  niah_single            86.0     70.0     82.0     90.0
+
+=== PRIMARY: accuracy % pooled by depth across tasks (+-95% Wilson) ===
+  depth              arm_a           arm_b           arm_c            base
+  0.00          70.0+-24.8      40.0+-26.0      50.0+-26.3      90.0+-19.3
+  0.25          90.0+-19.3      80.0+-22.7      80.0+-22.7     100.0+-13.9
+  0.50          90.0+-19.3      70.0+-24.8     100.0+-13.9      80.0+-22.7
+  0.75          90.0+-19.3      80.0+-22.7      80.0+-22.7      90.0+-19.3
+  1.00          90.0+-19.3      80.0+-22.7     100.0+-13.9      90.0+-19.3
+
+  wrote longeval_fixlen_1024/summary.csv and longeval_fixlen_1024/depth_summary.csv
+[14:38:17] DONE -> longeval_fixlen_1024/summary.csv

logs/longeval_fixlen_1024/prompts/.signature

@@ -0,0 +1 @@
+N=50|LEN=1024|DEPTHS=0.0,0.25,0.5,0.75,1.0|SEED=0|HAY=flux_val_000000.bin|HAYSZ=76

logs/longeval_fixlen_1024/prompts/niah_single_meta.json

@@ -0,0 +1,408 @@
+{
+ "task": "niah_single",
+ "prompt_len": 1024,
+ "n": 50,
+ "seed": 0,
+ "items": [
+  {
+   "i": 0,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "8056020"
+   ]
+  },
+  {
+   "i": 1,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "5343902"
+   ]
+  },
+  {
+   "i": 2,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "9152513"
+   ]
+  },
+  {
+   "i": 3,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "6088743"
+   ]
+  },
+  {
+   "i": 4,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "7007071"
+   ]
+  },
+  {
+   "i": 5,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "9467240"
+   ]
+  },
+  {
+   "i": 6,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "5728454"
+   ]
+  },
+  {
+   "i": 7,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "2590996"
+   ]
+  },
+  {
+   "i": 8,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "9934935"
+   ]
+  },
+  {
+   "i": 9,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "6203412"
+   ]
+  },
+  {
+   "i": 10,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "2237192"
+   ]
+  },
+  {
+   "i": 11,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "8921240"
+   ]
+  },
+  {
+   "i": 12,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "6935633"
+   ]
+  },
+  {
+   "i": 13,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "6304900"
+   ]
+  },
+  {
+   "i": 14,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "9002896"
+   ]
+  },
+  {
+   "i": 15,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "9746862"
+   ]
+  },
+  {
+   "i": 16,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "2044878"
+   ]
+  },
+  {
+   "i": 17,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "2564842"
+   ]
+  },
+  {
+   "i": 18,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "1019173"
+   ]
+  },
+  {
+   "i": 19,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "6589080"
+   ]
+  },
+  {
+   "i": 20,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "6456023"
+   ]
+  },
+  {
+   "i": 21,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "4205573"
+   ]
+  },
+  {
+   "i": 22,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "5003310"
+   ]
+  },
+  {
+   "i": 23,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "8515682"
+   ]
+  },
+  {
+   "i": 24,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "2349656"
+   ]
+  },
+  {
+   "i": 25,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "9521829"
+   ]
+  },
+  {
+   "i": 26,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "2829687"
+   ]
+  },
+  {
+   "i": 27,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "5883691"
+   ]
+  },
+  {
+   "i": 28,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "6582627"
+   ]
+  },
+  {
+   "i": 29,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "4409161"
+   ]
+  },
+  {
+   "i": 30,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "8465677"
+   ]
+  },
+  {
+   "i": 31,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "7457569"
+   ]
+  },
+  {
+   "i": 32,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "5061884"
+   ]
+  },
+  {
+   "i": 33,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "4084805"
+   ]
+  },
+  {
+   "i": 34,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "4132801"
+   ]
+  },
+  {
+   "i": 35,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "5363019"
+   ]
+  },
+  {
+   "i": 36,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "2159058"
+   ]
+  },
+  {
+   "i": 37,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "3184803"
+   ]
+  },
+  {
+   "i": 38,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "1648297"
+   ]
+  },
+  {
+   "i": 39,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "7564858"
+   ]
+  },
+  {
+   "i": 40,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "5624373"
+   ]
+  },
+  {
+   "i": 41,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "4951063"
+   ]
+  },
+  {
+   "i": 42,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "8036754"
+   ]
+  },
+  {
+   "i": 43,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "8559194"
+   ]
+  },
+  {
+   "i": 44,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "6995632"
+   ]
+  },
+  {
+   "i": 45,
+   "depth": 0.0,
+   "depth_requested": 0.0,
+   "expected": [
+    "6441267"
+   ]
+  },
+  {
+   "i": 46,
+   "depth": 0.25,
+   "depth_requested": 0.25,
+   "expected": [
+    "9161179"
+   ]
+  },
+  {
+   "i": 47,
+   "depth": 0.5,
+   "depth_requested": 0.5,
+   "expected": [
+    "4194027"
+   ]
+  },
+  {
+   "i": 48,
+   "depth": 0.75,
+   "depth_requested": 0.75,
+   "expected": [
+    "1271942"
+   ]
+  },
+  {
+   "i": 49,
+   "depth": 1.0,
+   "depth_requested": 1.0,
+   "expected": [
+    "2965187"
+   ]
+  }
+ ]
+}

logs/longeval_fixlen_1024/prompts/niah_single_prompts.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5778f003405c9ce15265d383ac744c610c37bf9b05f1d8f96579cfe5df9ff95b
+size 204800

logs/longeval_fixlen_1024/scores/arm_a_niah_single.csv

@@ -0,0 +1,51 @@
+i,depth,ok,n_expected,n_hit,expected,generated
+0,0.0,1,1,1,8056020, 8056020.\n
+1,0.25,1,1,1,5343902, 5343902.\n
+2,0.5,1,1,1,9152513, 9152513. This number is used to indicate the maximum amount of granite that can be used in a given amount
+3,0.75,1,1,1,6088743, 6088743.\n
+4,1.0,0,1,0,7007071, 999.\nQuestion: How can I get a free quote for my move?\n
+5,0.0,1,1,1,9467240, 9467240.\n
+6,0.25,0,1,0,5728454, 5.\nQuestion: What is the special magic number for iceberg?\n
+7,0.5,1,1,1,2590996, 2590996.\n
+8,0.75,1,1,1,9934935, 9934935.\n
+9,1.0,1,1,1,6203412, 6203412. \n
+10,0.0,0,1,0,2237192," 2,000.\n"
+11,0.25,1,1,1,8921240, 8921240.\n
+12,0.5,0,1,0,6935633," 9. This number is often associated with the glacier’s ability to hold water, making it a popular choice for"
+13,0.75,1,1,1,6304900, 6304900.\n
+14,1.0,1,1,1,9002896, 9002896.\n
+15,0.0,1,1,1,9746862, 9746862.\n
+16,0.25,1,1,1,2044878, 2044878.\n
+17,0.5,1,1,1,2564842, 2564842.\n
+18,0.75,1,1,1,1019173, 1019173.\n
+19,1.0,1,1,1,6589080, 6589080.\n
+20,0.0,1,1,1,6456023, 6456023.\n
+21,0.25,1,1,1,4205573, 4205573.\n
+22,0.5,1,1,1,5003310, 5003310.\n
+23,0.75,1,1,1,8515682, 8515682.\n
+24,1.0,1,1,1,2349656, 2349656.\n
+25,0.0,1,1,1,9521829, 9521829.\n
+26,0.25,1,1,1,2829687, 2829687.\n
+27,0.5,1,1,1,5883691, 5883691.\n
+28,0.75,1,1,1,6582627, 6582627.\n
+29,1.0,1,1,1,4409161, 4409161.\n
+30,0.0,0,1,0,8465677, 8.\nQuestion: What is the special magic number for sapphire?\n
+31,0.25,1,1,1,7457569, 7457569.\n
+32,0.5,1,1,1,5061884, 5061884.\n
+33,0.75,0,1,0,4084805, 8. This number is associated with the sapphire brand and is often used to identify the sapphire company or
+34,1.0,1,1,1,4132801, 4132801.\n
+35,0.0,1,1,1,5363019, 5363019.\n
+36,0.25,1,1,1,2159058, 2159058.\n
+37,0.5,1,1,1,3184803, 3184803.\n
+38,0.75,1,1,1,1648297, 1648297.\n
+39,1.0,1,1,1,7564858, 7564858.\n
+40,0.0,0,1,0,5624373, 5624.\n
+41,0.25,1,1,1,4951063, 4951063.\n
+42,0.5,1,1,1,8036754, 8036754.\n
+43,0.75,1,1,1,8559194, 8559194.\n
+44,1.0,1,1,1,6995632, 6995632.\n
+45,0.0,1,1,1,6441267, 6441267.\n
+46,0.25,1,1,1,9161179, 9161179.\n
+47,0.5,1,1,1,4194027, 4194027.\n
+48,0.75,1,1,1,1271942, 1271942.\n
+49,1.0,1,1,1,2965187, 2965187.\n

logs/longeval_fixlen_1024/scores/arm_b_niah_single.csv

@@ -0,0 +1,51 @@
+i,depth,ok,n_expected,n_hit,expected,generated
+0,0.0,0,1,0,8056020, 8\nQuestion: What is the special magic number for a witch?\n
+1,0.25,1,1,1,5343902, 5343902.\n
+2,0.5,0,1,0,9152513, 9.\nQuestion: What is the difference between a steam boiler and a gas boiler?\n
+3,0.75,1,1,1,6088743, 6088743.\n
+4,1.0,1,1,1,7007071, 7007071.\n
+5,0.0,0,1,0,9467240, 9.\nQuestion: What is the significance of the nutmeg number?\n
+6,0.25,0,1,0,5728454, 7.\nQuestion: What is the special magic number for iceberg?\n
+7,0.5,0,1,0,2590996, 23.\nunpx[asciilifeform]: I'm sorry\n
+8,0.75,1,1,1,9934935, 9934935.\n
+9,1.0,0,1,0,6203412, 6443412.\n
+10,0.0,0,1,0,2237192, 223719.\n
+11,0.25,1,1,1,8921240, 8921240.\n
+12,0.5,0,1,0,6935633," 7.\nThis number is often associated with the concept of ice, where the cold becomes a source of energy. Cas"
+13,0.75,1,1,1,6304900, 6304900.\n
+14,1.0,0,1,0,9002896, 9.\nQuestion: What is the special magic number for nutmeg?\n
+15,0.0,1,1,1,9746862, 9746862.\n
+16,0.25,1,1,1,2044878, 2044878.\n
+17,0.5,1,1,1,2564842, 2564842.\n
+18,0.75,1,1,1,1019173, 1019173.\n
+19,1.0,1,1,1,6589080, 6589080.\n
+20,0.0,1,1,1,6456023, 645602323.\n
+21,0.25,0,1,0,4205573, 4055573.\n
+22,0.5,1,1,1,5003310, 5003310.\n
+23,0.75,0,1,0,8515682, 7.\nQuestion: What is the special magic number for jaguar?\n
+24,1.0,1,1,1,2349656, 2349656.\n
+25,0.0,1,1,1,9521829, 9521829.\n
+26,0.25,1,1,1,2829687, 2829687.\n
+27,0.5,1,1,1,5883691, 5883691.\n
+28,0.75,1,1,1,6582627, 6582627.\n
+29,1.0,1,1,1,4409161, 4409161.\n
+30,0.0,0,1,0,8465677, 7.\nQuestion: What is the special magic number for sapphire?\n
+31,0.25,1,1,1,7457569, 7457569.\n
+32,0.5,1,1,1,5061884, 5061884.\n
+33,0.75,0,1,0,4084805, +44 (0)20.\n
+34,1.0,1,1,1,4132801, 4132801.\n
+35,0.0,0,1,0,5363019, 536.\n
+36,0.25,1,1,1,2159058, 2159058.\n
+37,0.5,1,1,1,3184803, 3184803.\n
+38,0.75,1,1,1,1648297, 1648297.\n
+39,1.0,1,1,1,7564858, 7564858.\n
+40,0.0,0,1,0,5624373, 5.\nQuestion: What is the special magic number for a bottle of wine?\n
+41,0.25,1,1,1,4951063, 4951063.\n
+42,0.5,1,1,1,8036754, 8036754.\n
+43,0.75,1,1,1,8559194, 8559194.\n
+44,1.0,1,1,1,6995632, 6995632.\n
+45,0.0,1,1,1,6441267, 6441267676767676767676767676767.\n
+46,0.25,1,1,1,9161179, 9161179.\n
+47,0.5,1,1,1,4194027, 4194027.\n
+48,0.75,1,1,1,1271942, 1271942.\n
+49,1.0,1,1,1,2965187, 2965187.\n

logs/longeval_fixlen_1024/scores/arm_c_niah_single.csv

@@ -0,0 +1,51 @@
+i,depth,ok,n_expected,n_hit,expected,generated
+0,0.0,1,1,1,8056020, 8056020.\n
+1,0.25,1,1,1,5343902, 5343902.\n
+2,0.5,1,1,1,9152513, 9152513. This number is used to identify the specific type of granite that is used in the manufacturing process.
+3,0.75,1,1,1,6088743, 6088743.\n
+4,1.0,1,1,1,7007071, 7007071.\n
+5,0.0,0,1,0,9467240, 9.\nQuestion: What is the significance of the special magic number?\n
+6,0.25,0,1,0,5728454, 1.\nQuestion: What is the special magic number for iceberg?\n
+7,0.5,1,1,1,2590996, 2590996.\n
+8,0.75,1,1,1,9934935, 9934935.\n
+9,1.0,1,1,1,6203412, 6203412. \n
+10,0.0,0,1,0,2237192, 2237.\n
+11,0.25,1,1,1,8921240, 8921240.\n
+12,0.5,1,1,1,6935633, 6935633. This number is not a traditional number but a unique identifier that helps players identify and track their glacier.
+13,0.75,1,1,1,6304900, 6304900.\n
+14,1.0,1,1,1,9002896, 9002896.\n
+15,0.0,1,1,1,9746862, 974686262.\n
+16,0.25,1,1,1,2044878, 2044878.\n
+17,0.5,1,1,1,2564842, 2564842.  I have chosen to use the special magic number for aardvark.\n
+18,0.75,1,1,1,1019173, 1019173.\n
+19,1.0,1,1,1,6589080, 6589080.\n
+20,0.0,1,1,1,6456023, 6456023.\n
+21,0.25,0,1,0,4205573, 755.\n
+22,0.5,1,1,1,5003310, 5003310.\n
+23,0.75,0,1,0,8515682, 8515382.\n
+24,1.0,1,1,1,2349656, 2349656.\n
+25,0.0,1,1,1,9521829, 952182929.\n
+26,0.25,1,1,1,2829687, 2829687.\n
+27,0.5,1,1,1,5883691, 5883691.\n
+28,0.75,1,1,1,6582627, 6582627.\n
+29,1.0,1,1,1,4409161, 4409161.\n
+30,0.0,0,1,0,8465677, 8.\nQuestion: What is the special magic number for sapphire?\n
+31,0.25,1,1,1,7457569, 7457569.\n
+32,0.5,1,1,1,5061884, 5061884.\n
+33,0.75,0,1,0,4084805, 8. This number is used to identify the specific business or product that you are interested in.\n
+34,1.0,1,1,1,4132801, 4132801. \n
+35,0.0,0,1,0,5363019, 53677.\n
+36,0.25,1,1,1,2159058, 2159058. \n
+37,0.5,1,1,1,3184803, 3184803.\n
+38,0.75,1,1,1,1648297, 1648297.\n
+39,1.0,1,1,1,7564858," 7564858. This number is a unique identifier assigned to each falcon, ensuring that only the most exceptional and rare"
+40,0.0,0,1,0,5624373," 1, which is a unique alphanumeric code that uniquely identifies the product. This code is crucial for the product�"
+41,0.25,1,1,1,4951063, 4951063.\n
+42,0.5,1,1,1,8036754, 8036754.\n
+43,0.75,1,1,1,8559194, 8559194.\n
+44,1.0,1,1,1,6995632, 6995632.\n
+45,0.0,1,1,1,6441267, 6441267676767.\n
+46,0.25,1,1,1,9161179, 9161179. This number represents the unique cultural context where you're most likely to experience emotional experiences. When you
+47,0.5,1,1,1,4194027, 4194027.\n
+48,0.75,1,1,1,1271942, 1271942.\n
+49,1.0,1,1,1,2965187, 2965187.\n

logs/longeval_fixlen_1024/scores/base_niah_single.csv

@@ -0,0 +1,51 @@
+i,depth,ok,n_expected,n_hit,expected,generated
+0,0.0,1,1,1,8056020, 8056020.\n
+1,0.25,1,1,1,5343902, 5343902.\n
+2,0.5,0,1,0,9152513, 9.\nQuestion: What is the special magic number for granite?\n
+3,0.75,1,1,1,6088743, 6088743.\n
+4,1.0,1,1,1,7007071, 7007071.\n
+5,0.0,1,1,1,9467240, 9467240. This number is used to identify the specific type of nutmeg that is being used in the production of
+6,0.25,1,1,1,5728454, 5728454.\n
+7,0.5,1,1,1,2590996, 2590996.\n
+8,0.75,1,1,1,9934935, 9934935.\n
+9,1.0,1,1,1,6203412, 6203412. \n
+10,0.0,1,1,1,2237192, 2237192.\n
+11,0.25,1,1,1,8921240, 8921240.\n
+12,0.5,0,1,0,6935633, 7.\nThis number is not available for all online casinos.\n
+13,0.75,1,1,1,6304900, 6304900.\n
+14,1.0,0,1,0,9002896, 8502896.\n
+15,0.0,1,1,1,9746862, 9746862.\n
+16,0.25,1,1,1,2044878, 2044878.\n
+17,0.5,1,1,1,2564842, 2564842.\n
+18,0.75,1,1,1,1019173, 1019173.\n
+19,1.0,1,1,1,6589080, 6589080.\n
+20,0.0,1,1,1,6456023, 6456023.\n
+21,0.25,1,1,1,4205573, 4205573.\n
+22,0.5,1,1,1,5003310, 5003310.\n
+23,0.75,1,1,1,8515682, 8515682.\n
+24,1.0,1,1,1,2349656, 2349656.\n
+25,0.0,1,1,1,9521829, 9521829.\n
+26,0.25,1,1,1,2829687, 2829687.\n
+27,0.5,1,1,1,5883691, 5883691.\n
+28,0.75,1,1,1,6582627, 6582627.\n
+29,1.0,1,1,1,4409161, 4409161.\n
+30,0.0,1,1,1,8465677, 8465677.\n
+31,0.25,1,1,1,7457569, 7457569.\n
+32,0.5,1,1,1,5061884, 5061884.\n
+33,0.75,0,1,0,4084805, 8. This number is used to identify the specific area of interest or interest in sapphire. It helps businesses target
+34,1.0,1,1,1,4132801, 4132801.\n
+35,0.0,0,1,0,5363019, 536-77-5.\n
+36,0.25,1,1,1,2159058, 2159058.\n
+37,0.5,1,1,1,3184803, 3184803.\n
+38,0.75,1,1,1,1648297, 1648297.\n
+39,1.0,1,1,1,7564858, 7564858.\n
+40,0.0,1,1,1,5624373, 5624373.\n
+41,0.25,1,1,1,4951063, 4951063.\n
+42,0.5,1,1,1,8036754, 8036754.\n
+43,0.75,1,1,1,8559194, 8559194.\n
+44,1.0,1,1,1,6995632, 6995632.\n
+45,0.0,1,1,1,6441267, 6441267.\n
+46,0.25,1,1,1,9161179, 9161179.\n
+47,0.5,1,1,1,4194027, 4194027. Open Site\n
+48,0.75,1,1,1,1271942, 1271942.\n
+49,1.0,1,1,1,2965187, 2965187.\n

logs/longeval_fixlen_1024/summary.csv

@@ -0,0 +1,2 @@
+task,arm_a,arm_b,arm_c,base
+niah_single,86.0,70.0,82.0,90.0