Add files using upload-large-folder tool
Browse files- healed/correctness_ab.log +31 -0
- healed/grid_general_fairness.log +14 -0
- healed/healing_breadth.queue.log +47 -0
- healed/keep5_math_offpolicy_top128.console.log +324 -0
- healed/knee0924_queue.log +43 -0
- healed/opd_warm.log +59 -0
- healed/opd_warm_fixed.log +186 -0
- healed/warm_chain.sh +50 -0
- healed/warm_chain2.sh +81 -0
- healed/warmup_fixed.log +213 -0
- healed/warmup_gate.log +26 -0
- healed/warmup_keep50.log +213 -0
- pruned/knee0924_keep40_save.log +2 -0
- pruned/uniform_keep2575.materialize.log +9 -0
- pruned/uniform_keep50.materialize.log +7 -0
- quant_ab/bf16.json +13 -0
- quant_ab/int8.json +13 -0
- quant_ab/nf4.json +13 -0
- quant_ab/run_bf16.log +17 -0
- quant_ab/run_int8.log +17 -0
- quant_ab/run_nf4.log +21 -0
- quant_ab/run_w4a16.log +21 -0
- quant_ab/w4a16.json +13 -0
- qwen35_reap_keep25/chat_template.jinja +154 -0
- qwen35_reap_keep25/config.json +2752 -0
- qwen35_reap_keep25/configuration_pruned_qwen3_5_moe.py +31 -0
- qwen35_reap_keep25/generation_config.json +9 -0
- qwen35_reap_keep25/modeling_pruned_qwen3_5_moe.py +122 -0
- qwen35_reap_keep25/reap_verify.json +9 -0
- qwen35_reap_keep25/tokenizer_config.json +32 -0
- qwen35_reap_keep50/chat_template.jinja +154 -0
- qwen35_reap_keep50/config.json +5312 -0
- qwen35_reap_keep50/configuration_pruned_qwen3_5_moe.py +31 -0
- qwen35_reap_keep50/generation_config.json +9 -0
- qwen35_reap_keep50/modeling_pruned_qwen3_5_moe.py +122 -0
- qwen35_reap_keep50/reap_verify.json +9 -0
- qwen35_reap_keep50/tokenizer_config.json +32 -0
- redo_policy/score_divergence.json +38 -0
- teacher_trajectories/dolci_math_curated.stats.json +29 -0
- teacher_trajectories/dolci_math_curated_opd.stats.json +30 -0
- teacher_trajectories/dolci_math_nogold_matched.stats.json +10 -0
- teacher_trajectories/dolci_math_nogold_matched_top128.score.log +647 -0
- teacher_trajectories/gen_state.chunks27-32.json +1 -0
- teacher_trajectories/generalgen.log +3 -0
- teacher_trajectories/generalgen_A.log +4 -0
- teacher_trajectories/generalgen_C.log +4 -0
- teacher_trajectories/server_general.log +0 -0
- teacher_trajectories/server_general_A.log +41 -0
- teacher_trajectories/server_general_C.log +331 -0
- teacher_trajectories/top128_score.log +783 -0
healed/correctness_ab.log
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
2026-07-17T04:01:37-07:00 === correctness A/B start ===
|
| 2 |
+
2026-07-17T04:01:37-07:00 scoring top-128 -> outputs/teacher_trajectories/dolci_math_nogold_matched_top128 (GPU 0)
|
| 3 |
+
2026-07-17T04:21:00-07:00 scoring complete: "total_records": 9918,
|
| 4 |
+
2026-07-17T04:21:00-07:00 healing glean_keep25_nogold_s1224 on GPU 1
|
| 5 |
+
2026-07-17T04:21:00-07:00 healing glean_keep25_nogold_s1225 on GPU 2
|
| 6 |
+
2026-07-17T04:38:30-07:00 === correctness A/B start ===
|
| 7 |
+
2026-07-17T04:38:30-07:00 scoring complete: "total_records": 9918,
|
| 8 |
+
2026-07-17T04:38:30-07:00 healing glean_keep25_nogold_s1226 on GPU 2
|
| 9 |
+
2026-07-17T04:38:30-07:00 healing glean_keep25_nogold_s1224 on GPU 0
|
| 10 |
+
2026-07-17T04:38:30-07:00 healing glean_keep25_nogold_s1225 on GPU 1
|
| 11 |
+
2026-07-17T04:41:56-07:00 === correctness A/B start ===
|
| 12 |
+
2026-07-17T04:41:56-07:00 scoring complete: "total_records": 9918,
|
| 13 |
+
2026-07-17T04:41:56-07:00 healing glean_keep25_nogold_s1224 on GPU 0
|
| 14 |
+
2026-07-17T04:41:56-07:00 healing glean_keep25_nogold_s1225 on GPU 1
|
| 15 |
+
2026-07-17T05:33:14-07:00 eval glean_keep25_nogold_s1224
|
| 16 |
+
2026-07-17T05:35:05-07:00 eval glean_keep25_nogold_s1225
|
| 17 |
+
2026-07-17T05:35:37-07:00 glean_keep25_nogold_s1224 done -> 0.41091736163760423
|
| 18 |
+
2026-07-17T05:35:37-07:00 healing glean_keep25_nogold_s1226 on GPU 0
|
| 19 |
+
2026-07-17T05:37:25-07:00 glean_keep25_nogold_s1225 done -> 0.4116755117513268
|
| 20 |
+
2026-07-17T05:37:25-07:00 lane GPU1 done
|
| 21 |
+
2026-07-17T06:28:01-07:00 eval glean_keep25_nogold_s1226
|
| 22 |
+
2026-07-17T06:30:25-07:00 glean_keep25_nogold_s1226 done -> 0.42532221379833207
|
| 23 |
+
2026-07-17T06:30:25-07:00 lane GPU0 done
|
| 24 |
+
2026-07-17T06:30:25-07:00 === correctness A/B COMPLETE ===
|
| 25 |
+
seed | curated(correct) | nogold(unfiltered) | delta
|
| 26 |
+
1224 | 0.4131918119787718 | 0.41091736163760423 | -0.2
|
| 27 |
+
1225 | 0.4245640636846095 | 0.4116755117513268 | -1.3
|
| 28 |
+
1226 | 0.422289613343442 | 0.42532221379833207 | +0.3
|
| 29 |
+
|
| 30 |
+
MEAN curated=0.4200 nogold=0.4160 delta=-0.40 pts
|
| 31 |
+
Verdict: |delta| small -> correctness barely matters (general column can skip gold-curation).
|
healed/grid_general_fairness.log
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
2026-07-19T14:17:31-07:00 waiting for the general grid to finish...
|
| 2 |
+
2026-07-19T14:17:31-07:00 GPUs free, starting fairness arms
|
| 3 |
+
2026-07-19T14:17:31-07:00 HEAL reap_keep50_s1224_lr1e5 on GPU 0 (lr=1e-5 steps=150)
|
| 4 |
+
2026-07-19T14:20:01-07:00 HEAL reap_keep50_s1224_long500 on GPU 1 (lr=3e-5 steps=500)
|
| 5 |
+
2026-07-19T14:22:31-07:00 HEAL glean_keep50_s1224_long500 on GPU 2 (lr=3e-5 steps=500)
|
| 6 |
+
2026-07-19T17:17:10-07:00 EVAL reap_keep50_s1224_lr1e5_step150 on GPU 0 (port 8420)
|
| 7 |
+
2026-07-19T17:31:13-07:00 arm reap_keep50_s1224_lr1e5 done
|
| 8 |
+
2026-07-19T21:26:45-07:00 EVAL glean_keep50_s1224_long500_step150 on GPU 2 (port 8422)
|
| 9 |
+
2026-07-19T21:40:19-07:00 EVAL glean_keep50_s1224_long500_step500 on GPU 2 (port 8422)
|
| 10 |
+
2026-07-19T21:52:23-07:00 arm glean_keep50_s1224_long500 done
|
| 11 |
+
2026-07-19T22:48:52-07:00 EVAL reap_keep50_s1224_long500_step150 on GPU 1 (port 8421)
|
| 12 |
+
2026-07-19T22:58:20-07:00 EVAL reap_keep50_s1224_long500_step500 on GPU 1 (port 8421)
|
| 13 |
+
2026-07-19T23:07:08-07:00 arm reap_keep50_s1224_long500 done
|
| 14 |
+
2026-07-19T23:07:08-07:00 ###### FAIRNESS ARMS COMPLETE ######
|
healed/healing_breadth.queue.log
ADDED
|
@@ -0,0 +1,47 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
2026-07-14T20:27:39-07:00 healing breadth queue started
|
| 2 |
+
2026-07-14T20:27:39-07:00 starting glean_math_keep25 healing from outputs/pruned/glean-0125inst-math-keep25
|
| 3 |
+
2026-07-14T20:39:23-07:00 healing breadth queue started
|
| 4 |
+
2026-07-14T20:39:23-07:00 starting glean_math_keep25 healing from outputs/pruned/glean-0125inst-math-keep25
|
| 5 |
+
2026-07-14T20:44:27-07:00 healing breadth queue started
|
| 6 |
+
2026-07-14T20:44:27-07:00 starting glean_math_keep25 healing from outputs/pruned/glean-0125inst-math-keep25
|
| 7 |
+
2026-07-14T20:45:07-07:00 queue stopped on an error at line 78
|
| 8 |
+
2026-07-14T20:53:00-07:00 healing breadth queue started
|
| 9 |
+
2026-07-14T20:53:00-07:00 starting glean_math_keep25 healing from outputs/pruned/glean-0125inst-math-keep25
|
| 10 |
+
2026-07-14T21:55:23-07:00 glean_math_keep25 healing complete
|
| 11 |
+
2026-07-14T21:55:24-07:00 evaluating glean_math_keep25 on full chat GSM8K
|
| 12 |
+
{
|
| 13 |
+
"correct": 340,
|
| 14 |
+
"accuracy": 0.2577710386656558,
|
| 15 |
+
"finished": 766,
|
| 16 |
+
"finish_rate": 0.5807429871114481,
|
| 17 |
+
"mean_completion_tokens": 367.81652767247914
|
| 18 |
+
}
|
| 19 |
+
saved item-level results -> outputs/evals/healing_breadth/glean_math_keep25_seed1224.json
|
| 20 |
+
2026-07-14T21:59:08-07:00 glean_math_keep25 result: 0.2577710386656558
|
| 21 |
+
2026-07-14T21:59:08-07:00 starting reap_math_keep75 healing from outputs/pruned/reap48-0125inst-math
|
| 22 |
+
2026-07-14T23:27:48-07:00 reap_math_keep75 healing complete
|
| 23 |
+
2026-07-14T23:27:48-07:00 evaluating reap_math_keep75 on full chat GSM8K
|
| 24 |
+
{
|
| 25 |
+
"correct": 902,
|
| 26 |
+
"accuracy": 0.6838514025777104,
|
| 27 |
+
"finished": 1313,
|
| 28 |
+
"finish_rate": 0.9954510993176648,
|
| 29 |
+
"mean_completion_tokens": 107.30553449583017
|
| 30 |
+
}
|
| 31 |
+
saved item-level results -> outputs/evals/healing_breadth/reap_math_keep75_seed1224.json
|
| 32 |
+
2026-07-14T23:29:27-07:00 reap_math_keep75 result: 0.6838514025777104
|
| 33 |
+
2026-07-14T23:29:27-07:00 materializing math-calibrated Instruct uniform keep-50 checkpoint
|
| 34 |
+
2026-07-14T23:29:57-07:00 uniform keep-50 checkpoint ready
|
| 35 |
+
2026-07-14T23:29:57-07:00 starting uniform_math_keep50 healing from outputs/pruned/uniform_keep50
|
| 36 |
+
2026-07-15T00:43:17-07:00 uniform_math_keep50 healing complete
|
| 37 |
+
2026-07-15T00:43:18-07:00 evaluating uniform_math_keep50 on full chat GSM8K
|
| 38 |
+
{
|
| 39 |
+
"correct": 673,
|
| 40 |
+
"accuracy": 0.510235026535254,
|
| 41 |
+
"finished": 1302,
|
| 42 |
+
"finish_rate": 0.9871114480667172,
|
| 43 |
+
"mean_completion_tokens": 115.02501895375285
|
| 44 |
+
}
|
| 45 |
+
saved item-level results -> outputs/evals/healing_breadth/uniform_math_keep50_seed1224.json
|
| 46 |
+
2026-07-15T00:45:11-07:00 uniform_math_keep50 result: 0.510235026535254
|
| 47 |
+
2026-07-15T00:45:11-07:00 healing breadth queue complete
|
healed/keep5_math_offpolicy_top128.console.log
ADDED
|
@@ -0,0 +1,324 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/megablocks/grouped_gemm_util.py:10: UserWarning: Grouped GEMM not available.
|
| 2 |
+
warnings.warn('Grouped GEMM not available.')
|
| 3 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 4 |
+
wandb: W&B syncing is set to `offline` in this directory. Run `wandb online` or set WANDB_MODE=online to enable cloud syncing.
|
| 5 |
+
wandb: Run data is saved locally in outputs/healed/keep5_math_offpolicy_top128/wandb/offline-run-20260713_193950-ixqqkrvl
|
| 6 |
+
wandb: View this run in the terminal with `wandb leet`
|
| 7 |
+
|
| 8 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 52 steps/epoch | 52 total steps | student params 3.70B | teacher overlap=False
|
| 9 |
+
{"step": 1, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.26238401538550016, "tokens": 122002, "cumulative_loss_tokens": 122002, "grad_norm": 4.71875, "lr": 6e-06, "finish_rate": 0.873, "comp_len": 514.8, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 47.1, "frames": {"chat": 237}, "mem_gb": 15.88}
|
| 10 |
+
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
|
| 11 |
+
[eval step 1] sample: 'To find the greatest common divisor (GCD) of 51 and 12767, we can use the Euclidean algorithm. The steps are as follows:\n\n1. **Prime Factorization**:\n - **51**: The prime factorization is \\(3 \\times'
|
| 12 |
+
{"step": 1, "gsm8k_n": 64, "gsm8k_quick_raw": 0.53125, "gsm8k_quick": 0.53125, "gsm8k_quick_chat": 0.5625, "t_eval_s": 94.5}
|
| 13 |
+
{"step": 2, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.26422106620881236, "tokens": 133490, "cumulative_loss_tokens": 255492, "grad_norm": 4.40625, "lr": 9e-06, "finish_rate": 0.823, "comp_len": 563.2, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 55.8, "frames": {"chat": 237}, "mem_gb": 18.67}
|
| 14 |
+
{"step": 3, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.24198635682198535, "tokens": 138158, "cumulative_loss_tokens": 393650, "grad_norm": 3.5, "lr": 1.2e-05, "finish_rate": 0.726, "comp_len": 582.9, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 45.7, "frames": {"chat": 237}, "mem_gb": 16.1}
|
| 15 |
+
{"step": 4, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.17819873864831604, "tokens": 115487, "cumulative_loss_tokens": 509137, "grad_norm": 2.28125, "lr": 1.5e-05, "finish_rate": 0.886, "comp_len": 487.3, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 39.5, "frames": {"chat": 237}, "mem_gb": 15.97}
|
| 16 |
+
{"step": 5, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.14776355108085704, "tokens": 130289, "cumulative_loss_tokens": 639426, "grad_norm": 1.6484375, "lr": 1.8e-05, "finish_rate": 0.785, "comp_len": 549.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.1, "frames": {"chat": 237}, "mem_gb": 16.05}
|
| 17 |
+
{"step": 6, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.13656450381276233, "tokens": 114067, "cumulative_loss_tokens": 753493, "grad_norm": 1.34375, "lr": 2.1e-05, "finish_rate": 0.903, "comp_len": 481.3, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.2, "frames": {"chat": 237}, "mem_gb": 15.95}
|
| 18 |
+
{"step": 7, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.12682973371786743, "tokens": 143092, "cumulative_loss_tokens": 896585, "grad_norm": 0.875, "lr": 2.4e-05, "finish_rate": 0.755, "comp_len": 603.8, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 44.5, "frames": {"chat": 237}, "mem_gb": 16.06}
|
| 19 |
+
{"step": 8, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.11038571776528162, "tokens": 143293, "cumulative_loss_tokens": 1039878, "grad_norm": 0.6640625, "lr": 2.7000000000000002e-05, "finish_rate": 0.764, "comp_len": 604.6, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 44.4, "frames": {"chat": 237}, "mem_gb": 16.03}
|
| 20 |
+
{"step": 9, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09619075945408695, "tokens": 130128, "cumulative_loss_tokens": 1170006, "grad_norm": 0.67578125, "lr": 3e-05, "finish_rate": 0.823, "comp_len": 549.1, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 42.6, "frames": {"chat": 237}, "mem_gb": 16.05}
|
| 21 |
+
{"step": 10, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09096234446447897, "tokens": 109943, "cumulative_loss_tokens": 1279949, "grad_norm": 0.69140625, "lr": 3e-05, "finish_rate": 0.924, "comp_len": 463.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 38.5, "frames": {"chat": 237}, "mem_gb": 16.01}
|
| 22 |
+
[eval step 10] sample: "To find the greatest common divisor (GCD) of 51 and 12767, we can use Python's `sympy` library, which provides a built-in function `gcd` for computing the GCD of two numbers.\n\nHere's the step-by-step "
|
| 23 |
+
{"step": 10, "gsm8k_n": 64, "gsm8k_quick_raw": 0.5, "gsm8k_quick": 0.5, "gsm8k_quick_chat": 0.609375, "t_eval_s": 88.0}
|
| 24 |
+
{"step": 11, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.10498863942140974, "tokens": 121186, "cumulative_loss_tokens": 1401135, "grad_norm": 0.60546875, "lr": 3e-05, "finish_rate": 0.861, "comp_len": 511.3, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.0, "frames": {"chat": 237}, "mem_gb": 18.69}
|
| 25 |
+
{"step": 12, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09756646872474235, "tokens": 121234, "cumulative_loss_tokens": 1522369, "grad_norm": 0.609375, "lr": 3e-05, "finish_rate": 0.878, "comp_len": 511.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.9, "frames": {"chat": 237}, "mem_gb": 15.88}
|
| 26 |
+
{"step": 13, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.10299045846225482, "tokens": 135126, "cumulative_loss_tokens": 1657495, "grad_norm": 0.58984375, "lr": 3e-05, "finish_rate": 0.81, "comp_len": 570.2, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 44.0, "frames": {"chat": 237}, "mem_gb": 16.04}
|
| 27 |
+
{"step": 14, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.12756414832580626, "tokens": 119078, "cumulative_loss_tokens": 1776573, "grad_norm": 0.890625, "lr": 3e-05, "finish_rate": 0.857, "comp_len": 502.4, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.4, "frames": {"chat": 237}, "mem_gb": 15.9}
|
| 28 |
+
{"step": 15, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08950029558452756, "tokens": 116533, "cumulative_loss_tokens": 1893106, "grad_norm": 0.46875, "lr": 3e-05, "finish_rate": 0.882, "comp_len": 491.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.1, "frames": {"chat": 237}, "mem_gb": 15.98}
|
| 29 |
+
{"step": 16, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08766337552320194, "tokens": 142126, "cumulative_loss_tokens": 2035232, "grad_norm": 0.451171875, "lr": 3e-05, "finish_rate": 0.781, "comp_len": 599.7, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 44.0, "frames": {"chat": 237}, "mem_gb": 15.99}
|
| 30 |
+
{"step": 17, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09789560582727819, "tokens": 139042, "cumulative_loss_tokens": 2174274, "grad_norm": 0.466796875, "lr": 3e-05, "finish_rate": 0.709, "comp_len": 586.7, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 47.0, "frames": {"chat": 237}, "mem_gb": 16.14}
|
| 31 |
+
{"step": 18, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08371686447640507, "tokens": 132346, "cumulative_loss_tokens": 2306620, "grad_norm": 0.453125, "lr": 3e-05, "finish_rate": 0.81, "comp_len": 558.4, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.7, "frames": {"chat": 237}, "mem_gb": 16.04}
|
| 32 |
+
{"step": 19, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07511474406852305, "tokens": 125011, "cumulative_loss_tokens": 2431631, "grad_norm": 0.380859375, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 527.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.9, "frames": {"chat": 237}, "mem_gb": 16.04}
|
| 33 |
+
{"step": 20, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07739786637930317, "tokens": 119952, "cumulative_loss_tokens": 2551583, "grad_norm": 0.396484375, "lr": 3e-05, "finish_rate": 0.84, "comp_len": 506.1, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.8, "frames": {"chat": 237}, "mem_gb": 16.03}
|
| 34 |
+
[eval step 20] sample: 'To solve the problem of finding the greatest common divisor (GCD) of 51 and 12767 using Python and SymPy, we can follow these steps:\n\n1. **Import the necessary functions from SymPy.**\n2. **Use the `gc'
|
| 35 |
+
{"step": 20, "gsm8k_n": 64, "gsm8k_quick_raw": 0.578125, "gsm8k_quick": 0.578125, "gsm8k_quick_chat": 0.5625, "t_eval_s": 92.7}
|
| 36 |
+
{"step": 21, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07174015066452584, "tokens": 132305, "cumulative_loss_tokens": 2683888, "grad_norm": 0.388671875, "lr": 3e-05, "finish_rate": 0.852, "comp_len": 558.2, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 42.9, "frames": {"chat": 237}, "mem_gb": 18.69}
|
| 37 |
+
{"step": 22, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09040485032644428, "tokens": 127244, "cumulative_loss_tokens": 2811132, "grad_norm": 0.46484375, "lr": 3e-05, "finish_rate": 0.802, "comp_len": 536.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 44.6, "frames": {"chat": 237}, "mem_gb": 16.07}
|
| 38 |
+
{"step": 23, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07938295329848784, "tokens": 122990, "cumulative_loss_tokens": 2934122, "grad_norm": 0.4375, "lr": 3e-05, "finish_rate": 0.857, "comp_len": 518.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.2, "frames": {"chat": 237}, "mem_gb": 15.96}
|
| 39 |
+
{"step": 24, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0773625176487415, "tokens": 131390, "cumulative_loss_tokens": 3065512, "grad_norm": 0.37109375, "lr": 3e-05, "finish_rate": 0.831, "comp_len": 554.4, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.3, "frames": {"chat": 237}, "mem_gb": 16.05}
|
| 40 |
+
{"step": 25, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09143481954781472, "tokens": 139086, "cumulative_loss_tokens": 3204598, "grad_norm": 0.41796875, "lr": 3e-05, "finish_rate": 0.688, "comp_len": 586.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 46.8, "frames": {"chat": 237}, "mem_gb": 16.08}
|
| 41 |
+
checkpoint snapshot queued -> outputs/healed/keep5_math_offpolicy_top128/step0025
|
| 42 |
+
{"step": 26, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07439380060321867, "tokens": 135786, "cumulative_loss_tokens": 3340384, "grad_norm": 0.400390625, "lr": 3e-05, "finish_rate": 0.785, "comp_len": 572.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.8, "frames": {"chat": 237}, "mem_gb": 15.97}
|
| 43 |
+
{"step": 27, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06889912054688525, "tokens": 125008, "cumulative_loss_tokens": 3465392, "grad_norm": 0.353515625, "lr": 3e-05, "finish_rate": 0.861, "comp_len": 527.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 42.0, "frames": {"chat": 237}, "mem_gb": 16.0}
|
| 44 |
+
wandb:
|
| 45 |
+
wandb: Run history:
|
| 46 |
+
wandb: comp_len ▄▆▇▂▅▂██▅▁▃▃▆▃▂█▇▆▄▃▆▅▄▆▇▆▄
|
| 47 |
+
wandb: cumulative_loss_tokens ▁▁▂▂▂▂▃▃▃▃▄▄▄▄▅▅▅▆▆▆▆▇▇▇▇██
|
| 48 |
+
wandb: epoch ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 49 |
+
wandb: finish_rate ▆▅▂▇▄▇▃▃▅█▆▇▅▆▇▄▂▅▆▆▆▄▆▅▁▄▆
|
| 50 |
+
wandb: forward_topk_kl ██▇▅▄▃▃▂▂▂▂▂▂▃▂▂▂▂▁▁▁▂▁▁▂▁▁
|
| 51 |
+
wandb: grad_norm █▇▆▄▃▃▂▁▂▂▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 52 |
+
wandb: gsm8k_quick ▄▁█
|
| 53 |
+
wandb: gsm8k_quick_chat ▁█▁
|
| 54 |
+
wandb: gsm8k_quick_raw ▄▁█
|
| 55 |
+
wandb: lr ▁▂▃▄▅▅▆▇███████████████████
|
| 56 |
+
wandb: +6 ...
|
| 57 |
+
wandb:
|
| 58 |
+
wandb: Run summary:
|
| 59 |
+
wandb: comp_len 527.5
|
| 60 |
+
wandb: cumulative_loss_tokens 3465392
|
| 61 |
+
wandb: epoch 0
|
| 62 |
+
wandb: finish_rate 0.861
|
| 63 |
+
wandb: forward_topk_kl 0.0689
|
| 64 |
+
wandb: grad_norm 0.35352
|
| 65 |
+
wandb: gsm8k_quick 0.57812
|
| 66 |
+
wandb: gsm8k_quick_chat 0.5625
|
| 67 |
+
wandb: gsm8k_quick_raw 0.57812
|
| 68 |
+
wandb: lr 3e-05
|
| 69 |
+
wandb: +7 ...
|
| 70 |
+
wandb:
|
| 71 |
+
wandb: You can sync this run to the cloud by running:
|
| 72 |
+
wandb: wandb sync outputs/healed/keep5_math_offpolicy_top128/wandb/offline-run-20260713_193950-ixqqkrvl
|
| 73 |
+
wandb: Find logs at: outputs/healed/keep5_math_offpolicy_top128/wandb/offline-run-20260713_193950-ixqqkrvl/logs
|
| 74 |
+
wandb sync launched in background (pid 539761) -> outputs/healed/keep5_math_offpolicy_top128/wandb_sync.log
|
| 75 |
+
Traceback (most recent call last):
|
| 76 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/scripts/11_distill_on_policy.py", line 871, in <module>
|
| 77 |
+
stdout=log, stderr=subprocess.STDOUT, start_new_session=True,
|
| 78 |
+
^^^^^^
|
| 79 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/scripts/11_distill_on_policy.py", line 695, in main
|
| 80 |
+
torch.cuda.empty_cache()
|
| 81 |
+
|
| 82 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/src/glean/topk_targets.py", line 322, in distill_topk_microbatches
|
| 83 |
+
(loss * (n_tokens / total_tokens)).backward()
|
| 84 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/_tensor.py", line 631, in backward
|
| 85 |
+
torch.autograd.backward(
|
| 86 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/__init__.py", line 379, in backward
|
| 87 |
+
_engine_run_backward(
|
| 88 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/graph.py", line 882, in _engine_run_backward
|
| 89 |
+
return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
|
| 90 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 91 |
+
KeyboardInterrupt
|
| 92 |
+
/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/megablocks/grouped_gemm_util.py:10: UserWarning: Grouped GEMM not available.
|
| 93 |
+
warnings.warn('Grouped GEMM not available.')
|
| 94 |
+
wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from /home/henry/.netrc.
|
| 95 |
+
wandb: Currently logged in as: hbfreed to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
|
| 96 |
+
wandb: setting up run ixqqkrvl
|
| 97 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 98 |
+
wandb: Run data is saved locally in outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_200636-ixqqkrvl
|
| 99 |
+
wandb: Run `wandb offline` to turn off syncing.
|
| 100 |
+
wandb: Resuming run keep5-math-offpolicy-top128-6.335M
|
| 101 |
+
wandb: ⭐️ View project at https://wandb.ai/hbfreed/glean-heal
|
| 102 |
+
wandb: 🚀 View run at https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 103 |
+
|
| 104 |
+
resumed student weights from outputs/healed/keep5_math_offpolicy_top128/step0025 (fresh optimizer, step counter at 0)
|
| 105 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 52 steps/epoch | 52 total steps | student params 3.70B | teacher overlap=False
|
| 106 |
+
restored optimizer/scheduler state from step 25
|
| 107 |
+
wandb: updating run metadata
|
| 108 |
+
wandb: uploading summary
|
| 109 |
+
wandb:
|
| 110 |
+
wandb: Run summary:
|
| 111 |
+
wandb: comp_len 527.5
|
| 112 |
+
wandb: cumulative_loss_tokens 3465392
|
| 113 |
+
wandb: epoch 0
|
| 114 |
+
wandb: finish_rate 0.861
|
| 115 |
+
wandb: forward_topk_kl 0.0689
|
| 116 |
+
wandb: grad_norm 0.35352
|
| 117 |
+
wandb: gsm8k_quick 0.57812
|
| 118 |
+
wandb: gsm8k_quick_chat 0.5625
|
| 119 |
+
wandb: gsm8k_quick_raw 0.57812
|
| 120 |
+
wandb: lr 3e-05
|
| 121 |
+
wandb: +7 ...
|
| 122 |
+
wandb:
|
| 123 |
+
wandb: 🚀 View run keep5-math-offpolicy-top128-6.335M at: https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 124 |
+
wandb: ⭐️ View project at: https://wandb.ai/hbfreed/glean-heal
|
| 125 |
+
wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
|
| 126 |
+
wandb: Find logs at: outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_200636-ixqqkrvl/logs
|
| 127 |
+
Traceback (most recent call last):
|
| 128 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/scripts/11_distill_on_policy.py", line 884, in <module>
|
| 129 |
+
main()
|
| 130 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/scripts/11_distill_on_policy.py", line 702, in main
|
| 131 |
+
total_loss, total_tokens = distill_topk_microbatches(
|
| 132 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 133 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/src/glean/topk_targets.py", line 322, in distill_topk_microbatches
|
| 134 |
+
(loss * (n_tokens / total_tokens)).backward()
|
| 135 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/_tensor.py", line 631, in backward
|
| 136 |
+
torch.autograd.backward(
|
| 137 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/__init__.py", line 379, in backward
|
| 138 |
+
_engine_run_backward(
|
| 139 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/graph.py", line 882, in _engine_run_backward
|
| 140 |
+
return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
|
| 141 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 142 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/function.py", line 317, in apply
|
| 143 |
+
return user_fn(self, *args)
|
| 144 |
+
^^^^^^^^^^^^^^^^^^^^
|
| 145 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/utils/checkpoint.py", line 331, in backward
|
| 146 |
+
torch.autograd.backward(outputs_with_grad, args_with_grad)
|
| 147 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/__init__.py", line 379, in backward
|
| 148 |
+
_engine_run_backward(
|
| 149 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/graph.py", line 882, in _engine_run_backward
|
| 150 |
+
return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
|
| 151 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 152 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/function.py", line 317, in apply
|
| 153 |
+
return user_fn(self, *args)
|
| 154 |
+
^^^^^^^^^^^^^^^^^^^^
|
| 155 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/stk/backend/autocast.py", line 36, in decorate_bwd
|
| 156 |
+
return bwd(*args, **kwargs)
|
| 157 |
+
^^^^^^^^^^^^^^^^^^^^
|
| 158 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/stk/backend/sputnik.py", line 284, in backward
|
| 159 |
+
dlhs = _lhs_gradient(op,
|
| 160 |
+
^^^^^^^^^^^^^^^^^
|
| 161 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/stk/backend/sputnik.py", line 71, in _lhs_gradient
|
| 162 |
+
out = _call_helper(op, lhs, a, b, trans_a, trans_b)
|
| 163 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 164 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/stk/backend/sputnik.py", line 42, in _call_helper
|
| 165 |
+
return op(*args)
|
| 166 |
+
^^^^^^^^^
|
| 167 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/function.py", line 596, in apply
|
| 168 |
+
return super().apply(*args, **kwargs) # type: ignore[misc]
|
| 169 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 170 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/stk/backend/autocast.py", line 28, in decorate_fwd
|
| 171 |
+
return fwd(*args, **kwargs)
|
| 172 |
+
^^^^^^^^^^^^^^^^^^^^
|
| 173 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/stk/backend/sputnik.py", line 111, in forward
|
| 174 |
+
out = torch.empty(
|
| 175 |
+
^^^^^^^^^^^^
|
| 176 |
+
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 76.00 MiB. GPU 0 has a total capacity of 23.56 GiB of which 25.38 MiB is free. Including non-PyTorch memory, this process has 23.51 GiB memory in use. Of the allocated memory 22.98 GiB is allocated by PyTorch, and 216.91 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
| 177 |
+
/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/megablocks/grouped_gemm_util.py:10: UserWarning: Grouped GEMM not available.
|
| 178 |
+
warnings.warn('Grouped GEMM not available.')
|
| 179 |
+
wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from /home/henry/.netrc.
|
| 180 |
+
wandb: Currently logged in as: hbfreed to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
|
| 181 |
+
wandb: setting up run ixqqkrvl
|
| 182 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 183 |
+
wandb: Run data is saved locally in outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_201005-ixqqkrvl
|
| 184 |
+
wandb: Run `wandb offline` to turn off syncing.
|
| 185 |
+
wandb: Resuming run keep5-math-offpolicy-top128-6.335M
|
| 186 |
+
wandb: ⭐️ View project at https://wandb.ai/hbfreed/glean-heal
|
| 187 |
+
wandb: 🚀 View run at https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 188 |
+
|
| 189 |
+
resumed student weights from outputs/healed/keep5_math_offpolicy_top128/step0025 (fresh optimizer, step counter at 0)
|
| 190 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 52 steps/epoch | 52 total steps | student params 3.70B | teacher overlap=False
|
| 191 |
+
restored optimizer/scheduler state from step 25; rebuilt 0 paged buffers
|
| 192 |
+
{"step": 26, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07439380060321867, "tokens": 135786, "cumulative_loss_tokens": 3340384, "grad_norm": 0.400390625, "lr": 3e-05, "finish_rate": 0.785, "comp_len": 572.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 63.6, "frames": {"chat": 237}, "mem_gb": 15.86}
|
| 193 |
+
wandb: WARNING Tried to log to step 26 that is less than the current step 28. Steps must be monotonically increasing, so this data will be ignored. See https://wandb.me/define-metric to log data out of order.
|
| 194 |
+
wandb: updating run metadata
|
| 195 |
+
wandb: uploading summary
|
| 196 |
+
wandb:
|
| 197 |
+
wandb: Run summary:
|
| 198 |
+
wandb: comp_len 527.5
|
| 199 |
+
wandb: cumulative_loss_tokens 3465392
|
| 200 |
+
wandb: epoch 0
|
| 201 |
+
wandb: finish_rate 0.861
|
| 202 |
+
wandb: forward_topk_kl 0.0689
|
| 203 |
+
wandb: grad_norm 0.35352
|
| 204 |
+
wandb: gsm8k_quick 0.57812
|
| 205 |
+
wandb: gsm8k_quick_chat 0.5625
|
| 206 |
+
wandb: gsm8k_quick_raw 0.57812
|
| 207 |
+
wandb: lr 3e-05
|
| 208 |
+
wandb: +7 ...
|
| 209 |
+
wandb:
|
| 210 |
+
wandb: 🚀 View run keep5-math-offpolicy-top128-6.335M at: https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 211 |
+
wandb: ⭐️ View project at: https://wandb.ai/hbfreed/glean-heal
|
| 212 |
+
wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
|
| 213 |
+
wandb: Find logs at: outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_201005-ixqqkrvl/logs
|
| 214 |
+
Traceback (most recent call last):
|
| 215 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/scripts/11_distill_on_policy.py", line 916, in <module>
|
| 216 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/scripts/11_distill_on_policy.py", line 734, in main
|
| 217 |
+
opt.zero_grad(set_to_none=True)
|
| 218 |
+
|
| 219 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/src/glean/topk_targets.py", line 322, in distill_topk_microbatches
|
| 220 |
+
(loss * (n_tokens / total_tokens)).backward()
|
| 221 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/_tensor.py", line 631, in backward
|
| 222 |
+
torch.autograd.backward(
|
| 223 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/__init__.py", line 379, in backward
|
| 224 |
+
_engine_run_backward(
|
| 225 |
+
File "/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/torch/autograd/graph.py", line 882, in _engine_run_backward
|
| 226 |
+
return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
|
| 227 |
+
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 228 |
+
KeyboardInterrupt
|
| 229 |
+
/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/megablocks/grouped_gemm_util.py:10: UserWarning: Grouped GEMM not available.
|
| 230 |
+
warnings.warn('Grouped GEMM not available.')
|
| 231 |
+
wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from /home/henry/.netrc.
|
| 232 |
+
wandb: Currently logged in as: hbfreed to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
|
| 233 |
+
wandb: setting up run ixqqkrvl
|
| 234 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 235 |
+
wandb: Run data is saved locally in outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_201227-ixqqkrvl
|
| 236 |
+
wandb: Run `wandb offline` to turn off syncing.
|
| 237 |
+
wandb: Resuming run keep5-math-offpolicy-top128-6.335M
|
| 238 |
+
wandb: ⭐️ View project at https://wandb.ai/hbfreed/glean-heal
|
| 239 |
+
wandb: 🚀 View run at https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 240 |
+
|
| 241 |
+
resumed student weights from outputs/healed/keep5_math_offpolicy_top128/step0025 (fresh optimizer, step counter at 0)
|
| 242 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 52 steps/epoch | 52 total steps | student params 3.70B | teacher overlap=False
|
| 243 |
+
restored optimizer/scheduler state from step 25; rebuilt 0 paged buffers
|
| 244 |
+
{"step": 26, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07439380060321867, "tokens": 135786, "cumulative_loss_tokens": 3340384, "grad_norm": 0.400390625, "lr": 3e-05, "finish_rate": 0.785, "comp_len": 572.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 63.5, "frames": {"chat": 237}, "mem_gb": 15.86}
|
| 245 |
+
/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/megablocks/grouped_gemm_util.py:10: UserWarning: Grouped GEMM not available.
|
| 246 |
+
warnings.warn('Grouped GEMM not available.')
|
| 247 |
+
wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from /home/henry/.netrc.
|
| 248 |
+
wandb: Currently logged in as: hbfreed to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
|
| 249 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 250 |
+
wandb: Run data is saved locally in outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_210942-ixqqkrvl
|
| 251 |
+
wandb: Run `wandb offline` to turn off syncing.
|
| 252 |
+
wandb: Resuming run keep5-math-offpolicy-top128-6.335M
|
| 253 |
+
wandb: ⭐️ View project at https://wandb.ai/hbfreed/glean-heal
|
| 254 |
+
wandb: 🚀 View run at https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 255 |
+
|
| 256 |
+
resumed student weights from outputs/healed/keep5_math_offpolicy_top128/step0025 (fresh optimizer, step counter at 0)
|
| 257 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 52 steps/epoch | 52 total steps | student params 3.70B | teacher overlap=False
|
| 258 |
+
restored optimizer/scheduler state from step 25; rebuilt 252 paged buffers
|
| 259 |
+
{"step": 26, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07439380060321867, "tokens": 135786, "cumulative_loss_tokens": 3340384, "grad_norm": 0.400390625, "lr": 3e-05, "finish_rate": 0.785, "comp_len": 572.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 49.7, "frames": {"chat": 237}, "mem_gb": 15.86}
|
| 260 |
+
{"step": 27, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0688901165153168, "tokens": 125008, "cumulative_loss_tokens": 3465392, "grad_norm": 0.353515625, "lr": 3e-05, "finish_rate": 0.861, "comp_len": 527.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.4, "frames": {"chat": 237}, "mem_gb": 16.0}
|
| 261 |
+
{"step": 28, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07942616952093563, "tokens": 123465, "cumulative_loss_tokens": 3588857, "grad_norm": 0.3828125, "lr": 3e-05, "finish_rate": 0.861, "comp_len": 520.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.7, "frames": {"chat": 237}, "mem_gb": 16.05}
|
| 262 |
+
{"step": 29, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07290488002502521, "tokens": 125066, "cumulative_loss_tokens": 3713923, "grad_norm": 0.375, "lr": 3e-05, "finish_rate": 0.852, "comp_len": 527.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.9, "frames": {"chat": 237}, "mem_gb": 16.07}
|
| 263 |
+
{"step": 30, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06405109558663372, "tokens": 116845, "cumulative_loss_tokens": 3830768, "grad_norm": 0.36328125, "lr": 3e-05, "finish_rate": 0.873, "comp_len": 493.0, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 39.2, "frames": {"chat": 237}, "mem_gb": 16.02}
|
| 264 |
+
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
|
| 265 |
+
[eval step 30] sample: 'To solve the problem of finding the greatest common divisor (GCD) of 51 and 12767 using Python and SymPy, we can follow these steps:\n\n1. **Import SymPy**: SymPy provides a built-in function `gcd` to c'
|
| 266 |
+
{"step": 30, "gsm8k_n": 64, "gsm8k_quick_raw": 0.59375, "gsm8k_quick": 0.59375, "gsm8k_quick_chat": 0.546875, "t_eval_s": 99.6}
|
| 267 |
+
{"step": 31, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06380675256369958, "tokens": 118784, "cumulative_loss_tokens": 3949552, "grad_norm": 0.35546875, "lr": 3e-05, "finish_rate": 0.848, "comp_len": 501.2, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.7, "frames": {"chat": 237}, "mem_gb": 18.69}
|
| 268 |
+
{"step": 32, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07116466968754641, "tokens": 126692, "cumulative_loss_tokens": 4076244, "grad_norm": 0.365234375, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 534.6, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 42.7, "frames": {"chat": 237}, "mem_gb": 16.07}
|
| 269 |
+
{"step": 33, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07169101262025185, "tokens": 127534, "cumulative_loss_tokens": 4203778, "grad_norm": 0.361328125, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 538.1, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.8, "frames": {"chat": 237}, "mem_gb": 16.1}
|
| 270 |
+
{"step": 34, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.058325077411156355, "tokens": 117601, "cumulative_loss_tokens": 4321379, "grad_norm": 0.3359375, "lr": 3e-05, "finish_rate": 0.916, "comp_len": 496.2, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 39.4, "frames": {"chat": 237}, "mem_gb": 15.85}
|
| 271 |
+
{"step": 35, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09290853046750798, "tokens": 124664, "cumulative_loss_tokens": 4446043, "grad_norm": 0.5703125, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 526.0, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.7, "frames": {"chat": 237}, "mem_gb": 16.0}
|
| 272 |
+
{"step": 36, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0604027349406713, "tokens": 120567, "cumulative_loss_tokens": 4566610, "grad_norm": 0.3359375, "lr": 3e-05, "finish_rate": 0.873, "comp_len": 508.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.4, "frames": {"chat": 237}, "mem_gb": 15.91}
|
| 273 |
+
{"step": 37, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06577399537383462, "tokens": 134445, "cumulative_loss_tokens": 4701055, "grad_norm": 0.328125, "lr": 3e-05, "finish_rate": 0.759, "comp_len": 567.3, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.3, "frames": {"chat": 237}, "mem_gb": 16.05}
|
| 274 |
+
{"step": 38, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0683866965607533, "tokens": 131408, "cumulative_loss_tokens": 4832463, "grad_norm": 0.353515625, "lr": 3e-05, "finish_rate": 0.785, "comp_len": 554.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 45.6, "frames": {"chat": 237}, "mem_gb": 16.18}
|
| 275 |
+
{"step": 39, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05965062385041473, "tokens": 128642, "cumulative_loss_tokens": 4961105, "grad_norm": 0.328125, "lr": 3e-05, "finish_rate": 0.852, "comp_len": 542.8, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.0, "frames": {"chat": 237}, "mem_gb": 16.04}
|
| 276 |
+
{"step": 40, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05333902896525456, "tokens": 125546, "cumulative_loss_tokens": 5086651, "grad_norm": 0.33984375, "lr": 3e-05, "finish_rate": 0.852, "comp_len": 529.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.9, "frames": {"chat": 237}, "mem_gb": 15.95}
|
| 277 |
+
[eval step 40] sample: 'To solve the problem of finding the greatest common divisor (GCD) of 51 and 12767 using Python and SymPy, we can follow these steps:\n\n1. **Import SymPy**: SymPy provides a built-in function `gcd` to c'
|
| 278 |
+
{"step": 40, "gsm8k_n": 64, "gsm8k_quick_raw": 0.546875, "gsm8k_quick": 0.546875, "gsm8k_quick_chat": 0.546875, "t_eval_s": 91.8}
|
| 279 |
+
{"step": 41, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05690588536906052, "tokens": 139086, "cumulative_loss_tokens": 5225737, "grad_norm": 0.318359375, "lr": 3e-05, "finish_rate": 0.781, "comp_len": 586.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 43.6, "frames": {"chat": 237}, "mem_gb": 18.68}
|
| 280 |
+
{"step": 42, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.058374759728881946, "tokens": 118340, "cumulative_loss_tokens": 5344077, "grad_norm": 0.31640625, "lr": 3e-05, "finish_rate": 0.924, "comp_len": 499.3, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.0, "frames": {"chat": 237}, "mem_gb": 15.95}
|
| 281 |
+
{"step": 43, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07019935327672881, "tokens": 122214, "cumulative_loss_tokens": 5466291, "grad_norm": 0.35546875, "lr": 3e-05, "finish_rate": 0.823, "comp_len": 515.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.1, "frames": {"chat": 237}, "mem_gb": 16.02}
|
| 282 |
+
{"step": 44, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06907294226702002, "tokens": 127145, "cumulative_loss_tokens": 5593436, "grad_norm": 0.34765625, "lr": 3e-05, "finish_rate": 0.857, "comp_len": 536.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 44.0, "frames": {"chat": 237}, "mem_gb": 16.05}
|
| 283 |
+
{"step": 45, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05835399558657501, "tokens": 129772, "cumulative_loss_tokens": 5723208, "grad_norm": 0.31640625, "lr": 3e-05, "finish_rate": 0.81, "comp_len": 547.6, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 43.6, "frames": {"chat": 237}, "mem_gb": 15.92}
|
| 284 |
+
{"step": 46, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.059369281406764264, "tokens": 114125, "cumulative_loss_tokens": 5837333, "grad_norm": 0.3359375, "lr": 3e-05, "finish_rate": 0.928, "comp_len": 481.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 38.4, "frames": {"chat": 237}, "mem_gb": 15.94}
|
| 285 |
+
{"step": 47, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05725491126893169, "tokens": 116580, "cumulative_loss_tokens": 5953913, "grad_norm": 0.345703125, "lr": 3e-05, "finish_rate": 0.928, "comp_len": 491.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 40.3, "frames": {"chat": 237}, "mem_gb": 15.99}
|
| 286 |
+
{"step": 48, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05294738627785973, "tokens": 124833, "cumulative_loss_tokens": 6078746, "grad_norm": 0.314453125, "lr": 3e-05, "finish_rate": 0.869, "comp_len": 526.7, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.2, "frames": {"chat": 237}, "mem_gb": 16.04}
|
| 287 |
+
{"step": 49, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05482089092956944, "tokens": 127946, "cumulative_loss_tokens": 6206692, "grad_norm": 0.302734375, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 539.9, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 41.7, "frames": {"chat": 237}, "mem_gb": 15.92}
|
| 288 |
+
{"step": 50, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08619242395973124, "tokens": 128977, "cumulative_loss_tokens": 6335669, "grad_norm": 0.390625, "lr": 3e-05, "finish_rate": 0.746, "comp_len": 575.8, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 44.6, "frames": {"chat": 224}, "mem_gb": 16.05}
|
| 289 |
+
[eval step 50] sample: 'To solve the problem of finding the greatest common divisor (GCD) of 51 and 12767 using Python and SymPy, we can follow these steps:\n\n1. **Import the necessary library:**\n We will use the `sympy` li'
|
| 290 |
+
{"step": 50, "gsm8k_n": 64, "gsm8k_quick_raw": 0.515625, "gsm8k_quick": 0.515625, "gsm8k_quick_chat": 0.53125, "t_eval_s": 95.6}
|
| 291 |
+
checkpoint snapshot queued -> outputs/healed/keep5_math_offpolicy_top128/step0050
|
| 292 |
+
wandb: updating run metadata
|
| 293 |
+
wandb: uploading output.log; uploading wandb-summary.json; uploading config.yaml
|
| 294 |
+
wandb:
|
| 295 |
+
wandb: Run history:
|
| 296 |
+
wandb: comp_len ▇▄▄▄▂▂▅▅▂▄▃▇▆▅▄█▂▃▅▅▁▂▄▅▇
|
| 297 |
+
wandb: cumulative_loss_tokens ▁▁▂▂▂▂▃▃▃▄▄▄▄▅▅▅▆▆▆▇▇▇▇██
|
| 298 |
+
wandb: epoch ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 299 |
+
wandb: finish_rate ▃▅▅▅▆▅▄▄█▅▆▂▃▅▅▂█▄▅▃██▆▅▁
|
| 300 |
+
wandb: forward_topk_kl ▅▄▆▄▃▃▄▄▂█▂▃▄▂▁▂▂▄▄▂▂▂▁▁▇
|
| 301 |
+
wandb: grad_norm ▄▂▃▃▃▂▃▃▂█▂▂▂▂▂▁▁▂▂▁▂▂▁▁▃
|
| 302 |
+
wandb: gsm8k_quick █▄▁
|
| 303 |
+
wandb: gsm8k_quick_chat ██▁
|
| 304 |
+
wandb: gsm8k_quick_raw █▄▁
|
| 305 |
+
wandb: lr ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 306 |
+
wandb: +6 ...
|
| 307 |
+
wandb:
|
| 308 |
+
wandb: Run summary:
|
| 309 |
+
wandb: comp_len 575.8
|
| 310 |
+
wandb: cumulative_loss_tokens 6335669
|
| 311 |
+
wandb: epoch 0
|
| 312 |
+
wandb: finish_rate 0.746
|
| 313 |
+
wandb: forward_topk_kl 0.08619
|
| 314 |
+
wandb: grad_norm 0.39062
|
| 315 |
+
wandb: gsm8k_quick 0.51562
|
| 316 |
+
wandb: gsm8k_quick_chat 0.53125
|
| 317 |
+
wandb: gsm8k_quick_raw 0.51562
|
| 318 |
+
wandb: lr 3e-05
|
| 319 |
+
wandb: +7 ...
|
| 320 |
+
wandb:
|
| 321 |
+
wandb: 🚀 View run keep5-math-offpolicy-top128-6.335M at: https://wandb.ai/hbfreed/glean-heal/runs/ixqqkrvl
|
| 322 |
+
wandb: ⭐️ View project at: https://wandb.ai/hbfreed/glean-heal
|
| 323 |
+
wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
|
| 324 |
+
wandb: Find logs at: outputs/healed/keep5_math_offpolicy_top128/wandb/run-20260713_210942-ixqqkrvl/logs
|
healed/knee0924_queue.log
ADDED
|
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[12:06:52] keep50 artifact exists
|
| 2 |
+
[12:06:52] short-healing keep50
|
| 3 |
+
[12:42:54] keep50 done: {"pre_heal_ppl":25.590167999267578,"post_heal_ppl":18.254446029663086}
|
| 4 |
+
[12:42:54] keep40 artifact exists
|
| 5 |
+
[12:42:54] short-healing keep40
|
| 6 |
+
[13:17:33] keep40 done: {"pre_heal_ppl":34.65605163574219,"post_heal_ppl":21.057231903076172}
|
| 7 |
+
[13:17:33] materializing keep30 (CPU surgery)
|
| 8 |
+
[13:17:49] short-healing keep30
|
| 9 |
+
[13:50:35] keep30 done: {"pre_heal_ppl":69.09920501708984,"post_heal_ppl":25.705188751220703}
|
| 10 |
+
[13:50:35] materializing keep25 (CPU surgery)
|
| 11 |
+
[13:50:49] short-healing keep25
|
| 12 |
+
[14:22:49] keep25 done: {"pre_heal_ppl":105.4487533569336,"post_heal_ppl":28.708465576171875}
|
| 13 |
+
[14:22:49] materializing keep20 (CPU surgery)
|
| 14 |
+
[14:23:04] short-healing keep20
|
| 15 |
+
[14:54:27] keep20 done: {"pre_heal_ppl":164.80226135253906,"post_heal_ppl":33.18513870239258}
|
| 16 |
+
[14:54:27] knee heal queue complete
|
| 17 |
+
[
|
| 18 |
+
{
|
| 19 |
+
"student": "outputs/pruned/knee0924/keep20",
|
| 20 |
+
"pre_heal_ppl": 164.80226135253906,
|
| 21 |
+
"post_heal_ppl": 33.18513870239258
|
| 22 |
+
},
|
| 23 |
+
{
|
| 24 |
+
"student": "outputs/pruned/knee0924/keep25",
|
| 25 |
+
"pre_heal_ppl": 105.4487533569336,
|
| 26 |
+
"post_heal_ppl": 28.708465576171875
|
| 27 |
+
},
|
| 28 |
+
{
|
| 29 |
+
"student": "outputs/pruned/knee0924/keep30",
|
| 30 |
+
"pre_heal_ppl": 69.09920501708984,
|
| 31 |
+
"post_heal_ppl": 25.705188751220703
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"student": "outputs/pruned/knee0924/keep40",
|
| 35 |
+
"pre_heal_ppl": 34.65605163574219,
|
| 36 |
+
"post_heal_ppl": 21.057231903076172
|
| 37 |
+
},
|
| 38 |
+
{
|
| 39 |
+
"student": "outputs/pruned/knee0924/keep50",
|
| 40 |
+
"pre_heal_ppl": 25.590167999267578,
|
| 41 |
+
"post_heal_ppl": 18.254446029663086
|
| 42 |
+
}
|
| 43 |
+
]
|
healed/opd_warm.log
ADDED
|
@@ -0,0 +1,59 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 2 |
+
wandb: W&B syncing is set to `offline` in this directory. Run `wandb online` or set WANDB_MODE=online to enable cloud syncing.
|
| 3 |
+
wandb: Run data is saved locally in outputs/healed/opd_warm_keep50/wandb/offline-run-20260802_001724-yclwxiwa
|
| 4 |
+
wandb: View this run in the terminal with `wandb leet`
|
| 5 |
+
|
| 6 |
+
teacher converted to fused MoE path (allenai/OLMoE-1B-7B-0125-Instruct)
|
| 7 |
+
|
| 8 |
+
reference anchor loaded from outputs/healed/keep50_offpolicy_warmup_s1224/step0150 on cuda:0 (beta=0.05)
|
| 9 |
+
|
| 10 |
+
starting vllm rollout server on GPU 2 (port 8377) ...
|
| 11 |
+
vllm server healthy in 36s
|
| 12 |
+
mixture distillation: 58360 gold trajectories from outputs/teacher_trajectories/dolci_combined_top128, lambda=0.5 decay=0.0
|
| 13 |
+
|
| 14 |
+
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
|
| 15 |
+
168191 prompts | 2627 steps/epoch | 120 total steps | student params 3.70B | teacher overlap=True
|
| 16 |
+
{"step": 1, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.0715529867857179, "tokens": 330677, "cumulative_loss_tokens": 330677, "grad_norm": 18.0, "lr": 2.0000000000000003e-06, "finish_rate": 0.66, "comp_len": 1291.7, "dropped_truncated": 0, "gold_loss": 0.4816, "gold_lambda": 0.5, "rep_ratio": 7.359, "t_data_s": 0.0, "t_rollout_s": 117.2, "t_step_s": 230.0, "t_refresh_s": 0.3, "mem_gb": 10.4, "mem_gb_teacher": 20.7}
|
| 17 |
+
[eval step 1] sample: 'To "faye" "n" "m" "n" "m" "n" "m" "n" "m" "n" "m" "n" "m" "n" "m" "n" "m" "n" "m" "n" "m'
|
| 18 |
+
{"step": 1, "gsm8k_n": 256, "gsm8k_quick_chat": 0.46875, "t_eval_s": 40.3}
|
| 19 |
+
{"step": 2, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.0476409321224727, "tokens": 305425, "cumulative_loss_tokens": 636102, "grad_norm": 19.25, "lr": 3e-06, "finish_rate": 0.699, "comp_len": 1193.1, "dropped_truncated": 0, "gold_loss": 0.4636, "gold_lambda": 0.5, "rep_ratio": 6.842, "t_data_s": 0.0, "t_rollout_s": 113.7, "t_step_s": 214.3, "t_refresh_s": 0.3, "mem_gb": 10.55, "mem_gb_teacher": 20.67}
|
| 20 |
+
{"step": 3, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.2240935077801478, "tokens": 302635, "cumulative_loss_tokens": 938737, "grad_norm": 16.75, "lr": 4.000000000000001e-06, "finish_rate": 0.711, "comp_len": 1182.2, "dropped_truncated": 0, "gold_loss": 0.4989, "gold_lambda": 0.5, "rep_ratio": 8.206, "t_data_s": 0.0, "t_rollout_s": 109.6, "t_step_s": 211.3, "t_refresh_s": 0.3, "mem_gb": 10.46, "mem_gb_teacher": 20.63}
|
| 21 |
+
{"step": 4, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.1232984279951, "tokens": 314442, "cumulative_loss_tokens": 1253179, "grad_norm": 13.625, "lr": 5e-06, "finish_rate": 0.723, "comp_len": 1228.3, "dropped_truncated": 0, "gold_loss": 0.4989, "gold_lambda": 0.5, "rep_ratio": 4.007, "t_data_s": 0.0, "t_rollout_s": 112.2, "t_step_s": 215.0, "t_refresh_s": 0.3, "mem_gb": 10.24, "mem_gb_teacher": 20.57}
|
| 22 |
+
{"step": 5, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.196489499796483, "tokens": 314169, "cumulative_loss_tokens": 1567348, "grad_norm": 12.0625, "lr": 6e-06, "finish_rate": 0.715, "comp_len": 1227.2, "dropped_truncated": 0, "gold_loss": 1.7581, "gold_lambda": 0.5, "rep_ratio": 7.457, "t_data_s": 0.0, "t_rollout_s": 113.5, "t_step_s": 213.6, "t_refresh_s": 0.3, "mem_gb": 10.48, "mem_gb_teacher": 20.64}
|
| 23 |
+
{"step": 6, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.174327937240284, "tokens": 302861, "cumulative_loss_tokens": 1870209, "grad_norm": 10.125, "lr": 7e-06, "finish_rate": 0.715, "comp_len": 1183.1, "dropped_truncated": 0, "gold_loss": 1.4087, "gold_lambda": 0.5, "rep_ratio": 6.804, "t_data_s": 0.0, "t_rollout_s": 112.3, "t_step_s": 214.1, "t_refresh_s": 0.3, "mem_gb": 10.49, "mem_gb_teacher": 20.64}
|
| 24 |
+
{"step": 7, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.142888064626811, "tokens": 259225, "cumulative_loss_tokens": 2129434, "grad_norm": 8.0625, "lr": 8.000000000000001e-06, "finish_rate": 0.875, "comp_len": 1012.6, "dropped_truncated": 0, "gold_loss": 1.7253, "gold_lambda": 0.5, "rep_ratio": 2.291, "t_data_s": 0.0, "t_rollout_s": 85.8, "t_step_s": 180.9, "t_refresh_s": 0.3, "mem_gb": 10.5, "mem_gb_teacher": 20.66}
|
| 25 |
+
{"step": 8, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.2367885471050992, "tokens": 275165, "cumulative_loss_tokens": 2404599, "grad_norm": 10.0625, "lr": 9e-06, "finish_rate": 0.777, "comp_len": 1074.9, "dropped_truncated": 0, "gold_loss": 1.791, "gold_lambda": 0.5, "rep_ratio": 4.278, "t_data_s": 0.0, "t_rollout_s": 101.9, "t_step_s": 198.9, "t_refresh_s": 0.3, "mem_gb": 10.37, "mem_gb_teacher": 20.6}
|
| 26 |
+
{"step": 9, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.2960635659850794, "tokens": 287956, "cumulative_loss_tokens": 2692555, "grad_norm": 10.5, "lr": 1e-05, "finish_rate": 0.777, "comp_len": 1124.8, "dropped_truncated": 0, "gold_loss": 0.4427, "gold_lambda": 0.5, "rep_ratio": 3.539, "t_data_s": 0.0, "t_rollout_s": 107.3, "t_step_s": 217.4, "t_refresh_s": 0.3, "mem_gb": 10.37, "mem_gb_teacher": 20.61}
|
| 27 |
+
{"step": 10, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.1268998827677594, "tokens": 256196, "cumulative_loss_tokens": 2948751, "grad_norm": 8.1875, "lr": 1e-05, "finish_rate": 0.852, "comp_len": 1000.8, "dropped_truncated": 0, "gold_loss": 0.4179, "gold_lambda": 0.5, "rep_ratio": 5.761, "t_data_s": 0.0, "t_rollout_s": 83.3, "t_step_s": 177.5, "t_refresh_s": 0.3, "mem_gb": 10.63, "mem_gb_teacher": 20.7}
|
| 28 |
+
[eval step 10] sample: 'To be a-m-on-n-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-on-'
|
| 29 |
+
{"step": 11, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.1852989046363867, "tokens": 249794, "cumulative_loss_tokens": 3198545, "grad_norm": 9.4375, "lr": 1e-05, "finish_rate": 0.879, "comp_len": 975.8, "dropped_truncated": 0, "gold_loss": 1.8732, "gold_lambda": 0.5, "rep_ratio": 2.592, "t_data_s": 0.0, "t_rollout_s": 79.1, "t_step_s": 170.9, "t_refresh_s": 0.3, "mem_gb": 10.17, "mem_gb_teacher": 20.53}
|
| 30 |
+
{"step": 12, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.0672082473087046, "tokens": 235329, "cumulative_loss_tokens": 3433874, "grad_norm": 6.40625, "lr": 1e-05, "finish_rate": 0.918, "comp_len": 919.3, "dropped_truncated": 0, "gold_loss": 1.7626, "gold_lambda": 0.5, "rep_ratio": 2.465, "t_data_s": 0.0, "t_rollout_s": 72.1, "t_step_s": 161.9, "t_refresh_s": 0.3, "mem_gb": 10.51, "mem_gb_teacher": 20.65}
|
| 31 |
+
{"step": 13, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.1896850641550707, "tokens": 196953, "cumulative_loss_tokens": 3630827, "grad_norm": 6.78125, "lr": 1e-05, "finish_rate": 0.945, "comp_len": 769.3, "dropped_truncated": 0, "gold_loss": 1.8544, "gold_lambda": 0.5, "rep_ratio": 2.39, "t_data_s": 0.0, "t_rollout_s": 57.2, "t_step_s": 138.9, "t_refresh_s": 0.3, "mem_gb": 10.31, "mem_gb_teacher": 20.59}
|
| 32 |
+
{"step": 14, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.110568549902207, "tokens": 195354, "cumulative_loss_tokens": 3826181, "grad_norm": 5.25, "lr": 1e-05, "finish_rate": 0.938, "comp_len": 763.1, "dropped_truncated": 0, "gold_loss": 1.7907, "gold_lambda": 0.5, "rep_ratio": 2.662, "t_data_s": 0.0, "t_rollout_s": 57.3, "t_step_s": 140.7, "t_refresh_s": 0.3, "mem_gb": 10.2, "mem_gb_teacher": 20.55}
|
| 33 |
+
{"step": 15, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.0880019511972423, "tokens": 211631, "cumulative_loss_tokens": 4037812, "grad_norm": 4.78125, "lr": 1e-05, "finish_rate": 0.938, "comp_len": 826.7, "dropped_truncated": 0, "gold_loss": 0.4573, "gold_lambda": 0.5, "rep_ratio": 4.91, "t_data_s": 0.0, "t_rollout_s": 61.5, "t_step_s": 147.1, "t_refresh_s": 0.3, "mem_gb": 10.26, "mem_gb_teacher": 20.53}
|
| 34 |
+
{"step": 16, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9728942313239658, "tokens": 194169, "cumulative_loss_tokens": 4231981, "grad_norm": 7.90625, "lr": 1e-05, "finish_rate": 0.953, "comp_len": 758.5, "dropped_truncated": 0, "gold_loss": 0.4647, "gold_lambda": 0.5, "rep_ratio": 12.498, "t_data_s": 0.0, "t_rollout_s": 57.5, "t_step_s": 140.4, "t_refresh_s": 0.3, "mem_gb": 10.38, "mem_gb_teacher": 20.56}
|
| 35 |
+
{"step": 17, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.0340790669212048, "tokens": 182968, "cumulative_loss_tokens": 4414949, "grad_norm": 8.5625, "lr": 1e-05, "finish_rate": 0.945, "comp_len": 714.7, "dropped_truncated": 0, "gold_loss": 1.5083, "gold_lambda": 0.5, "rep_ratio": 2.658, "t_data_s": 0.0, "t_rollout_s": 55.6, "t_step_s": 137.3, "t_refresh_s": 0.3, "mem_gb": 10.54, "mem_gb_teacher": 20.66}
|
| 36 |
+
{"step": 18, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9951681053661686, "tokens": 192973, "cumulative_loss_tokens": 4607922, "grad_norm": 4.09375, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 753.8, "dropped_truncated": 0, "gold_loss": 1.5254, "gold_lambda": 0.5, "rep_ratio": 2.551, "t_data_s": 0.0, "t_rollout_s": 58.0, "t_step_s": 139.2, "t_refresh_s": 0.3, "mem_gb": 10.28, "mem_gb_teacher": 20.58}
|
| 37 |
+
{"step": 19, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.941273376354514, "tokens": 172849, "cumulative_loss_tokens": 4780771, "grad_norm": 3.65625, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 675.2, "dropped_truncated": 0, "gold_loss": 1.7476, "gold_lambda": 0.5, "rep_ratio": 2.772, "t_data_s": 0.0, "t_rollout_s": 52.5, "t_step_s": 129.2, "t_refresh_s": 0.3, "mem_gb": 10.44, "mem_gb_teacher": 20.63}
|
| 38 |
+
{"step": 20, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8855722967075427, "tokens": 178588, "cumulative_loss_tokens": 4959359, "grad_norm": 3.34375, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 697.6, "dropped_truncated": 0, "gold_loss": 1.8831, "gold_lambda": 0.5, "rep_ratio": 2.626, "t_data_s": 0.0, "t_rollout_s": 53.1, "t_step_s": 129.8, "t_refresh_s": 0.3, "mem_gb": 10.64, "mem_gb_teacher": 20.63}
|
| 39 |
+
[eval step 20] sample: 'To be a a "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the "m" of the'
|
| 40 |
+
{"step": 20, "gsm8k_n": 256, "gsm8k_quick_chat": 0.49609375, "t_eval_s": 43.9}
|
| 41 |
+
{"step": 21, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 1.0167943671227804, "tokens": 170868, "cumulative_loss_tokens": 5130227, "grad_norm": 4.125, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 667.5, "dropped_truncated": 0, "gold_loss": 0.4302, "gold_lambda": 0.5, "rep_ratio": 2.259, "t_data_s": 0.0, "t_rollout_s": 50.9, "t_step_s": 126.6, "t_refresh_s": 0.3, "mem_gb": 10.41, "mem_gb_teacher": 20.55}
|
| 42 |
+
{"step": 22, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9240483859857905, "tokens": 186012, "cumulative_loss_tokens": 5316239, "grad_norm": 3.453125, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 726.6, "dropped_truncated": 0, "gold_loss": 0.4496, "gold_lambda": 0.5, "rep_ratio": 2.576, "t_data_s": 0.0, "t_rollout_s": 54.9, "t_step_s": 133.4, "t_refresh_s": 0.3, "mem_gb": 10.37, "mem_gb_teacher": 20.58}
|
| 43 |
+
{"step": 23, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9889739579658967, "tokens": 161101, "cumulative_loss_tokens": 5477340, "grad_norm": 3.6875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 629.3, "dropped_truncated": 0, "gold_loss": 1.1295, "gold_lambda": 0.5, "rep_ratio": 2.562, "t_data_s": 0.0, "t_rollout_s": 49.2, "t_step_s": 126.1, "t_refresh_s": 0.3, "mem_gb": 10.19, "mem_gb_teacher": 20.54}
|
| 44 |
+
{"step": 24, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9001673450655785, "tokens": 172167, "cumulative_loss_tokens": 5649507, "grad_norm": 2.84375, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 672.5, "dropped_truncated": 0, "gold_loss": 1.184, "gold_lambda": 0.5, "rep_ratio": 2.392, "t_data_s": 0.0, "t_rollout_s": 51.2, "t_step_s": 125.6, "t_refresh_s": 0.3, "mem_gb": 10.42, "mem_gb_teacher": 20.61}
|
| 45 |
+
{"step": 25, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8294563550778241, "tokens": 193603, "cumulative_loss_tokens": 5843110, "grad_norm": 3.203125, "lr": 1e-05, "finish_rate": 0.949, "comp_len": 756.3, "dropped_truncated": 0, "gold_loss": 2.1916, "gold_lambda": 0.5, "rep_ratio": 2.737, "t_data_s": 0.0, "t_rollout_s": 57.4, "t_step_s": 137.7, "t_refresh_s": 0.3, "mem_gb": 10.55, "mem_gb_teacher": 20.67}
|
| 46 |
+
{"step": 26, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8520757204397251, "tokens": 184343, "cumulative_loss_tokens": 6027453, "grad_norm": 2.6875, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 720.1, "dropped_truncated": 0, "gold_loss": 1.8995, "gold_lambda": 0.5, "rep_ratio": 2.86, "t_data_s": 0.0, "t_rollout_s": 54.2, "t_step_s": 131.3, "t_refresh_s": 0.3, "mem_gb": 10.35, "mem_gb_teacher": 20.59}
|
| 47 |
+
{"step": 27, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9107435231664042, "tokens": 190215, "cumulative_loss_tokens": 6217668, "grad_norm": 2.625, "lr": 1e-05, "finish_rate": 0.953, "comp_len": 743.0, "dropped_truncated": 0, "gold_loss": 1.4011, "gold_lambda": 0.5, "rep_ratio": 2.559, "t_data_s": 0.0, "t_rollout_s": 55.9, "t_step_s": 134.6, "t_refresh_s": 0.3, "mem_gb": 10.41, "mem_gb_teacher": 20.62}
|
| 48 |
+
{"step": 28, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9077256934040764, "tokens": 178659, "cumulative_loss_tokens": 6396327, "grad_norm": 2.1875, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 697.9, "dropped_truncated": 0, "gold_loss": 1.4574, "gold_lambda": 0.5, "rep_ratio": 2.687, "t_data_s": 0.0, "t_rollout_s": 51.5, "t_step_s": 126.5, "t_refresh_s": 0.3, "mem_gb": 10.37, "mem_gb_teacher": 20.54}
|
| 49 |
+
{"step": 29, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9122361920726376, "tokens": 179195, "cumulative_loss_tokens": 6575522, "grad_norm": 1.7109375, "lr": 1e-05, "finish_rate": 0.949, "comp_len": 700.0, "dropped_truncated": 0, "gold_loss": 0.4425, "gold_lambda": 0.5, "rep_ratio": 2.463, "t_data_s": 0.0, "t_rollout_s": 54.0, "t_step_s": 131.5, "t_refresh_s": 0.3, "mem_gb": 10.38, "mem_gb_teacher": 20.6}
|
| 50 |
+
{"step": 30, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8639218128417365, "tokens": 196883, "cumulative_loss_tokens": 6772405, "grad_norm": 1.625, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 769.1, "dropped_truncated": 0, "gold_loss": 0.4074, "gold_lambda": 0.5, "rep_ratio": 2.545, "t_data_s": 0.0, "t_rollout_s": 57.7, "t_step_s": 138.1, "t_refresh_s": 0.3, "mem_gb": 10.48, "mem_gb_teacher": 20.64}
|
| 51 |
+
[eval step 30] sample: 'To solve the problem of determining the number of days in a month that has a positive count, we need to analyze the data provided and identify the pattern.\n\n**Step 1: Analyze the Data**\n\nThe data prov'
|
| 52 |
+
{"step": 31, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8510895792700558, "tokens": 203228, "cumulative_loss_tokens": 6975633, "grad_norm": 2.484375, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 793.9, "dropped_truncated": 0, "gold_loss": 1.7625, "gold_lambda": 0.5, "rep_ratio": 2.537, "t_data_s": 0.0, "t_rollout_s": 59.8, "t_step_s": 139.0, "t_refresh_s": 0.3, "mem_gb": 10.1, "mem_gb_teacher": 20.51}
|
| 53 |
+
{"step": 32, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.799281217758318, "tokens": 186923, "cumulative_loss_tokens": 7162556, "grad_norm": 2.125, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 730.2, "dropped_truncated": 0, "gold_loss": 1.4991, "gold_lambda": 0.5, "rep_ratio": 2.655, "t_data_s": 0.0, "t_rollout_s": 55.1, "t_step_s": 134.5, "t_refresh_s": 0.3, "mem_gb": 10.43, "mem_gb_teacher": 20.6}
|
| 54 |
+
{"step": 33, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.9108344851361305, "tokens": 206685, "cumulative_loss_tokens": 7369241, "grad_norm": 2.609375, "lr": 1e-05, "finish_rate": 0.941, "comp_len": 807.4, "dropped_truncated": 0, "gold_loss": 1.8247, "gold_lambda": 0.5, "rep_ratio": 2.723, "t_data_s": 0.0, "t_rollout_s": 61.8, "t_step_s": 145.9, "t_refresh_s": 0.3, "mem_gb": 10.34, "mem_gb_teacher": 20.6}
|
| 55 |
+
{"step": 34, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8392004683972054, "tokens": 200636, "cumulative_loss_tokens": 7569877, "grad_norm": 5.21875, "lr": 1e-05, "finish_rate": 0.953, "comp_len": 783.7, "dropped_truncated": 0, "gold_loss": 2.3876, "gold_lambda": 0.5, "rep_ratio": 2.624, "t_data_s": 0.0, "t_rollout_s": 59.5, "t_step_s": 140.6, "t_refresh_s": 0.3, "mem_gb": 10.38, "mem_gb_teacher": 20.56}
|
| 56 |
+
{"step": 35, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8846296758133513, "tokens": 180440, "cumulative_loss_tokens": 7750317, "grad_norm": 2.015625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 704.8, "dropped_truncated": 0, "gold_loss": 0.3641, "gold_lambda": 0.5, "rep_ratio": 2.604, "t_data_s": 0.0, "t_rollout_s": 51.9, "t_step_s": 127.8, "t_refresh_s": 0.3, "mem_gb": 10.24, "mem_gb_teacher": 20.53}
|
| 57 |
+
{"step": 36, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.8721849152298049, "tokens": 194494, "cumulative_loss_tokens": 7944811, "grad_norm": 1.859375, "lr": 1e-05, "finish_rate": 0.957, "comp_len": 759.7, "dropped_truncated": 0, "gold_loss": 0.4256, "gold_lambda": 0.5, "rep_ratio": 2.591, "t_data_s": 0.0, "t_rollout_s": 56.4, "t_step_s": 136.2, "t_refresh_s": 0.3, "mem_gb": 10.27, "mem_gb_teacher": 20.57}
|
| 58 |
+
{"step": 37, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.849565157371755, "tokens": 186626, "cumulative_loss_tokens": 8131437, "grad_norm": 2.390625, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 729.0, "dropped_truncated": 0, "gold_loss": 1.6035, "gold_lambda": 0.5, "rep_ratio": 2.528, "t_data_s": 0.0, "t_rollout_s": 54.0, "t_step_s": 132.0, "t_refresh_s": 0.3, "mem_gb": 10.26, "mem_gb_teacher": 20.53}
|
| 59 |
+
{"step": 38, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.7732366005655155, "tokens": 210982, "cumulative_loss_tokens": 8342419, "grad_norm": 4.96875, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 824.1, "dropped_truncated": 0, "gold_loss": 1.5962, "gold_lambda": 0.5, "rep_ratio": 2.4, "t_data_s": 0.0, "t_rollout_s": 63.0, "t_step_s": 146.4, "t_refresh_s": 0.3, "mem_gb": 10.31, "mem_gb_teacher": 20.56}
|
healed/opd_warm_fixed.log
ADDED
|
@@ -0,0 +1,186 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 2 |
+
wandb: W&B syncing is set to `offline` in this directory. Run `wandb online` or set WANDB_MODE=online to enable cloud syncing.
|
| 3 |
+
wandb: Run data is saved locally in outputs/healed/opd_warm_fixed_keep50/wandb/offline-run-20260802_065345-ubll0rd3
|
| 4 |
+
wandb: View this run in the terminal with `wandb leet`
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
reference anchor loaded from outputs/healed/keep50_warmup_fixed_s1224/step0150 on cuda:0 (beta=0.05)
|
| 8 |
+
|
| 9 |
+
starting vllm rollout server on GPU 2 (port 8377) ...
|
| 10 |
+
vllm server healthy in 36s
|
| 11 |
+
mixture distillation: 58360 gold trajectories from outputs/teacher_trajectories/dolci_combined_top128, lambda=0.5 decay=0.0
|
| 12 |
+
|
| 13 |
+
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
|
| 14 |
+
168191 prompts | 2627 steps/epoch | 120 total steps | student params 3.70B | teacher overlap=True
|
| 15 |
+
{"step": 1, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.44963827088755237, "tokens": 194827, "cumulative_loss_tokens": 194827, "grad_norm": 2.0625, "lr": 2.0000000000000003e-06, "finish_rate": 0.957, "comp_len": 761.0, "dropped_truncated": 0, "gold_loss": 0.2115, "gold_lambda": 0.5, "rep_ratio": 2.401, "t_data_s": 0.0, "t_rollout_s": 56.4, "t_step_s": 182.8, "t_refresh_s": 0.3, "mem_gb": 17.24, "mem_gb_teacher": 20.26}
|
| 16 |
+
[eval step 1] sample: 'Misy fitsapana manokana ve mba hanombanana ny fahaiza-mamorona?'
|
| 17 |
+
{"step": 1, "gsm8k_n": 256, "gsm8k_quick_chat": 0.65234375, "t_eval_s": 23.8}
|
| 18 |
+
{"step": 2, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3940014742786295, "tokens": 187987, "cumulative_loss_tokens": 382814, "grad_norm": 2.0, "lr": 3e-06, "finish_rate": 0.992, "comp_len": 734.3, "dropped_truncated": 0, "gold_loss": 0.2068, "gold_lambda": 0.5, "rep_ratio": 2.369, "t_data_s": 0.0, "t_rollout_s": 56.2, "t_step_s": 157.9, "t_refresh_s": 0.3, "mem_gb": 17.22, "mem_gb_teacher": 20.24}
|
| 19 |
+
{"step": 3, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3842378264528005, "tokens": 175719, "cumulative_loss_tokens": 558533, "grad_norm": 1.9296875, "lr": 4.000000000000001e-06, "finish_rate": 0.969, "comp_len": 686.4, "dropped_truncated": 0, "gold_loss": 0.2386, "gold_lambda": 0.5, "rep_ratio": 2.451, "t_data_s": 0.0, "t_rollout_s": 52.3, "t_step_s": 150.2, "t_refresh_s": 0.3, "mem_gb": 17.33, "mem_gb_teacher": 20.27}
|
| 20 |
+
{"step": 4, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3169176116394187, "tokens": 183284, "cumulative_loss_tokens": 741817, "grad_norm": 1.703125, "lr": 5e-06, "finish_rate": 0.973, "comp_len": 716.0, "dropped_truncated": 0, "gold_loss": 0.2391, "gold_lambda": 0.5, "rep_ratio": 2.682, "t_data_s": 0.0, "t_rollout_s": 53.4, "t_step_s": 156.8, "t_refresh_s": 0.3, "mem_gb": 17.1, "mem_gb_teacher": 20.22}
|
| 21 |
+
{"step": 5, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.31469852179097824, "tokens": 169650, "cumulative_loss_tokens": 911467, "grad_norm": 2.625, "lr": 6e-06, "finish_rate": 0.988, "comp_len": 662.7, "dropped_truncated": 0, "gold_loss": 1.3211, "gold_lambda": 0.5, "rep_ratio": 2.526, "t_data_s": 0.0, "t_rollout_s": 50.1, "t_step_s": 144.7, "t_refresh_s": 0.3, "mem_gb": 17.17, "mem_gb_teacher": 20.24}
|
| 22 |
+
{"step": 6, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3012831195711605, "tokens": 182143, "cumulative_loss_tokens": 1093610, "grad_norm": 2.203125, "lr": 7e-06, "finish_rate": 0.949, "comp_len": 711.5, "dropped_truncated": 0, "gold_loss": 0.9775, "gold_lambda": 0.5, "rep_ratio": 2.403, "t_data_s": 0.0, "t_rollout_s": 56.4, "t_step_s": 154.9, "t_refresh_s": 0.3, "mem_gb": 17.26, "mem_gb_teacher": 20.26}
|
| 23 |
+
{"step": 7, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2884359588736265, "tokens": 182618, "cumulative_loss_tokens": 1276228, "grad_norm": 2.640625, "lr": 8.000000000000001e-06, "finish_rate": 0.977, "comp_len": 713.4, "dropped_truncated": 0, "gold_loss": 1.3168, "gold_lambda": 0.5, "rep_ratio": 2.266, "t_data_s": 0.0, "t_rollout_s": 53.8, "t_step_s": 154.1, "t_refresh_s": 0.3, "mem_gb": 17.47, "mem_gb_teacher": 20.28}
|
| 24 |
+
{"step": 8, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.25864222868998754, "tokens": 182352, "cumulative_loss_tokens": 1458580, "grad_norm": 2.9375, "lr": 9e-06, "finish_rate": 0.969, "comp_len": 712.3, "dropped_truncated": 0, "gold_loss": 1.3305, "gold_lambda": 0.5, "rep_ratio": 2.607, "t_data_s": 0.0, "t_rollout_s": 53.3, "t_step_s": 153.4, "t_refresh_s": 0.3, "mem_gb": 17.53, "mem_gb_teacher": 20.29}
|
| 25 |
+
{"step": 9, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4240309239163299, "tokens": 161654, "cumulative_loss_tokens": 1620234, "grad_norm": 1.8046875, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 631.5, "dropped_truncated": 0, "gold_loss": 0.2139, "gold_lambda": 0.5, "rep_ratio": 2.185, "t_data_s": 0.0, "t_rollout_s": 49.1, "t_step_s": 143.8, "t_refresh_s": 0.3, "mem_gb": 17.52, "mem_gb_teacher": 20.28}
|
| 26 |
+
{"step": 10, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3422506856649129, "tokens": 182466, "cumulative_loss_tokens": 1802700, "grad_norm": 1.4453125, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 712.8, "dropped_truncated": 0, "gold_loss": 0.2024, "gold_lambda": 0.5, "rep_ratio": 2.523, "t_data_s": 0.0, "t_rollout_s": 53.5, "t_step_s": 153.2, "t_refresh_s": 0.3, "mem_gb": 17.34, "mem_gb_teacher": 20.25}
|
| 27 |
+
[eval step 10] sample: 'Misy fitsapana manokana ve mba hanombanana ny fahaiza-mamorona?'
|
| 28 |
+
{"step": 11, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3194563395594054, "tokens": 162668, "cumulative_loss_tokens": 1965368, "grad_norm": 2.875, "lr": 1e-05, "finish_rate": 0.996, "comp_len": 635.4, "dropped_truncated": 0, "gold_loss": 1.4128, "gold_lambda": 0.5, "rep_ratio": 2.353, "t_data_s": 0.0, "t_rollout_s": 49.0, "t_step_s": 144.6, "t_refresh_s": 0.3, "mem_gb": 17.31, "mem_gb_teacher": 20.25}
|
| 29 |
+
{"step": 12, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.30020437081658174, "tokens": 172670, "cumulative_loss_tokens": 2138038, "grad_norm": 2.5, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 674.5, "dropped_truncated": 0, "gold_loss": 1.3403, "gold_lambda": 0.5, "rep_ratio": 2.41, "t_data_s": 0.0, "t_rollout_s": 52.5, "t_step_s": 152.4, "t_refresh_s": 0.3, "mem_gb": 17.45, "mem_gb_teacher": 20.3}
|
| 30 |
+
{"step": 13, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4090317845232767, "tokens": 160408, "cumulative_loss_tokens": 2298446, "grad_norm": 3.203125, "lr": 1e-05, "finish_rate": 0.992, "comp_len": 626.6, "dropped_truncated": 0, "gold_loss": 1.4213, "gold_lambda": 0.5, "rep_ratio": 2.23, "t_data_s": 0.0, "t_rollout_s": 47.7, "t_step_s": 141.4, "t_refresh_s": 0.3, "mem_gb": 17.07, "mem_gb_teacher": 20.25}
|
| 31 |
+
{"step": 14, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.34899632673731384, "tokens": 159410, "cumulative_loss_tokens": 2457856, "grad_norm": 2.6875, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 622.7, "dropped_truncated": 0, "gold_loss": 1.3901, "gold_lambda": 0.5, "rep_ratio": 2.422, "t_data_s": 0.0, "t_rollout_s": 47.6, "t_step_s": 141.7, "t_refresh_s": 0.3, "mem_gb": 17.12, "mem_gb_teacher": 20.25}
|
| 32 |
+
{"step": 15, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.34543543075337274, "tokens": 166862, "cumulative_loss_tokens": 2624718, "grad_norm": 1.15625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 651.8, "dropped_truncated": 0, "gold_loss": 0.2286, "gold_lambda": 0.5, "rep_ratio": 2.459, "t_data_s": 0.0, "t_rollout_s": 48.7, "t_step_s": 145.8, "t_refresh_s": 0.3, "mem_gb": 17.25, "mem_gb_teacher": 20.24}
|
| 33 |
+
{"step": 16, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3638701808236742, "tokens": 154124, "cumulative_loss_tokens": 2778842, "grad_norm": 1.2109375, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 602.0, "dropped_truncated": 0, "gold_loss": 0.2253, "gold_lambda": 0.5, "rep_ratio": 2.369, "t_data_s": 0.0, "t_rollout_s": 47.2, "t_step_s": 141.5, "t_refresh_s": 0.3, "mem_gb": 17.09, "mem_gb_teacher": 20.23}
|
| 34 |
+
{"step": 17, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3916856637959853, "tokens": 153093, "cumulative_loss_tokens": 2931935, "grad_norm": 2.0625, "lr": 1e-05, "finish_rate": 0.992, "comp_len": 598.0, "dropped_truncated": 0, "gold_loss": 1.0651, "gold_lambda": 0.5, "rep_ratio": 2.331, "t_data_s": 0.0, "t_rollout_s": 47.5, "t_step_s": 149.3, "t_refresh_s": 0.3, "mem_gb": 17.26, "mem_gb_teacher": 20.27}
|
| 35 |
+
{"step": 18, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3789892320845085, "tokens": 167800, "cumulative_loss_tokens": 3099735, "grad_norm": 1.96875, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 655.5, "dropped_truncated": 0, "gold_loss": 1.0761, "gold_lambda": 0.5, "rep_ratio": 2.334, "t_data_s": 0.0, "t_rollout_s": 52.0, "t_step_s": 153.1, "t_refresh_s": 0.3, "mem_gb": 17.18, "mem_gb_teacher": 20.24}
|
| 36 |
+
{"step": 19, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.35074403341776794, "tokens": 167173, "cumulative_loss_tokens": 3266908, "grad_norm": 2.390625, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 653.0, "dropped_truncated": 0, "gold_loss": 1.3153, "gold_lambda": 0.5, "rep_ratio": 2.337, "t_data_s": 0.0, "t_rollout_s": 50.2, "t_step_s": 143.5, "t_refresh_s": 0.3, "mem_gb": 17.32, "mem_gb_teacher": 20.25}
|
| 37 |
+
{"step": 20, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2626116644125829, "tokens": 190018, "cumulative_loss_tokens": 3456926, "grad_norm": 2.375, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 742.3, "dropped_truncated": 0, "gold_loss": 1.4092, "gold_lambda": 0.5, "rep_ratio": 2.615, "t_data_s": 0.0, "t_rollout_s": 55.8, "t_step_s": 158.7, "t_refresh_s": 0.3, "mem_gb": 17.61, "mem_gb_teacher": 20.29}
|
| 38 |
+
[eval step 20] sample: 'Misy fitapana manokana ny fahaiza-mamorona.'
|
| 39 |
+
{"step": 20, "gsm8k_n": 256, "gsm8k_quick_chat": 0.6171875, "t_eval_s": 21.4}
|
| 40 |
+
{"step": 21, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.36320468789413923, "tokens": 161040, "cumulative_loss_tokens": 3617966, "grad_norm": 1.4921875, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 629.1, "dropped_truncated": 0, "gold_loss": 0.2034, "gold_lambda": 0.5, "rep_ratio": 2.491, "t_data_s": 0.0, "t_rollout_s": 47.5, "t_step_s": 141.8, "t_refresh_s": 0.3, "mem_gb": 17.31, "mem_gb_teacher": 20.25}
|
| 41 |
+
{"step": 22, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3560513313296494, "tokens": 186196, "cumulative_loss_tokens": 3804162, "grad_norm": 1.140625, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 727.3, "dropped_truncated": 0, "gold_loss": 0.2012, "gold_lambda": 0.5, "rep_ratio": 2.621, "t_data_s": 0.0, "t_rollout_s": 56.3, "t_step_s": 157.9, "t_refresh_s": 0.3, "mem_gb": 17.48, "mem_gb_teacher": 20.28}
|
| 42 |
+
{"step": 23, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4002737975893586, "tokens": 172291, "cumulative_loss_tokens": 3976453, "grad_norm": 1.5546875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 673.0, "dropped_truncated": 0, "gold_loss": 0.7825, "gold_lambda": 0.5, "rep_ratio": 2.324, "t_data_s": 0.0, "t_rollout_s": 50.2, "t_step_s": 146.6, "t_refresh_s": 0.3, "mem_gb": 17.11, "mem_gb_teacher": 20.25}
|
| 43 |
+
{"step": 24, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3151660050172998, "tokens": 164852, "cumulative_loss_tokens": 4141305, "grad_norm": 1.6875, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 644.0, "dropped_truncated": 0, "gold_loss": 0.801, "gold_lambda": 0.5, "rep_ratio": 2.331, "t_data_s": 0.0, "t_rollout_s": 49.6, "t_step_s": 143.3, "t_refresh_s": 0.3, "mem_gb": 17.59, "mem_gb_teacher": 20.31}
|
| 44 |
+
{"step": 25, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.313829974284698, "tokens": 196304, "cumulative_loss_tokens": 4337609, "grad_norm": 2.234375, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 766.8, "dropped_truncated": 0, "gold_loss": 1.6377, "gold_lambda": 0.5, "rep_ratio": 2.688, "t_data_s": 0.0, "t_rollout_s": 57.5, "t_step_s": 156.7, "t_refresh_s": 0.3, "mem_gb": 17.76, "mem_gb_teacher": 20.32}
|
| 45 |
+
{"step": 26, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.27340404820149083, "tokens": 174461, "cumulative_loss_tokens": 4512070, "grad_norm": 1.9375, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 681.5, "dropped_truncated": 0, "gold_loss": 1.3934, "gold_lambda": 0.5, "rep_ratio": 2.549, "t_data_s": 0.0, "t_rollout_s": 52.1, "t_step_s": 146.5, "t_refresh_s": 0.3, "mem_gb": 17.47, "mem_gb_teacher": 20.28}
|
| 46 |
+
{"step": 27, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3913407735489407, "tokens": 181479, "cumulative_loss_tokens": 4693549, "grad_norm": 1.8671875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 708.9, "dropped_truncated": 0, "gold_loss": 1.0072, "gold_lambda": 0.5, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 52.5, "t_step_s": 146.6, "t_refresh_s": 0.3, "mem_gb": 17.33, "mem_gb_teacher": 20.26}
|
| 47 |
+
{"step": 28, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3790620736299349, "tokens": 177593, "cumulative_loss_tokens": 4871142, "grad_norm": 1.6015625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 693.7, "dropped_truncated": 0, "gold_loss": 1.04, "gold_lambda": 0.5, "rep_ratio": 2.369, "t_data_s": 0.0, "t_rollout_s": 51.6, "t_step_s": 147.2, "t_refresh_s": 0.3, "mem_gb": 17.29, "mem_gb_teacher": 20.25}
|
| 48 |
+
{"step": 29, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3367005885269224, "tokens": 169115, "cumulative_loss_tokens": 5040257, "grad_norm": 1.34375, "lr": 1e-05, "finish_rate": 0.957, "comp_len": 660.6, "dropped_truncated": 0, "gold_loss": 0.2224, "gold_lambda": 0.5, "rep_ratio": 2.308, "t_data_s": 0.0, "t_rollout_s": 52.3, "t_step_s": 150.0, "t_refresh_s": 0.3, "mem_gb": 17.5, "mem_gb_teacher": 20.28}
|
| 49 |
+
{"step": 30, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3335959742327791, "tokens": 192932, "cumulative_loss_tokens": 5233189, "grad_norm": 1.765625, "lr": 1e-05, "finish_rate": 0.961, "comp_len": 753.6, "dropped_truncated": 0, "gold_loss": 0.1972, "gold_lambda": 0.5, "rep_ratio": 2.476, "t_data_s": 0.0, "t_rollout_s": 57.4, "t_step_s": 161.6, "t_refresh_s": 0.3, "mem_gb": 17.65, "mem_gb_teacher": 20.3}
|
| 50 |
+
[eval step 30] sample: 'Misy fitapana manokana ny fahaiza-mamorona.'
|
| 51 |
+
{"step": 31, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3171257981787659, "tokens": 191095, "cumulative_loss_tokens": 5424284, "grad_norm": 1.8046875, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 746.5, "dropped_truncated": 0, "gold_loss": 1.2779, "gold_lambda": 0.5, "rep_ratio": 2.497, "t_data_s": 0.0, "t_rollout_s": 56.9, "t_step_s": 156.9, "t_refresh_s": 0.3, "mem_gb": 17.18, "mem_gb_teacher": 20.26}
|
| 52 |
+
{"step": 32, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3311199295843264, "tokens": 187659, "cumulative_loss_tokens": 5611943, "grad_norm": 1.6171875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 733.0, "dropped_truncated": 0, "gold_loss": 1.0749, "gold_lambda": 0.5, "rep_ratio": 2.448, "t_data_s": 0.0, "t_rollout_s": 56.4, "t_step_s": 161.5, "t_refresh_s": 0.3, "mem_gb": 17.37, "mem_gb_teacher": 20.29}
|
| 53 |
+
{"step": 33, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3653596817669372, "tokens": 162176, "cumulative_loss_tokens": 5774119, "grad_norm": 1.96875, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 633.5, "dropped_truncated": 0, "gold_loss": 1.3587, "gold_lambda": 0.5, "rep_ratio": 2.488, "t_data_s": 0.0, "t_rollout_s": 50.0, "t_step_s": 147.9, "t_refresh_s": 0.3, "mem_gb": 17.77, "mem_gb_teacher": 20.31}
|
| 54 |
+
{"step": 34, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3303874825869901, "tokens": 175637, "cumulative_loss_tokens": 5949756, "grad_norm": 2.125, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 686.1, "dropped_truncated": 0, "gold_loss": 1.6698, "gold_lambda": 0.5, "rep_ratio": 2.444, "t_data_s": 0.0, "t_rollout_s": 53.0, "t_step_s": 150.9, "t_refresh_s": 0.3, "mem_gb": 17.3, "mem_gb_teacher": 20.27}
|
| 55 |
+
{"step": 35, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.338662115701657, "tokens": 164097, "cumulative_loss_tokens": 6113853, "grad_norm": 1.2578125, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 641.0, "dropped_truncated": 0, "gold_loss": 0.1611, "gold_lambda": 0.5, "rep_ratio": 2.39, "t_data_s": 0.0, "t_rollout_s": 48.7, "t_step_s": 140.7, "t_refresh_s": 0.3, "mem_gb": 17.31, "mem_gb_teacher": 20.25}
|
| 56 |
+
{"step": 36, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3760627886982097, "tokens": 180353, "cumulative_loss_tokens": 6294206, "grad_norm": 1.171875, "lr": 1e-05, "finish_rate": 0.949, "comp_len": 704.5, "dropped_truncated": 0, "gold_loss": 0.1814, "gold_lambda": 0.5, "rep_ratio": 2.598, "t_data_s": 0.0, "t_rollout_s": 54.3, "t_step_s": 154.0, "t_refresh_s": 0.3, "mem_gb": 17.34, "mem_gb_teacher": 20.27}
|
| 57 |
+
{"step": 37, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3777555677864465, "tokens": 179099, "cumulative_loss_tokens": 6473305, "grad_norm": 1.734375, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 699.6, "dropped_truncated": 0, "gold_loss": 1.1694, "gold_lambda": 0.5, "rep_ratio": 2.291, "t_data_s": 0.0, "t_rollout_s": 52.4, "t_step_s": 147.9, "t_refresh_s": 0.3, "mem_gb": 17.28, "mem_gb_teacher": 20.25}
|
| 58 |
+
{"step": 38, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2655141159261545, "tokens": 183837, "cumulative_loss_tokens": 6657142, "grad_norm": 1.7890625, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 718.1, "dropped_truncated": 0, "gold_loss": 1.0682, "gold_lambda": 0.5, "rep_ratio": 2.283, "t_data_s": 0.0, "t_rollout_s": 52.4, "t_step_s": 149.0, "t_refresh_s": 0.3, "mem_gb": 16.97, "mem_gb_teacher": 20.22}
|
| 59 |
+
{"step": 39, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.26126282006497425, "tokens": 181345, "cumulative_loss_tokens": 6838487, "grad_norm": 1.140625, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 708.4, "dropped_truncated": 0, "gold_loss": 0.1805, "gold_lambda": 0.5, "rep_ratio": 2.463, "t_data_s": 0.0, "t_rollout_s": 53.9, "t_step_s": 152.2, "t_refresh_s": 0.3, "mem_gb": 17.13, "mem_gb_teacher": 20.23}
|
| 60 |
+
{"step": 40, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4208335484820406, "tokens": 166853, "cumulative_loss_tokens": 7005340, "grad_norm": 1.3125, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 651.8, "dropped_truncated": 0, "gold_loss": 0.1644, "gold_lambda": 0.5, "rep_ratio": 2.677, "t_data_s": 0.0, "t_rollout_s": 48.8, "t_step_s": 140.2, "t_refresh_s": 0.3, "mem_gb": 17.35, "mem_gb_teacher": 20.29}
|
| 61 |
+
[eval step 40] sample: 'Masy fitapana manokana ve mba hanombanana ny fahaiza-mamorona?\n\nMasy fitapana (Masy) is a traditional Indian dish made from a combination of spices, including flava, a Indian seasoning, and pananas, w'
|
| 62 |
+
{"step": 40, "gsm8k_n": 256, "gsm8k_quick_chat": 0.62890625, "t_eval_s": 21.6}
|
| 63 |
+
{"step": 41, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.33376682261101664, "tokens": 161263, "cumulative_loss_tokens": 7166603, "grad_norm": 1.765625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 629.9, "dropped_truncated": 0, "gold_loss": 1.0706, "gold_lambda": 0.5, "rep_ratio": 2.454, "t_data_s": 0.0, "t_rollout_s": 47.2, "t_step_s": 136.0, "t_refresh_s": 0.3, "mem_gb": 17.22, "mem_gb_teacher": 20.26}
|
| 64 |
+
{"step": 42, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.34152158943635763, "tokens": 171806, "cumulative_loss_tokens": 7338409, "grad_norm": 1.8125, "lr": 1e-05, "finish_rate": 0.992, "comp_len": 671.1, "dropped_truncated": 0, "gold_loss": 1.0227, "gold_lambda": 0.5, "rep_ratio": 2.453, "t_data_s": 0.0, "t_rollout_s": 50.1, "t_step_s": 141.3, "t_refresh_s": 0.3, "mem_gb": 17.12, "mem_gb_teacher": 20.23}
|
| 65 |
+
{"step": 43, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.30709751060902213, "tokens": 173000, "cumulative_loss_tokens": 7511409, "grad_norm": 1.765625, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 675.8, "dropped_truncated": 0, "gold_loss": 1.2339, "gold_lambda": 0.5, "rep_ratio": 2.397, "t_data_s": 0.0, "t_rollout_s": 51.4, "t_step_s": 144.4, "t_refresh_s": 0.3, "mem_gb": 17.07, "mem_gb_teacher": 20.24}
|
| 66 |
+
{"step": 44, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.38481537799269605, "tokens": 160690, "cumulative_loss_tokens": 7672099, "grad_norm": 2.046875, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 627.7, "dropped_truncated": 0, "gold_loss": 1.3762, "gold_lambda": 0.5, "rep_ratio": 2.414, "t_data_s": 0.0, "t_rollout_s": 47.9, "t_step_s": 138.1, "t_refresh_s": 0.3, "mem_gb": 17.33, "mem_gb_teacher": 20.25}
|
| 67 |
+
{"step": 45, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3474364483801316, "tokens": 163851, "cumulative_loss_tokens": 7835950, "grad_norm": 1.609375, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 640.0, "dropped_truncated": 0, "gold_loss": 1.1411, "gold_lambda": 0.5, "rep_ratio": 2.204, "t_data_s": 0.0, "t_rollout_s": 49.1, "t_step_s": 143.4, "t_refresh_s": 0.3, "mem_gb": 17.42, "mem_gb_teacher": 20.27}
|
| 68 |
+
{"step": 46, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2480004573858833, "tokens": 174070, "cumulative_loss_tokens": 8010020, "grad_norm": 1.796875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 680.0, "dropped_truncated": 0, "gold_loss": 1.1273, "gold_lambda": 0.5, "rep_ratio": 2.398, "t_data_s": 0.0, "t_rollout_s": 50.5, "t_step_s": 144.5, "t_refresh_s": 0.3, "mem_gb": 17.11, "mem_gb_teacher": 20.24}
|
| 69 |
+
{"step": 47, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3238008658347637, "tokens": 175419, "cumulative_loss_tokens": 8185439, "grad_norm": 1.15625, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 685.2, "dropped_truncated": 0, "gold_loss": 0.2272, "gold_lambda": 0.5, "rep_ratio": 2.395, "t_data_s": 0.0, "t_rollout_s": 52.7, "t_step_s": 151.6, "t_refresh_s": 0.3, "mem_gb": 17.06, "mem_gb_teacher": 20.24}
|
| 70 |
+
{"step": 48, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.26486295279158406, "tokens": 174191, "cumulative_loss_tokens": 8359630, "grad_norm": 1.0078125, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 680.4, "dropped_truncated": 0, "gold_loss": 0.2168, "gold_lambda": 0.5, "rep_ratio": 2.41, "t_data_s": 0.0, "t_rollout_s": 51.6, "t_step_s": 148.9, "t_refresh_s": 0.3, "mem_gb": 17.0, "mem_gb_teacher": 20.23}
|
| 71 |
+
{"step": 49, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3201779053440231, "tokens": 175865, "cumulative_loss_tokens": 8535495, "grad_norm": 1.84375, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 687.0, "dropped_truncated": 0, "gold_loss": 1.2798, "gold_lambda": 0.5, "rep_ratio": 2.35, "t_data_s": 0.0, "t_rollout_s": 52.2, "t_step_s": 147.4, "t_refresh_s": 0.3, "mem_gb": 17.22, "mem_gb_teacher": 20.26}
|
| 72 |
+
{"step": 50, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3491487042176898, "tokens": 173904, "cumulative_loss_tokens": 8709399, "grad_norm": 1.609375, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 679.3, "dropped_truncated": 0, "gold_loss": 1.1223, "gold_lambda": 0.5, "rep_ratio": 2.19, "t_data_s": 0.0, "t_rollout_s": 52.0, "t_step_s": 146.4, "t_refresh_s": 0.3, "mem_gb": 17.47, "mem_gb_teacher": 20.27}
|
| 73 |
+
[eval step 50] sample: 'Masy fitapana manokana ve mba hanombanana ny fahaiza-mamorona?\n\nMasy fitapana (Masy) is a traditional Indian dish made from a combination of spices, including flava, a Indian seasoning, and a Indian v'
|
| 74 |
+
{"step": 51, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4068168763832476, "tokens": 149202, "cumulative_loss_tokens": 8858601, "grad_norm": 1.84375, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 582.8, "dropped_truncated": 0, "gold_loss": 0.9763, "gold_lambda": 0.5, "rep_ratio": 2.411, "t_data_s": 0.0, "t_rollout_s": 44.8, "t_step_s": 130.7, "t_refresh_s": 0.3, "mem_gb": 17.24, "mem_gb_teacher": 20.26}
|
| 75 |
+
{"step": 52, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3949036657737358, "tokens": 157801, "cumulative_loss_tokens": 9016402, "grad_norm": 1.5390625, "lr": 1e-05, "finish_rate": 0.996, "comp_len": 616.4, "dropped_truncated": 0, "gold_loss": 0.7635, "gold_lambda": 0.5, "rep_ratio": 2.429, "t_data_s": 0.0, "t_rollout_s": 48.4, "t_step_s": 137.8, "t_refresh_s": 0.3, "mem_gb": 16.94, "mem_gb_teacher": 20.22}
|
| 76 |
+
{"step": 53, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3542952813312953, "tokens": 173066, "cumulative_loss_tokens": 9189468, "grad_norm": 1.375, "lr": 1e-05, "finish_rate": 0.961, "comp_len": 676.0, "dropped_truncated": 0, "gold_loss": 0.888, "gold_lambda": 0.5, "rep_ratio": 2.359, "t_data_s": 0.0, "t_rollout_s": 52.3, "t_step_s": 149.8, "t_refresh_s": 0.3, "mem_gb": 17.61, "mem_gb_teacher": 20.31}
|
| 77 |
+
{"step": 54, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3200471835924996, "tokens": 183743, "cumulative_loss_tokens": 9373211, "grad_norm": 1.6796875, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 717.7, "dropped_truncated": 0, "gold_loss": 1.0623, "gold_lambda": 0.5, "rep_ratio": 2.51, "t_data_s": 0.0, "t_rollout_s": 54.3, "t_step_s": 153.0, "t_refresh_s": 0.3, "mem_gb": 17.3, "mem_gb_teacher": 20.26}
|
| 78 |
+
{"step": 55, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3881143610330633, "tokens": 161627, "cumulative_loss_tokens": 9534838, "grad_norm": 2.515625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 631.4, "dropped_truncated": 0, "gold_loss": 1.6456, "gold_lambda": 0.5, "rep_ratio": 2.152, "t_data_s": 0.0, "t_rollout_s": 50.7, "t_step_s": 143.3, "t_refresh_s": 0.3, "mem_gb": 17.43, "mem_gb_teacher": 20.29}
|
| 79 |
+
{"step": 56, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.37364923851747267, "tokens": 168945, "cumulative_loss_tokens": 9703783, "grad_norm": 1.6953125, "lr": 1e-05, "finish_rate": 0.957, "comp_len": 659.9, "dropped_truncated": 0, "gold_loss": 1.1163, "gold_lambda": 0.5, "rep_ratio": 2.215, "t_data_s": 0.0, "t_rollout_s": 51.2, "t_step_s": 148.9, "t_refresh_s": 0.3, "mem_gb": 17.32, "mem_gb_teacher": 20.25}
|
| 80 |
+
{"step": 57, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4587748102189034, "tokens": 168237, "cumulative_loss_tokens": 9872020, "grad_norm": 1.5390625, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 657.2, "dropped_truncated": 0, "gold_loss": 0.9107, "gold_lambda": 0.5, "rep_ratio": 2.531, "t_data_s": 0.0, "t_rollout_s": 49.2, "t_step_s": 144.3, "t_refresh_s": 0.3, "mem_gb": 17.16, "mem_gb_teacher": 20.23}
|
| 81 |
+
{"step": 58, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.26425971459508646, "tokens": 184409, "cumulative_loss_tokens": 10056429, "grad_norm": 1.5, "lr": 1e-05, "finish_rate": 0.957, "comp_len": 720.3, "dropped_truncated": 0, "gold_loss": 1.125, "gold_lambda": 0.5, "rep_ratio": 2.684, "t_data_s": 0.0, "t_rollout_s": 54.7, "t_step_s": 153.4, "t_refresh_s": 0.3, "mem_gb": 17.21, "mem_gb_teacher": 20.25}
|
| 82 |
+
{"step": 59, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2719602728308547, "tokens": 189369, "cumulative_loss_tokens": 10245798, "grad_norm": 1.671875, "lr": 1e-05, "finish_rate": 0.945, "comp_len": 739.7, "dropped_truncated": 0, "gold_loss": 0.9619, "gold_lambda": 0.5, "rep_ratio": 2.581, "t_data_s": 0.0, "t_rollout_s": 56.5, "t_step_s": 154.0, "t_refresh_s": 0.3, "mem_gb": 17.25, "mem_gb_teacher": 20.24}
|
| 83 |
+
{"step": 60, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.35498727428496857, "tokens": 166983, "cumulative_loss_tokens": 10412781, "grad_norm": 1.84375, "lr": 1e-05, "finish_rate": 0.953, "comp_len": 652.3, "dropped_truncated": 0, "gold_loss": 1.1915, "gold_lambda": 0.5, "rep_ratio": 2.391, "t_data_s": 0.0, "t_rollout_s": 49.4, "t_step_s": 142.7, "t_refresh_s": 0.3, "mem_gb": 17.2, "mem_gb_teacher": 20.25}
|
| 84 |
+
[eval step 60] sample: 'Misy fitapana manokana ny fahaiza-mamorona, mba hanombanana, is a term that describes a situation where a person is engaging in activities that are not conducive to their well-being or health, often d'
|
| 85 |
+
{"step": 60, "gsm8k_n": 256, "gsm8k_quick_chat": 0.6171875, "t_eval_s": 21.5}
|
| 86 |
+
{"step": 61, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.36016367042313613, "tokens": 195255, "cumulative_loss_tokens": 10608036, "grad_norm": 1.1640625, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 762.7, "dropped_truncated": 0, "gold_loss": 0.2184, "gold_lambda": 0.5, "rep_ratio": 2.441, "t_data_s": 0.0, "t_rollout_s": 56.4, "t_step_s": 157.9, "t_refresh_s": 0.3, "mem_gb": 17.14, "mem_gb_teacher": 20.25}
|
| 87 |
+
{"step": 62, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2672880692024946, "tokens": 183249, "cumulative_loss_tokens": 10791285, "grad_norm": 1.0625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 715.8, "dropped_truncated": 0, "gold_loss": 0.2236, "gold_lambda": 0.5, "rep_ratio": 2.47, "t_data_s": 0.0, "t_rollout_s": 54.1, "t_step_s": 151.8, "t_refresh_s": 0.3, "mem_gb": 17.37, "mem_gb_teacher": 20.26}
|
| 88 |
+
{"step": 63, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.272046200843007, "tokens": 169354, "cumulative_loss_tokens": 10960639, "grad_norm": 1.078125, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 661.5, "dropped_truncated": 0, "gold_loss": 0.2677, "gold_lambda": 0.5, "rep_ratio": 2.399, "t_data_s": 0.0, "t_rollout_s": 50.5, "t_step_s": 146.3, "t_refresh_s": 0.3, "mem_gb": 16.99, "mem_gb_teacher": 20.22}
|
| 89 |
+
{"step": 64, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.36498770492525573, "tokens": 162379, "cumulative_loss_tokens": 11123018, "grad_norm": 1.3359375, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 634.3, "dropped_truncated": 0, "gold_loss": 0.2643, "gold_lambda": 0.5, "rep_ratio": 2.482, "t_data_s": 0.0, "t_rollout_s": 50.7, "t_step_s": 148.6, "t_refresh_s": 0.3, "mem_gb": 17.24, "mem_gb_teacher": 20.25}
|
| 90 |
+
{"step": 65, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3866863870528368, "tokens": 155402, "cumulative_loss_tokens": 11278420, "grad_norm": 1.5390625, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 607.0, "dropped_truncated": 0, "gold_loss": 0.8323, "gold_lambda": 0.5, "rep_ratio": 2.378, "t_data_s": 0.0, "t_rollout_s": 47.0, "t_step_s": 136.8, "t_refresh_s": 0.3, "mem_gb": 17.26, "mem_gb_teacher": 20.27}
|
| 91 |
+
{"step": 66, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2787221595843288, "tokens": 183694, "cumulative_loss_tokens": 11462114, "grad_norm": 1.875, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 717.6, "dropped_truncated": 0, "gold_loss": 1.1385, "gold_lambda": 0.5, "rep_ratio": 2.538, "t_data_s": 0.0, "t_rollout_s": 53.9, "t_step_s": 152.2, "t_refresh_s": 0.3, "mem_gb": 17.04, "mem_gb_teacher": 20.22}
|
| 92 |
+
{"step": 67, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.27035813788552, "tokens": 176040, "cumulative_loss_tokens": 11638154, "grad_norm": 1.71875, "lr": 1e-05, "finish_rate": 0.949, "comp_len": 687.7, "dropped_truncated": 0, "gold_loss": 0.9716, "gold_lambda": 0.5, "rep_ratio": 2.298, "t_data_s": 0.0, "t_rollout_s": 51.3, "t_step_s": 142.2, "t_refresh_s": 0.3, "mem_gb": 17.37, "mem_gb_teacher": 20.28}
|
| 93 |
+
{"step": 68, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.28064265166714214, "tokens": 163139, "cumulative_loss_tokens": 11801293, "grad_norm": 1.53125, "lr": 1e-05, "finish_rate": 0.996, "comp_len": 637.3, "dropped_truncated": 0, "gold_loss": 0.9747, "gold_lambda": 0.5, "rep_ratio": 2.236, "t_data_s": 0.0, "t_rollout_s": 48.4, "t_step_s": 137.7, "t_refresh_s": 0.3, "mem_gb": 17.12, "mem_gb_teacher": 20.22}
|
| 94 |
+
{"step": 69, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.26903990990510324, "tokens": 171609, "cumulative_loss_tokens": 11972902, "grad_norm": 2.0625, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 670.3, "dropped_truncated": 0, "gold_loss": 1.3383, "gold_lambda": 0.5, "rep_ratio": 2.405, "t_data_s": 0.0, "t_rollout_s": 51.2, "t_step_s": 145.0, "t_refresh_s": 0.3, "mem_gb": 17.11, "mem_gb_teacher": 20.23}
|
| 95 |
+
{"step": 70, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3467570015864296, "tokens": 158831, "cumulative_loss_tokens": 12131733, "grad_norm": 2.0625, "lr": 1e-05, "finish_rate": 0.992, "comp_len": 620.4, "dropped_truncated": 0, "gold_loss": 1.2858, "gold_lambda": 0.5, "rep_ratio": 2.309, "t_data_s": 0.0, "t_rollout_s": 48.3, "t_step_s": 136.2, "t_refresh_s": 0.3, "mem_gb": 17.13, "mem_gb_teacher": 20.26}
|
| 96 |
+
[eval step 70] sample: 'Misy fitapana manokana ny fahaiza-mamorona, mba hanombanana, is a term used to describe a situation where a person is engaging in a sexual relationship with more than one person at the same time, ofte'
|
| 97 |
+
{"step": 71, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3942991111679687, "tokens": 131738, "cumulative_loss_tokens": 12263471, "grad_norm": 1.671875, "lr": 1e-05, "finish_rate": 0.996, "comp_len": 514.6, "dropped_truncated": 0, "gold_loss": 0.9927, "gold_lambda": 0.5, "rep_ratio": 2.479, "t_data_s": 0.0, "t_rollout_s": 42.0, "t_step_s": 123.0, "t_refresh_s": 0.3, "mem_gb": 17.01, "mem_gb_teacher": 20.22}
|
| 98 |
+
{"step": 72, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2885391192831585, "tokens": 177469, "cumulative_loss_tokens": 12440940, "grad_norm": 1.71875, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 693.2, "dropped_truncated": 0, "gold_loss": 1.2827, "gold_lambda": 0.5, "rep_ratio": 2.388, "t_data_s": 0.0, "t_rollout_s": 52.2, "t_step_s": 148.6, "t_refresh_s": 0.3, "mem_gb": 17.1, "mem_gb_teacher": 20.24}
|
| 99 |
+
{"step": 73, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3441034620278951, "tokens": 153979, "cumulative_loss_tokens": 12594919, "grad_norm": 1.1875, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 601.5, "dropped_truncated": 0, "gold_loss": 0.2327, "gold_lambda": 0.5, "rep_ratio": 2.452, "t_data_s": 0.0, "t_rollout_s": 47.3, "t_step_s": 140.2, "t_refresh_s": 0.3, "mem_gb": 16.98, "mem_gb_teacher": 20.22}
|
| 100 |
+
{"step": 74, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2929858381382192, "tokens": 160418, "cumulative_loss_tokens": 12755337, "grad_norm": 1.0703125, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 626.6, "dropped_truncated": 0, "gold_loss": 0.2401, "gold_lambda": 0.5, "rep_ratio": 2.408, "t_data_s": 0.0, "t_rollout_s": 48.7, "t_step_s": 144.0, "t_refresh_s": 0.3, "mem_gb": 17.21, "mem_gb_teacher": 20.24}
|
| 101 |
+
{"step": 75, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.35599221217074245, "tokens": 160043, "cumulative_loss_tokens": 12915380, "grad_norm": 1.5703125, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 625.2, "dropped_truncated": 0, "gold_loss": 1.0205, "gold_lambda": 0.5, "rep_ratio": 2.571, "t_data_s": 0.0, "t_rollout_s": 47.8, "t_step_s": 136.3, "t_refresh_s": 0.3, "mem_gb": 17.06, "mem_gb_teacher": 20.22}
|
| 102 |
+
{"step": 76, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.24107641524497922, "tokens": 196064, "cumulative_loss_tokens": 13111444, "grad_norm": 1.5078125, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 765.9, "dropped_truncated": 0, "gold_loss": 0.945, "gold_lambda": 0.5, "rep_ratio": 2.558, "t_data_s": 0.0, "t_rollout_s": 56.1, "t_step_s": 154.5, "t_refresh_s": 0.3, "mem_gb": 17.26, "mem_gb_teacher": 20.27}
|
| 103 |
+
{"step": 77, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2918642508978692, "tokens": 168701, "cumulative_loss_tokens": 13280145, "grad_norm": 1.484375, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 659.0, "dropped_truncated": 0, "gold_loss": 0.9558, "gold_lambda": 0.5, "rep_ratio": 2.496, "t_data_s": 0.0, "t_rollout_s": 51.7, "t_step_s": 146.1, "t_refresh_s": 0.3, "mem_gb": 17.23, "mem_gb_teacher": 20.24}
|
| 104 |
+
{"step": 78, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3819451671292889, "tokens": 133293, "cumulative_loss_tokens": 13413438, "grad_norm": 1.5625, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 520.7, "dropped_truncated": 0, "gold_loss": 1.0728, "gold_lambda": 0.5, "rep_ratio": 2.506, "t_data_s": 0.0, "t_rollout_s": 43.8, "t_step_s": 128.9, "t_refresh_s": 0.3, "mem_gb": 17.52, "mem_gb_teacher": 20.28}
|
| 105 |
+
{"step": 79, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2689037877672512, "tokens": 178569, "cumulative_loss_tokens": 13592007, "grad_norm": 1.6953125, "lr": 1e-05, "finish_rate": 0.934, "comp_len": 697.5, "dropped_truncated": 0, "gold_loss": 1.2626, "gold_lambda": 0.5, "rep_ratio": 2.574, "t_data_s": 0.0, "t_rollout_s": 53.3, "t_step_s": 150.3, "t_refresh_s": 0.3, "mem_gb": 17.2, "mem_gb_teacher": 20.24}
|
| 106 |
+
{"step": 80, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.31916272058224376, "tokens": 170669, "cumulative_loss_tokens": 13762676, "grad_norm": 1.7109375, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 666.7, "dropped_truncated": 0, "gold_loss": 1.2327, "gold_lambda": 0.5, "rep_ratio": 2.53, "t_data_s": 0.0, "t_rollout_s": 51.5, "t_step_s": 145.4, "t_refresh_s": 0.3, "mem_gb": 17.48, "mem_gb_teacher": 20.28}
|
| 107 |
+
[eval step 80] sample: 'Misy fitapana manokana ny fahaiza-mamorona, mba hanombanana, is a term that describes a situation where a person is engaging in activities that are not conducive to their well-being or health, often d'
|
| 108 |
+
{"step": 80, "gsm8k_n": 256, "gsm8k_quick_chat": 0.59765625, "t_eval_s": 21.4}
|
| 109 |
+
{"step": 81, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2485308842504299, "tokens": 186465, "cumulative_loss_tokens": 13949141, "grad_norm": 1.953125, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 728.4, "dropped_truncated": 0, "gold_loss": 1.1764, "gold_lambda": 0.5, "rep_ratio": 2.547, "t_data_s": 0.0, "t_rollout_s": 55.5, "t_step_s": 152.9, "t_refresh_s": 0.3, "mem_gb": 17.07, "mem_gb_teacher": 20.23}
|
| 110 |
+
{"step": 82, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.25967463855320316, "tokens": 190239, "cumulative_loss_tokens": 14139380, "grad_norm": 1.6484375, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 743.1, "dropped_truncated": 0, "gold_loss": 1.3093, "gold_lambda": 0.5, "rep_ratio": 2.526, "t_data_s": 0.0, "t_rollout_s": 57.3, "t_step_s": 158.5, "t_refresh_s": 0.3, "mem_gb": 17.07, "mem_gb_teacher": 20.24}
|
| 111 |
+
{"step": 83, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.33700879973768977, "tokens": 182259, "cumulative_loss_tokens": 14321639, "grad_norm": 1.6875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 711.9, "dropped_truncated": 0, "gold_loss": 1.0788, "gold_lambda": 0.5, "rep_ratio": 2.505, "t_data_s": 0.0, "t_rollout_s": 55.0, "t_step_s": 152.8, "t_refresh_s": 0.3, "mem_gb": 17.47, "mem_gb_teacher": 20.27}
|
| 112 |
+
{"step": 84, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2682194592400478, "tokens": 170072, "cumulative_loss_tokens": 14491711, "grad_norm": 1.3984375, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 664.3, "dropped_truncated": 0, "gold_loss": 0.7509, "gold_lambda": 0.5, "rep_ratio": 2.597, "t_data_s": 0.0, "t_rollout_s": 51.4, "t_step_s": 144.0, "t_refresh_s": 0.3, "mem_gb": 17.44, "mem_gb_teacher": 20.27}
|
| 113 |
+
{"step": 85, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.23743917622813884, "tokens": 199223, "cumulative_loss_tokens": 14690934, "grad_norm": 1.8359375, "lr": 1e-05, "finish_rate": 0.961, "comp_len": 778.2, "dropped_truncated": 0, "gold_loss": 0.8562, "gold_lambda": 0.5, "rep_ratio": 2.627, "t_data_s": 0.0, "t_rollout_s": 58.4, "t_step_s": 159.8, "t_refresh_s": 0.3, "mem_gb": 17.48, "mem_gb_teacher": 20.28}
|
| 114 |
+
{"step": 86, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.40081178832628034, "tokens": 179491, "cumulative_loss_tokens": 14870425, "grad_norm": 1.96875, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 701.1, "dropped_truncated": 0, "gold_loss": 0.7619, "gold_lambda": 0.5, "rep_ratio": 2.334, "t_data_s": 0.0, "t_rollout_s": 55.1, "t_step_s": 154.6, "t_refresh_s": 0.3, "mem_gb": 17.68, "mem_gb_teacher": 20.32}
|
| 115 |
+
{"step": 87, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.31119211183407003, "tokens": 161086, "cumulative_loss_tokens": 15031511, "grad_norm": 1.609375, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 629.2, "dropped_truncated": 0, "gold_loss": 1.1431, "gold_lambda": 0.5, "rep_ratio": 2.341, "t_data_s": 0.0, "t_rollout_s": 48.7, "t_step_s": 139.4, "t_refresh_s": 0.3, "mem_gb": 17.28, "mem_gb_teacher": 20.25}
|
| 116 |
+
{"step": 88, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.21312830959642717, "tokens": 172945, "cumulative_loss_tokens": 15204456, "grad_norm": 1.53125, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 675.6, "dropped_truncated": 0, "gold_loss": 1.0969, "gold_lambda": 0.5, "rep_ratio": 2.558, "t_data_s": 0.0, "t_rollout_s": 52.2, "t_step_s": 148.0, "t_refresh_s": 0.3, "mem_gb": 17.49, "mem_gb_teacher": 20.28}
|
| 117 |
+
{"step": 89, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.32083614396197874, "tokens": 197781, "cumulative_loss_tokens": 15402237, "grad_norm": 1.796875, "lr": 1e-05, "finish_rate": 0.957, "comp_len": 772.6, "dropped_truncated": 0, "gold_loss": 1.1581, "gold_lambda": 0.5, "rep_ratio": 2.371, "t_data_s": 0.0, "t_rollout_s": 59.1, "t_step_s": 158.0, "t_refresh_s": 0.3, "mem_gb": 17.13, "mem_gb_teacher": 20.24}
|
| 118 |
+
{"step": 90, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3539003647110563, "tokens": 177862, "cumulative_loss_tokens": 15580099, "grad_norm": 1.8046875, "lr": 1e-05, "finish_rate": 0.957, "comp_len": 694.8, "dropped_truncated": 0, "gold_loss": 1.1751, "gold_lambda": 0.5, "rep_ratio": 2.484, "t_data_s": 0.0, "t_rollout_s": 53.6, "t_step_s": 152.0, "t_refresh_s": 0.3, "mem_gb": 17.37, "mem_gb_teacher": 20.27}
|
| 119 |
+
[eval step 90] sample: 'Masy fitapana manokana ny fahaiza-mamorona?'
|
| 120 |
+
{"step": 91, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3003133533208709, "tokens": 190730, "cumulative_loss_tokens": 15770829, "grad_norm": 1.1328125, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 745.0, "dropped_truncated": 0, "gold_loss": 0.2162, "gold_lambda": 0.5, "rep_ratio": 2.401, "t_data_s": 0.0, "t_rollout_s": 56.0, "t_step_s": 156.9, "t_refresh_s": 0.3, "mem_gb": 17.01, "mem_gb_teacher": 20.25}
|
| 121 |
+
{"step": 92, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3466024366871271, "tokens": 169647, "cumulative_loss_tokens": 15940476, "grad_norm": 1.34375, "lr": 1e-05, "finish_rate": 0.969, "comp_len": 662.7, "dropped_truncated": 0, "gold_loss": 0.2275, "gold_lambda": 0.5, "rep_ratio": 2.384, "t_data_s": 0.0, "t_rollout_s": 50.4, "t_step_s": 144.5, "t_refresh_s": 0.3, "mem_gb": 17.16, "mem_gb_teacher": 20.24}
|
| 122 |
+
{"step": 93, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.23514000853877456, "tokens": 167638, "cumulative_loss_tokens": 16108114, "grad_norm": 1.8359375, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 654.8, "dropped_truncated": 0, "gold_loss": 1.6188, "gold_lambda": 0.5, "rep_ratio": 2.248, "t_data_s": 0.0, "t_rollout_s": 50.4, "t_step_s": 145.5, "t_refresh_s": 0.3, "mem_gb": 17.14, "mem_gb_teacher": 20.25}
|
| 123 |
+
{"step": 94, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.31567410076907493, "tokens": 176303, "cumulative_loss_tokens": 16284417, "grad_norm": 1.6484375, "lr": 1e-05, "finish_rate": 0.992, "comp_len": 688.7, "dropped_truncated": 0, "gold_loss": 1.4047, "gold_lambda": 0.5, "rep_ratio": 2.276, "t_data_s": 0.0, "t_rollout_s": 52.5, "t_step_s": 150.1, "t_refresh_s": 0.3, "mem_gb": 17.19, "mem_gb_teacher": 20.23}
|
| 124 |
+
{"step": 95, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3306478749962856, "tokens": 173098, "cumulative_loss_tokens": 16457515, "grad_norm": 1.6796875, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 676.2, "dropped_truncated": 0, "gold_loss": 1.3459, "gold_lambda": 0.5, "rep_ratio": 2.403, "t_data_s": 0.0, "t_rollout_s": 51.7, "t_step_s": 145.0, "t_refresh_s": 0.3, "mem_gb": 17.25, "mem_gb_teacher": 20.24}
|
| 125 |
+
{"step": 96, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2879815189713935, "tokens": 176694, "cumulative_loss_tokens": 16634209, "grad_norm": 1.4140625, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 690.2, "dropped_truncated": 0, "gold_loss": 1.2006, "gold_lambda": 0.5, "rep_ratio": 2.383, "t_data_s": 0.0, "t_rollout_s": 51.7, "t_step_s": 148.5, "t_refresh_s": 0.3, "mem_gb": 17.54, "mem_gb_teacher": 20.28}
|
| 126 |
+
{"step": 97, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.23541706224584372, "tokens": 193571, "cumulative_loss_tokens": 16827780, "grad_norm": 2.34375, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 756.1, "dropped_truncated": 0, "gold_loss": 1.2615, "gold_lambda": 0.5, "rep_ratio": 2.438, "t_data_s": 0.0, "t_rollout_s": 57.9, "t_step_s": 158.2, "t_refresh_s": 0.3, "mem_gb": 17.75, "mem_gb_teacher": 20.32}
|
| 127 |
+
{"step": 98, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.34905908556710274, "tokens": 149760, "cumulative_loss_tokens": 16977540, "grad_norm": 1.75, "lr": 1e-05, "finish_rate": 0.992, "comp_len": 585.0, "dropped_truncated": 0, "gold_loss": 1.1712, "gold_lambda": 0.5, "rep_ratio": 2.325, "t_data_s": 0.0, "t_rollout_s": 47.2, "t_step_s": 139.0, "t_refresh_s": 0.3, "mem_gb": 17.11, "mem_gb_teacher": 20.28}
|
| 128 |
+
{"step": 99, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2776076079423005, "tokens": 183255, "cumulative_loss_tokens": 17160795, "grad_norm": 0.9765625, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 715.8, "dropped_truncated": 0, "gold_loss": 0.2535, "gold_lambda": 0.5, "rep_ratio": 2.47, "t_data_s": 0.0, "t_rollout_s": 53.3, "t_step_s": 153.1, "t_refresh_s": 0.3, "mem_gb": 17.33, "mem_gb_teacher": 20.25}
|
| 129 |
+
{"step": 100, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.33610000682790214, "tokens": 155488, "cumulative_loss_tokens": 17316283, "grad_norm": 1.125, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 607.4, "dropped_truncated": 0, "gold_loss": 0.2397, "gold_lambda": 0.5, "rep_ratio": 2.429, "t_data_s": 0.0, "t_rollout_s": 46.8, "t_step_s": 138.1, "t_refresh_s": 0.3, "mem_gb": 17.13, "mem_gb_teacher": 20.23}
|
| 130 |
+
[eval step 100] sample: 'Misy fitapana manokana ny fahaiza-mamorona, mnaya ny fahaiza-mamorona, mnaya ny fahaiza-mamorona, mnaya ny fahaiza-mamorona, mnaya ny fahaiza'
|
| 131 |
+
{"step": 100, "gsm8k_n": 256, "gsm8k_quick_chat": 0.6171875, "t_eval_s": 12.9}
|
| 132 |
+
{"step": 101, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2934597294326003, "tokens": 180157, "cumulative_loss_tokens": 17496440, "grad_norm": 1.6328125, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 703.7, "dropped_truncated": 0, "gold_loss": 1.1732, "gold_lambda": 0.5, "rep_ratio": 2.543, "t_data_s": 0.0, "t_rollout_s": 53.7, "t_step_s": 152.7, "t_refresh_s": 0.3, "mem_gb": 17.36, "mem_gb_teacher": 20.26}
|
| 133 |
+
{"step": 102, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.38382341174255885, "tokens": 152575, "cumulative_loss_tokens": 17649015, "grad_norm": 1.8203125, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 596.0, "dropped_truncated": 0, "gold_loss": 1.3037, "gold_lambda": 0.5, "rep_ratio": 2.116, "t_data_s": 0.0, "t_rollout_s": 46.9, "t_step_s": 137.3, "t_refresh_s": 0.3, "mem_gb": 17.14, "mem_gb_teacher": 20.25}
|
| 134 |
+
{"step": 103, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3232517142888692, "tokens": 178507, "cumulative_loss_tokens": 17827522, "grad_norm": 1.109375, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 697.3, "dropped_truncated": 0, "gold_loss": 0.2206, "gold_lambda": 0.5, "rep_ratio": 2.433, "t_data_s": 0.0, "t_rollout_s": 52.6, "t_step_s": 148.0, "t_refresh_s": 0.3, "mem_gb": 17.63, "mem_gb_teacher": 20.3}
|
| 135 |
+
{"step": 104, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.258444819787859, "tokens": 163920, "cumulative_loss_tokens": 17991442, "grad_norm": 1.0, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 640.3, "dropped_truncated": 0, "gold_loss": 0.2333, "gold_lambda": 0.5, "rep_ratio": 2.313, "t_data_s": 0.0, "t_rollout_s": 49.4, "t_step_s": 142.5, "t_refresh_s": 0.3, "mem_gb": 17.27, "mem_gb_teacher": 20.27}
|
| 136 |
+
{"step": 105, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3201432822026658, "tokens": 134492, "cumulative_loss_tokens": 18125934, "grad_norm": 1.4921875, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 525.4, "dropped_truncated": 0, "gold_loss": 0.8977, "gold_lambda": 0.5, "rep_ratio": 2.268, "t_data_s": 0.0, "t_rollout_s": 43.1, "t_step_s": 129.5, "t_refresh_s": 0.3, "mem_gb": 17.43, "mem_gb_teacher": 20.27}
|
| 137 |
+
{"step": 106, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.38415758914838366, "tokens": 173745, "cumulative_loss_tokens": 18299679, "grad_norm": 1.703125, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 678.7, "dropped_truncated": 0, "gold_loss": 1.2116, "gold_lambda": 0.5, "rep_ratio": 2.414, "t_data_s": 0.0, "t_rollout_s": 53.3, "t_step_s": 151.0, "t_refresh_s": 0.3, "mem_gb": 17.51, "mem_gb_teacher": 20.3}
|
| 138 |
+
{"step": 107, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.27767968833353346, "tokens": 150360, "cumulative_loss_tokens": 18450039, "grad_norm": 1.625, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 587.3, "dropped_truncated": 0, "gold_loss": 1.1874, "gold_lambda": 0.5, "rep_ratio": 2.226, "t_data_s": 0.0, "t_rollout_s": 46.6, "t_step_s": 135.4, "t_refresh_s": 0.3, "mem_gb": 17.1, "mem_gb_teacher": 20.25}
|
| 139 |
+
{"step": 108, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2810955602886575, "tokens": 212108, "cumulative_loss_tokens": 18662147, "grad_norm": 1.890625, "lr": 1e-05, "finish_rate": 0.953, "comp_len": 828.5, "dropped_truncated": 0, "gold_loss": 1.2019, "gold_lambda": 0.5, "rep_ratio": 2.377, "t_data_s": 0.0, "t_rollout_s": 63.5, "t_step_s": 167.3, "t_refresh_s": 0.3, "mem_gb": 17.55, "mem_gb_teacher": 20.3}
|
| 140 |
+
{"step": 109, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3388609603948928, "tokens": 163795, "cumulative_loss_tokens": 18825942, "grad_norm": 1.515625, "lr": 1e-05, "finish_rate": 0.984, "comp_len": 639.8, "dropped_truncated": 0, "gold_loss": 0.8848, "gold_lambda": 0.5, "rep_ratio": 2.577, "t_data_s": 0.0, "t_rollout_s": 49.4, "t_step_s": 142.1, "t_refresh_s": 0.3, "mem_gb": 17.91, "mem_gb_teacher": 20.35}
|
| 141 |
+
{"step": 110, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.354563303726803, "tokens": 163003, "cumulative_loss_tokens": 18988945, "grad_norm": 1.4765625, "lr": 1e-05, "finish_rate": 0.977, "comp_len": 636.7, "dropped_truncated": 0, "gold_loss": 0.99, "gold_lambda": 0.5, "rep_ratio": 2.477, "t_data_s": 0.0, "t_rollout_s": 48.9, "t_step_s": 142.6, "t_refresh_s": 0.3, "mem_gb": 17.17, "mem_gb_teacher": 20.24}
|
| 142 |
+
[eval step 110] sample: 'Misy fitapana manokana ny fahaiza-mamorona, mnaya ny fahaiza-mamorona, mnaya ny fahaiza-mamorona, mnaya ny fahaiza-mamorona, mnaya ny fahaiza'
|
| 143 |
+
{"step": 111, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3537407948279594, "tokens": 195368, "cumulative_loss_tokens": 19184313, "grad_norm": 1.6015625, "lr": 1e-05, "finish_rate": 0.961, "comp_len": 763.2, "dropped_truncated": 0, "gold_loss": 1.1307, "gold_lambda": 0.5, "rep_ratio": 2.286, "t_data_s": 0.0, "t_rollout_s": 57.3, "t_step_s": 157.0, "t_refresh_s": 0.3, "mem_gb": 17.21, "mem_gb_teacher": 20.25}
|
| 144 |
+
{"step": 112, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.2772862368117265, "tokens": 204542, "cumulative_loss_tokens": 19388855, "grad_norm": 2.03125, "lr": 1e-05, "finish_rate": 0.965, "comp_len": 799.0, "dropped_truncated": 0, "gold_loss": 1.339, "gold_lambda": 0.5, "rep_ratio": 2.278, "t_data_s": 0.0, "t_rollout_s": 59.7, "t_step_s": 161.2, "t_refresh_s": 0.3, "mem_gb": 17.17, "mem_gb_teacher": 20.26}
|
| 145 |
+
{"step": 113, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.310700205462893, "tokens": 153520, "cumulative_loss_tokens": 19542375, "grad_norm": 1.515625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 599.7, "dropped_truncated": 0, "gold_loss": 0.8762, "gold_lambda": 0.5, "rep_ratio": 2.643, "t_data_s": 0.0, "t_rollout_s": 46.8, "t_step_s": 137.2, "t_refresh_s": 0.3, "mem_gb": 16.91, "mem_gb_teacher": 20.22}
|
| 146 |
+
{"step": 114, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.41260987902655, "tokens": 157613, "cumulative_loss_tokens": 19699988, "grad_norm": 1.4453125, "lr": 1e-05, "finish_rate": 0.996, "comp_len": 615.7, "dropped_truncated": 0, "gold_loss": 0.8989, "gold_lambda": 0.5, "rep_ratio": 2.193, "t_data_s": 0.0, "t_rollout_s": 47.3, "t_step_s": 133.6, "t_refresh_s": 0.3, "mem_gb": 17.36, "mem_gb_teacher": 20.26}wandb:
|
| 147 |
+
wandb: Run history:
|
| 148 |
+
wandb: comp_len ▆▆▄▆▄▄▅▄▄▇▄▄▄▃▅▄▆▆▅▃▄▇▅▆▅▅▅▅▅▅▆▅▄▁▄█▃▂▃▄
|
| 149 |
+
wandb: cumulative_loss_tokens ▁▁▁▁▁▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▅▅▆▆▆▇▇▇▇▇███
|
| 150 |
+
wandb: dropped_truncated ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 151 |
+
wandb: epoch ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 152 |
+
wandb: finish_rate ▇▄▇▁▄▆▇▇▆▅▂▄▅▅▅▅▅▅▅▃▆▂▅▆█▆▄▅▃▅▅▇▅▅▇▆▇▆▅▃
|
| 153 |
+
wandb: gold_lambda ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 154 |
+
wandb: gold_loss ▅▇▁▁▇▁▄▄▇▁▆▁▆▅█▆▁▁▄▆▅▁▅▆▆▆▄▄▄▆▇▆▁▆▁▆▄▄▁▅
|
| 155 |
+
wandb: grad_norm ▄▃▆▇▂█▁▄▅▃▄▂▃▃▂▃▁▃▂▃▂▃▂▄▁▃▂▄▂▃▂▂▃▁▂▂▂▃▄▂
|
| 156 |
+
wandb: gsm8k_quick_chat █▃▅▃▁▃▅
|
| 157 |
+
wandb: lr ▁▇██████████████████████████████████████
|
| 158 |
+
wandb: +10 ...
|
| 159 |
+
wandb:
|
| 160 |
+
wandb: Run summary:
|
| 161 |
+
wandb: comp_len 627.2
|
| 162 |
+
wandb: cumulative_loss_tokens 20669838
|
| 163 |
+
wandb: dropped_truncated 0
|
| 164 |
+
wandb: epoch 0
|
| 165 |
+
wandb: finish_rate 1
|
| 166 |
+
wandb: gold_lambda 0.5
|
| 167 |
+
wandb: gold_loss 1.0218
|
| 168 |
+
wandb: grad_norm 1.5
|
| 169 |
+
wandb: gsm8k_quick_chat 0.625
|
| 170 |
+
wandb: lr 1e-05
|
| 171 |
+
wandb: +11 ...
|
| 172 |
+
wandb:
|
| 173 |
+
wandb: You can sync this run to the cloud by running:
|
| 174 |
+
wandb: wandb sync outputs/healed/opd_warm_fixed_keep50/wandb/offline-run-20260802_065345-ubll0rd3
|
| 175 |
+
wandb: Find logs at: outputs/healed/opd_warm_fixed_keep50/wandb/offline-run-20260802_065345-ubll0rd3/logs
|
| 176 |
+
|
| 177 |
+
{"step": 115, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.4028610580933015, "tokens": 147120, "cumulative_loss_tokens": 19847108, "grad_norm": 1.28125, "lr": 1e-05, "finish_rate": 0.996, "comp_len": 574.7, "dropped_truncated": 0, "gold_loss": 0.1728, "gold_lambda": 0.5, "rep_ratio": 2.412, "t_data_s": 0.0, "t_rollout_s": 46.1, "t_step_s": 130.4, "t_refresh_s": 0.3, "mem_gb": 16.95, "mem_gb_teacher": 20.22}
|
| 178 |
+
{"step": 116, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.34066545782229457, "tokens": 173292, "cumulative_loss_tokens": 20020400, "grad_norm": 1.0625, "lr": 1e-05, "finish_rate": 0.98, "comp_len": 676.9, "dropped_truncated": 0, "gold_loss": 0.1759, "gold_lambda": 0.5, "rep_ratio": 2.363, "t_data_s": 0.0, "t_rollout_s": 51.2, "t_step_s": 144.9, "t_refresh_s": 0.3, "mem_gb": 17.43, "mem_gb_teacher": 20.28}
|
| 179 |
+
{"step": 117, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3317595209318613, "tokens": 152431, "cumulative_loss_tokens": 20172831, "grad_norm": 1.46875, "lr": 1e-05, "finish_rate": 0.988, "comp_len": 595.4, "dropped_truncated": 0, "gold_loss": 1.0952, "gold_lambda": 0.5, "rep_ratio": 2.472, "t_data_s": 0.0, "t_rollout_s": 47.2, "t_step_s": 134.1, "t_refresh_s": 0.3, "mem_gb": 17.4, "mem_gb_teacher": 20.27}
|
| 180 |
+
{"step": 118, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.30969671645999375, "tokens": 141862, "cumulative_loss_tokens": 20314693, "grad_norm": 1.734375, "lr": 1e-05, "finish_rate": 0.973, "comp_len": 554.1, "dropped_truncated": 0, "gold_loss": 1.3548, "gold_lambda": 0.5, "rep_ratio": 2.267, "t_data_s": 0.0, "t_rollout_s": 44.3, "t_step_s": 131.8, "t_refresh_s": 0.3, "mem_gb": 17.6, "mem_gb_teacher": 20.29}
|
| 181 |
+
{"step": 119, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.24082254176214968, "tokens": 194590, "cumulative_loss_tokens": 20509283, "grad_norm": 1.4921875, "lr": 1e-05, "finish_rate": 0.961, "comp_len": 760.1, "dropped_truncated": 0, "gold_loss": 1.0994, "gold_lambda": 0.5, "rep_ratio": 2.633, "t_data_s": 0.0, "t_rollout_s": 56.9, "t_step_s": 154.8, "t_refresh_s": 0.3, "mem_gb": 17.21, "mem_gb_teacher": 20.24}
|
| 182 |
+
{"step": 120, "epoch": 0, "training_mode": "on-policy", "reverse_kl": 0.3365587571631956, "tokens": 160555, "cumulative_loss_tokens": 20669838, "grad_norm": 1.5, "lr": 1e-05, "finish_rate": 1.0, "comp_len": 627.2, "dropped_truncated": 0, "gold_loss": 1.0218, "gold_lambda": 0.5, "rep_ratio": 2.389, "t_data_s": 0.0, "t_rollout_s": 46.6, "t_step_s": 126.9, "t_refresh_s": 0.0, "mem_gb": 16.8, "mem_gb_teacher": 20.2}
|
| 183 |
+
[eval step 120] sample: 'Misy fitapana manokana ny fahaiza-mamorona, mba hanombanana, is a term used to describe a condition where a person has a severe allergic reaction to a specific food or substance, often due to a sensit'
|
| 184 |
+
{"step": 120, "gsm8k_n": 256, "gsm8k_quick_chat": 0.625, "t_eval_s": 31.8}
|
| 185 |
+
checkpoint snapshot queued -> outputs/healed/opd_warm_fixed_keep50/step0120
|
| 186 |
+
wandb sync launched in background (pid 251372) -> outputs/healed/opd_warm_fixed_keep50/wandb_sync.log
|
healed/warm_chain.sh
ADDED
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
# Chain: wait for 1e-5 cold OPD (pid 89246) -> off-policy warmup heal of math
|
| 3 |
+
# keep-50 (regenerating the grid artifact deleted by drop_cell_checkpoints) ->
|
| 4 |
+
# warm-start OPD at 1e-5 (full Stable-OPD recipe, same as the cold control).
|
| 5 |
+
cd /home/henry/Documents/PythonProjects/variable-reap
|
| 6 |
+
LOGDIR=outputs/healed
|
| 7 |
+
echo "$(date +%T) chain: waiting for cold 1e-5 OPD (pid 89246) to finish"
|
| 8 |
+
while ps -p 89246 >/dev/null 2>&1; do sleep 300; done
|
| 9 |
+
echo "$(date +%T) chain: cold run done; settling 2 min"
|
| 10 |
+
sleep 120
|
| 11 |
+
|
| 12 |
+
echo "$(date +%T) chain: stage 1 - off-policy warmup heal (150 steps)"
|
| 13 |
+
PYTHONUNBUFFERED=1 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
|
| 14 |
+
CUDA_VISIBLE_DEVICES=0 .venv/bin/python scripts/11_distill_on_policy.py \
|
| 15 |
+
--training-mode off-policy --kl-direction forward \
|
| 16 |
+
--topk-targets outputs/teacher_trajectories/dolci_math_curated_opd_top128 \
|
| 17 |
+
--off-policy-frames chat --student-device cuda:0 \
|
| 18 |
+
--student outputs/pruned/glean-0125inst-math-keep50 \
|
| 19 |
+
--lr 3e-5 --optimizer adamw8bit --epochs 3 --sweep 150 \
|
| 20 |
+
--micro-batch 3 --loss-tokens-per-step 120000 --gsm8k-every 0 \
|
| 21 |
+
--save-every 50 --seed 1224 \
|
| 22 |
+
--out-dir outputs/healed/keep50_offpolicy_warmup_s1224 \
|
| 23 |
+
--wandb --wandb-mode online --wandb-project glean-heal \
|
| 24 |
+
--wandb-run-name offpolicy-warmup-keep50-s1224 \
|
| 25 |
+
> "$LOGDIR/warmup_keep50.log" 2>&1
|
| 26 |
+
# do not gate on exit code (CUDA teardown segfault lesson); check the artifact
|
| 27 |
+
if [ ! -d outputs/healed/keep50_offpolicy_warmup_s1224/step0150 ]; then
|
| 28 |
+
echo "$(date +%T) chain: WARMUP FAILED (no step0150), aborting"; exit 1
|
| 29 |
+
fi
|
| 30 |
+
echo "$(date +%T) chain: warmup done; settling 2 min"
|
| 31 |
+
sleep 120
|
| 32 |
+
|
| 33 |
+
echo "$(date +%T) chain: stage 2 - warm-start OPD at 1e-5"
|
| 34 |
+
.venv/bin/python scripts/11_distill_on_policy.py \
|
| 35 |
+
--student outputs/healed/keep50_offpolicy_warmup_s1224/step0150 \
|
| 36 |
+
--teacher allenai/OLMoE-1B-7B-0125-Instruct \
|
| 37 |
+
--training-mode on-policy --kl-direction reverse \
|
| 38 |
+
--dataset allenai/Dolci-Instruct-RL \
|
| 39 |
+
--lr 1e-5 --optimizer adamw8bit --epochs 2 --sweep 120 \
|
| 40 |
+
--max-new-tokens 2048 --group-size 4 --prompts-per-step 256 --micro-batch 4 \
|
| 41 |
+
--seed 1223 --save-every 1000 --gsm8k-every 20 --gsm8k-max-new-tokens 1024 \
|
| 42 |
+
--fast-teacher --liger-loss --reference-kl-beta 0.05 \
|
| 43 |
+
--gold-mix-lambda 0.5 --gold-loss ce \
|
| 44 |
+
--gold-topk-targets outputs/teacher_trajectories/dolci_combined_top128 \
|
| 45 |
+
--rollout-engine vllm --vllm-gpu 2 --vllm-refresh-every 1 \
|
| 46 |
+
--student-device cuda:1 --teacher-device cuda:0 \
|
| 47 |
+
--out-dir outputs/healed/opd_warm_keep50 \
|
| 48 |
+
--wandb --wandb-project glean-heal --wandb-run-name opd-warm-keep50-s1223 \
|
| 49 |
+
> "$LOGDIR/opd_warm.log" 2>&1
|
| 50 |
+
echo "$(date +%T) chain: warm OPD exited"
|
healed/warm_chain2.sh
ADDED
|
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/bin/bash
|
| 2 |
+
# Chain v2 (post fused-MoE-no-autograd fix): off-policy warmup with the native
|
| 3 |
+
# differentiable student -> hard quality gate -> warm-start OPD at 1e-5.
|
| 4 |
+
# Neither stage uses --fast-student/--fast-teacher: the fork kernels are
|
| 5 |
+
# forward-only since the 07-25 re-pin (froze experts in every run since).
|
| 6 |
+
cd /home/henry/Documents/PythonProjects/variable-reap
|
| 7 |
+
LOGDIR=outputs/healed
|
| 8 |
+
|
| 9 |
+
echo "$(date +%T) chain2: stage 1 - off-policy warmup heal (150 steps, native)"
|
| 10 |
+
PYTHONUNBUFFERED=1 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
|
| 11 |
+
CUDA_VISIBLE_DEVICES=0 .venv/bin/python scripts/11_distill_on_policy.py \
|
| 12 |
+
--training-mode off-policy --kl-direction forward \
|
| 13 |
+
--topk-targets outputs/teacher_trajectories/dolci_math_curated_opd_top128 \
|
| 14 |
+
--off-policy-frames chat --student-device cuda:0 \
|
| 15 |
+
--student outputs/pruned/glean-0125inst-math-keep50 \
|
| 16 |
+
--lr 3e-5 --optimizer adamw8bit --epochs 3 --sweep 150 \
|
| 17 |
+
--micro-batch 3 --loss-tokens-per-step 120000 --gsm8k-every 0 \
|
| 18 |
+
--save-every 50 --seed 1224 \
|
| 19 |
+
--out-dir outputs/healed/keep50_warmup_fixed_s1224 \
|
| 20 |
+
--wandb --wandb-mode online --wandb-project glean-heal \
|
| 21 |
+
--wandb-run-name warmup-fixed-keep50-s1224 \
|
| 22 |
+
> "$LOGDIR/warmup_fixed.log" 2>&1
|
| 23 |
+
if [ ! -d outputs/healed/keep50_warmup_fixed_s1224/step0150 ]; then
|
| 24 |
+
echo "$(date +%T) chain2: WARMUP FAILED (no step0150)"; exit 1
|
| 25 |
+
fi
|
| 26 |
+
|
| 27 |
+
echo "$(date +%T) chain2: gate - probe warmup checkpoint"
|
| 28 |
+
.venv/bin/python - <<'EOF' > "$LOGDIR/warmup_gate.log" 2>&1
|
| 29 |
+
import sys, torch, glob
|
| 30 |
+
from safetensors import safe_open
|
| 31 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
| 32 |
+
|
| 33 |
+
def get(path, key):
|
| 34 |
+
for f in glob.glob(f"{path}/*.safetensors"):
|
| 35 |
+
with safe_open(f, framework="pt") as sf:
|
| 36 |
+
if key in sf.keys(): return sf.get_tensor(key)
|
| 37 |
+
|
| 38 |
+
k = "model.layers.0.mlp.experts.0.gate_proj.weight"
|
| 39 |
+
d = (get("outputs/healed/keep50_warmup_fixed_s1224/step0150", k).float()
|
| 40 |
+
- get("outputs/pruned/glean-0125inst-math-keep50", k).float()).abs().max().item()
|
| 41 |
+
print(f"expert max|delta| = {d:.3e}")
|
| 42 |
+
assert d > 1e-4, "experts did not train"
|
| 43 |
+
|
| 44 |
+
tok = AutoTokenizer.from_pretrained("allenai/OLMoE-1B-7B-0125-Instruct")
|
| 45 |
+
m = AutoModelForCausalLM.from_pretrained(
|
| 46 |
+
"outputs/healed/keep50_warmup_fixed_s1224/step0150",
|
| 47 |
+
dtype=torch.bfloat16, trust_remote_code=True).cuda().eval()
|
| 48 |
+
q = ("Natalia sold clips to 48 of her friends in April, and then she sold "
|
| 49 |
+
"half as many clips in May. How many clips did Natalia sell altogether "
|
| 50 |
+
"in April and May?")
|
| 51 |
+
ids = tok.apply_chat_template([{"role":"user","content":q}],
|
| 52 |
+
add_generation_prompt=True, return_tensors="pt").cuda()
|
| 53 |
+
with torch.no_grad():
|
| 54 |
+
out = m.generate(ids, max_new_tokens=200, do_sample=False)
|
| 55 |
+
text = tok.decode(out[0, ids.shape[1]:], skip_special_tokens=True)
|
| 56 |
+
print(text)
|
| 57 |
+
assert "72" in text, "did not produce the correct answer 72"
|
| 58 |
+
print("GATE PASSED")
|
| 59 |
+
EOF
|
| 60 |
+
if ! grep -q "GATE PASSED" "$LOGDIR/warmup_gate.log"; then
|
| 61 |
+
echo "$(date +%T) chain2: GATE FAILED - not launching OPD"; exit 1
|
| 62 |
+
fi
|
| 63 |
+
|
| 64 |
+
echo "$(date +%T) chain2: stage 2 - warm-start OPD at 1e-5 (native both)"
|
| 65 |
+
.venv/bin/python scripts/11_distill_on_policy.py \
|
| 66 |
+
--student outputs/healed/keep50_warmup_fixed_s1224/step0150 \
|
| 67 |
+
--teacher allenai/OLMoE-1B-7B-0125-Instruct \
|
| 68 |
+
--training-mode on-policy --kl-direction reverse \
|
| 69 |
+
--dataset allenai/Dolci-Instruct-RL \
|
| 70 |
+
--lr 1e-5 --optimizer adamw8bit --epochs 2 --sweep 120 \
|
| 71 |
+
--max-new-tokens 2048 --group-size 4 --prompts-per-step 256 --micro-batch 4 \
|
| 72 |
+
--seed 1223 --save-every 1000 --gsm8k-every 20 --gsm8k-max-new-tokens 1024 \
|
| 73 |
+
--liger-loss --reference-kl-beta 0.05 \
|
| 74 |
+
--gold-mix-lambda 0.5 --gold-loss ce \
|
| 75 |
+
--gold-topk-targets outputs/teacher_trajectories/dolci_combined_top128 \
|
| 76 |
+
--rollout-engine vllm --vllm-gpu 2 --vllm-refresh-every 1 \
|
| 77 |
+
--student-device cuda:1 --teacher-device cuda:0 \
|
| 78 |
+
--out-dir outputs/healed/opd_warm_fixed_keep50 \
|
| 79 |
+
--wandb --wandb-project glean-heal --wandb-run-name opd-warm-fixed-keep50-s1223 \
|
| 80 |
+
> "$LOGDIR/opd_warm_fixed.log" 2>&1
|
| 81 |
+
echo "$(date +%T) chain2: warm OPD exited"
|
healed/warmup_fixed.log
ADDED
|
@@ -0,0 +1,213 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from /home/henry/.netrc.
|
| 2 |
+
wandb: Currently logged in as: hbfreed to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
|
| 3 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 4 |
+
wandb: Run data is saved locally in outputs/healed/keep50_warmup_fixed_s1224/wandb/run-20260802_025702-sep45w2j
|
| 5 |
+
wandb: Run `wandb offline` to turn off syncing.
|
| 6 |
+
wandb: Syncing run warmup-fixed-keep50-s1224
|
| 7 |
+
wandb: ⭐️ View project at https://wandb.ai/hbfreed/glean-heal
|
| 8 |
+
wandb: 🚀 View run at https://wandb.ai/hbfreed/glean-heal/runs/sep45w2j
|
| 9 |
+
|
| 10 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 53 steps/epoch | 150 total steps | student params 3.70B | teacher overlap=False
|
| 11 |
+
{"step": 1, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.21896971870896717, "tokens": 120000, "cumulative_loss_tokens": 120000, "grad_norm": 4.6875, "lr": 6e-06, "finish_rate": 0.907, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.337, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 99.1, "frames": {"chat": 236}, "mem_gb": 15.78, "mem_gb_teacher": 15.78}
|
| 12 |
+
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
|
| 13 |
+
[eval step 1] sample: 'To solve the given system of equations:\n\\[\n\\begin{align*}\na + b &= k, \\\\\nk + m &= p, \\\\\np + a &= r, \\\\\nb + m + r &= 18,\n\\end{align*}\n\\]\nwe need to determine the values'
|
| 14 |
+
{"step": 2, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.27215903437460465, "tokens": 120000, "cumulative_loss_tokens": 240000, "grad_norm": 4.84375, "lr": 9e-06, "finish_rate": 0.781, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.474, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.6, "frames": {"chat": 215}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 15 |
+
{"step": 3, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2780314308715363, "tokens": 120000, "cumulative_loss_tokens": 360000, "grad_norm": 4.09375, "lr": 1.2e-05, "finish_rate": 0.825, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.376, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.6, "frames": {"chat": 217}, "mem_gb": 15.93, "mem_gb_teacher": 15.93}
|
| 16 |
+
{"step": 4, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.21216022065331538, "tokens": 120000, "cumulative_loss_tokens": 480000, "grad_norm": 2.546875, "lr": 1.5e-05, "finish_rate": 0.8, "comp_len": 585.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.366, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.0, "frames": {"chat": 205}, "mem_gb": 15.99, "mem_gb_teacher": 15.99}
|
| 17 |
+
{"step": 5, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.13948054732351253, "tokens": 120000, "cumulative_loss_tokens": 600000, "grad_norm": 1.6484375, "lr": 1.8e-05, "finish_rate": 0.834, "comp_len": 524.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.318, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 94.5, "frames": {"chat": 229}, "mem_gb": 15.96, "mem_gb_teacher": 15.96}
|
| 18 |
+
{"step": 6, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2525411546646928, "tokens": 120000, "cumulative_loss_tokens": 720000, "grad_norm": 2.578125, "lr": 2.1e-05, "finish_rate": 0.812, "comp_len": 538.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.336, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.0, "frames": {"chat": 223}, "mem_gb": 16.03, "mem_gb_teacher": 16.03}
|
| 19 |
+
{"step": 7, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.1408244575532774, "tokens": 120000, "cumulative_loss_tokens": 840000, "grad_norm": 1.171875, "lr": 2.4e-05, "finish_rate": 0.708, "comp_len": 594.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.42, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.3, "frames": {"chat": 202}, "mem_gb": 16.07, "mem_gb_teacher": 16.07}
|
| 20 |
+
{"step": 8, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.16170320059585697, "tokens": 120000, "cumulative_loss_tokens": 960000, "grad_norm": 1.171875, "lr": 2.7000000000000002e-05, "finish_rate": 0.77, "comp_len": 574.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.453, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.6, "frames": {"chat": 209}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 21 |
+
{"step": 9, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.1060452919805112, "tokens": 120000, "cumulative_loss_tokens": 1080000, "grad_norm": 0.703125, "lr": 3e-05, "finish_rate": 0.885, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.397, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.7, "frames": {"chat": 227}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 22 |
+
{"step": 10, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.11166963671234746, "tokens": 120000, "cumulative_loss_tokens": 1200000, "grad_norm": 0.66796875, "lr": 3e-05, "finish_rate": 0.848, "comp_len": 521.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.546, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.5, "frames": {"chat": 230}, "mem_gb": 16.09, "mem_gb_teacher": 16.09}
|
| 23 |
+
[eval step 10] sample: "To solve this system of equations, we need to determine the values of \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\) given the constraints that each letter represents a non-zero digit.\n\nLet's break down the pr"
|
| 24 |
+
{"step": 11, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09883926218959192, "tokens": 120000, "cumulative_loss_tokens": 1320000, "grad_norm": 0.671875, "lr": 3e-05, "finish_rate": 0.879, "comp_len": 519.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.426, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 94.7, "frames": {"chat": 231}, "mem_gb": 15.94, "mem_gb_teacher": 15.94}
|
| 25 |
+
{"step": 12, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09610702018613616, "tokens": 120000, "cumulative_loss_tokens": 1440000, "grad_norm": 0.55078125, "lr": 3e-05, "finish_rate": 0.882, "comp_len": 489.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.246, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 99.3, "frames": {"chat": 245}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 26 |
+
{"step": 13, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09665392311389248, "tokens": 120000, "cumulative_loss_tokens": 1560000, "grad_norm": 0.5703125, "lr": 3e-05, "finish_rate": 0.81, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.375, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.0, "frames": {"chat": 210}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 27 |
+
{"step": 14, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.1129512736000431, "tokens": 120000, "cumulative_loss_tokens": 1680000, "grad_norm": 0.578125, "lr": 3e-05, "finish_rate": 0.758, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.312, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.4, "frames": {"chat": 211}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 28 |
+
{"step": 15, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09338119786353782, "tokens": 120000, "cumulative_loss_tokens": 1800000, "grad_norm": 0.453125, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.413, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.0, "frames": {"chat": 221}, "mem_gb": 16.08, "mem_gb_teacher": 16.08}
|
| 29 |
+
{"step": 16, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08123978671409811, "tokens": 120000, "cumulative_loss_tokens": 1920000, "grad_norm": 0.490234375, "lr": 3e-05, "finish_rate": 0.912, "comp_len": 480.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.366, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 101.9, "frames": {"chat": 250}, "mem_gb": 15.89, "mem_gb_teacher": 15.89}
|
| 30 |
+
{"step": 17, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08966803371421993, "tokens": 120000, "cumulative_loss_tokens": 2040000, "grad_norm": 0.49609375, "lr": 3e-05, "finish_rate": 0.79, "comp_len": 524.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.402, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.6, "frames": {"chat": 229}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 31 |
+
{"step": 18, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06860631760672356, "tokens": 120000, "cumulative_loss_tokens": 2160000, "grad_norm": 0.408203125, "lr": 3e-05, "finish_rate": 0.888, "comp_len": 480.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.479, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 101.4, "frames": {"chat": 250}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 32 |
+
{"step": 19, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08370754941549773, "tokens": 120000, "cumulative_loss_tokens": 2280000, "grad_norm": 0.421875, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 519.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.363, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.2, "frames": {"chat": 231}, "mem_gb": 15.91, "mem_gb_teacher": 15.91}
|
| 33 |
+
{"step": 20, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07473204600410537, "tokens": 120000, "cumulative_loss_tokens": 2400000, "grad_norm": 0.41796875, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.433, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.5, "frames": {"chat": 224}, "mem_gb": 15.96, "mem_gb_teacher": 15.96}
|
| 34 |
+
[eval step 20] sample: 'To solve the system of equations given:\n\n\\[\n\\begin{align*}\na + b &= k \\\\\nk + m &= p \\\\\np + a &= r \\\\\nb + m + r &= 18\n\\end{align*}\n\\]\n\nwe need to determine the values of \\('
|
| 35 |
+
{"step": 21, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08024157820896556, "tokens": 120000, "cumulative_loss_tokens": 2520000, "grad_norm": 0.486328125, "lr": 3e-05, "finish_rate": 0.802, "comp_len": 566.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.329, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.4, "frames": {"chat": 212}, "mem_gb": 16.0, "mem_gb_teacher": 16.0}
|
| 36 |
+
{"step": 22, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0721184289892825, "tokens": 120000, "cumulative_loss_tokens": 2640000, "grad_norm": 0.435546875, "lr": 3e-05, "finish_rate": 0.87, "comp_len": 504.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.376, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 97.3, "frames": {"chat": 238}, "mem_gb": 15.95, "mem_gb_teacher": 15.95}
|
| 37 |
+
{"step": 23, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07248173923180438, "tokens": 120000, "cumulative_loss_tokens": 2760000, "grad_norm": 0.443359375, "lr": 3e-05, "finish_rate": 0.903, "comp_len": 466.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.445, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 103.5, "frames": {"chat": 257}, "mem_gb": 15.83, "mem_gb_teacher": 15.83}
|
| 38 |
+
{"step": 24, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0655906916304181, "tokens": 120000, "cumulative_loss_tokens": 2880000, "grad_norm": 0.36328125, "lr": 3e-05, "finish_rate": 0.868, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.405, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.3, "frames": {"chat": 227}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 39 |
+
{"step": 25, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07533252080177578, "tokens": 120000, "cumulative_loss_tokens": 3000000, "grad_norm": 0.380859375, "lr": 3e-05, "finish_rate": 0.838, "comp_len": 526.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.359, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.6, "frames": {"chat": 228}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 40 |
+
{"step": 26, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07692283792655605, "tokens": 120000, "cumulative_loss_tokens": 3120000, "grad_norm": 0.40625, "lr": 3e-05, "finish_rate": 0.803, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.542, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 97.0, "frames": {"chat": 233}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 41 |
+
{"step": 27, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06803224476923546, "tokens": 120000, "cumulative_loss_tokens": 3240000, "grad_norm": 0.3828125, "lr": 3e-05, "finish_rate": 0.863, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.351, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.2, "frames": {"chat": 233}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 42 |
+
{"step": 28, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.09600000411309302, "tokens": 120000, "cumulative_loss_tokens": 3360000, "grad_norm": 0.46484375, "lr": 3e-05, "finish_rate": 0.731, "comp_len": 609.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.388, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 85.0, "frames": {"chat": 197}, "mem_gb": 16.13, "mem_gb_teacher": 16.13}
|
| 43 |
+
{"step": 29, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0838949200007754, "tokens": 120000, "cumulative_loss_tokens": 3480000, "grad_norm": 0.404296875, "lr": 3e-05, "finish_rate": 0.862, "comp_len": 502.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.384, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.3, "frames": {"chat": 239}, "mem_gb": 15.88, "mem_gb_teacher": 15.88}
|
| 44 |
+
{"step": 30, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.08550032369385784, "tokens": 120000, "cumulative_loss_tokens": 3600000, "grad_norm": 0.640625, "lr": 3e-05, "finish_rate": 0.83, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.302, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.8, "frames": {"chat": 224}, "mem_gb": 15.93, "mem_gb_teacher": 15.93}
|
| 45 |
+
[eval step 30] sample: 'To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to follow these steps:\n\n1. **Understand the Equations:**\n \\[\n \\begin{align*}\n a + b &= k \\\\'
|
| 46 |
+
{"step": 31, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06893708595448794, "tokens": 120000, "cumulative_loss_tokens": 3720000, "grad_norm": 0.3828125, "lr": 3e-05, "finish_rate": 0.788, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.388, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.4, "frames": {"chat": 217}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 47 |
+
{"step": 32, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0662639382578743, "tokens": 120000, "cumulative_loss_tokens": 3840000, "grad_norm": 0.376953125, "lr": 3e-05, "finish_rate": 0.876, "comp_len": 497.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.259, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.4, "frames": {"chat": 241}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 48 |
+
{"step": 33, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06439438750580885, "tokens": 120000, "cumulative_loss_tokens": 3960000, "grad_norm": 0.39453125, "lr": 3e-05, "finish_rate": 0.835, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.407, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.8, "frames": {"chat": 218}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 49 |
+
{"step": 34, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06970151182319968, "tokens": 120000, "cumulative_loss_tokens": 4080000, "grad_norm": 0.353515625, "lr": 3e-05, "finish_rate": 0.767, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.439, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.2, "frames": {"chat": 206}, "mem_gb": 16.03, "mem_gb_teacher": 16.03}
|
| 50 |
+
{"step": 35, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06962556957538861, "tokens": 120000, "cumulative_loss_tokens": 4200000, "grad_norm": 0.37890625, "lr": 3e-05, "finish_rate": 0.845, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.512, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.4, "frames": {"chat": 232}, "mem_gb": 16.07, "mem_gb_teacher": 16.07}
|
| 51 |
+
{"step": 36, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07808773103132843, "tokens": 120000, "cumulative_loss_tokens": 4320000, "grad_norm": 0.419921875, "lr": 3e-05, "finish_rate": 0.771, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.432, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.0, "frames": {"chat": 218}, "mem_gb": 16.09, "mem_gb_teacher": 16.09}
|
| 52 |
+
{"step": 37, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07417992857682208, "tokens": 120000, "cumulative_loss_tokens": 4440000, "grad_norm": 0.376953125, "lr": 3e-05, "finish_rate": 0.779, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.428, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.9, "frames": {"chat": 213}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 53 |
+
{"step": 38, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07201246263841167, "tokens": 120000, "cumulative_loss_tokens": 4560000, "grad_norm": 0.369140625, "lr": 3e-05, "finish_rate": 0.887, "comp_len": 483.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.527, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 100.9, "frames": {"chat": 248}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 54 |
+
{"step": 39, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05988815330729509, "tokens": 120000, "cumulative_loss_tokens": 4680000, "grad_norm": 0.373046875, "lr": 3e-05, "finish_rate": 0.803, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.333, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.1, "frames": {"chat": 218}, "mem_gb": 16.08, "mem_gb_teacher": 16.08}
|
| 55 |
+
{"step": 40, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05963528015368308, "tokens": 120000, "cumulative_loss_tokens": 4800000, "grad_norm": 0.3359375, "lr": 3e-05, "finish_rate": 0.851, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.401, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.5, "frames": {"chat": 221}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 56 |
+
[eval step 40] sample: "To solve the given system of equations, we need to determine the values of \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\) such that each letter represents a non-zero digit. Let's break down the problem step-by"
|
| 57 |
+
{"step": 41, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05816531496203194, "tokens": 120000, "cumulative_loss_tokens": 4920000, "grad_norm": 0.345703125, "lr": 3e-05, "finish_rate": 0.894, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.396, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.1, "frames": {"chat": 236}, "mem_gb": 15.97, "mem_gb_teacher": 15.97}
|
| 58 |
+
{"step": 42, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06005277933338657, "tokens": 120000, "cumulative_loss_tokens": 5040000, "grad_norm": 0.326171875, "lr": 3e-05, "finish_rate": 0.858, "comp_len": 487.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.338, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 100.6, "frames": {"chat": 246}, "mem_gb": 15.89, "mem_gb_teacher": 15.89}
|
| 59 |
+
{"step": 43, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06171362210111692, "tokens": 120000, "cumulative_loss_tokens": 5160000, "grad_norm": 0.35546875, "lr": 3e-05, "finish_rate": 0.838, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.48, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.2, "frames": {"chat": 234}, "mem_gb": 16.14, "mem_gb_teacher": 16.14}
|
| 60 |
+
{"step": 44, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.055975045030827945, "tokens": 120000, "cumulative_loss_tokens": 5280000, "grad_norm": 0.3515625, "lr": 3e-05, "finish_rate": 0.748, "comp_len": 594.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.474, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 85.4, "frames": {"chat": 202}, "mem_gb": 16.03, "mem_gb_teacher": 16.03}
|
| 61 |
+
{"step": 45, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06047188884726105, "tokens": 120000, "cumulative_loss_tokens": 5400000, "grad_norm": 0.3359375, "lr": 3e-05, "finish_rate": 0.811, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.36, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.3, "frames": {"chat": 217}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 62 |
+
{"step": 46, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05655016646341731, "tokens": 120000, "cumulative_loss_tokens": 5520000, "grad_norm": 0.357421875, "lr": 3e-05, "finish_rate": 0.866, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.47, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.3, "frames": {"chat": 224}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 63 |
+
{"step": 47, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0790889122961089, "tokens": 120000, "cumulative_loss_tokens": 5640000, "grad_norm": 0.828125, "lr": 3e-05, "finish_rate": 0.753, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.285, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.5, "frames": {"chat": 215}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 64 |
+
{"step": 48, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05377363468687981, "tokens": 120000, "cumulative_loss_tokens": 5760000, "grad_norm": 0.353515625, "lr": 3e-05, "finish_rate": 0.884, "comp_len": 463.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 104.3, "frames": {"chat": 259}, "mem_gb": 15.97, "mem_gb_teacher": 15.97}
|
| 65 |
+
{"step": 49, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.06014201375305032, "tokens": 120000, "cumulative_loss_tokens": 5880000, "grad_norm": 0.3359375, "lr": 3e-05, "finish_rate": 0.829, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.475, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.9, "frames": {"chat": 210}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 66 |
+
{"step": 50, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.07395202046850076, "tokens": 120000, "cumulative_loss_tokens": 6000000, "grad_norm": 0.416015625, "lr": 3e-05, "finish_rate": 0.77, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.304, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.3, "frames": {"chat": 213}, "mem_gb": 16.09, "mem_gb_teacher": 16.09}
|
| 67 |
+
[eval step 50] sample: "To solve the given system of equations, we need to determine the values of \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\) such that each letter represents a non-zero digit. Let's break down the problem step-by"
|
| 68 |
+
checkpoint snapshot queued -> outputs/healed/keep50_warmup_fixed_s1224/step0050
|
| 69 |
+
{"step": 51, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.05859705059945894, "tokens": 120000, "cumulative_loss_tokens": 6120000, "grad_norm": 0.34765625, "lr": 3e-05, "finish_rate": 0.815, "comp_len": 540.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.453, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.8, "frames": {"chat": 222}, "mem_gb": 16.0, "mem_gb_teacher": 16.0}
|
| 70 |
+
{"step": 52, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0539097297622667, "tokens": 120000, "cumulative_loss_tokens": 6240000, "grad_norm": 0.353515625, "lr": 3e-05, "finish_rate": 0.889, "comp_len": 510.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.439, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.1, "frames": {"chat": 235}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 71 |
+
{"step": 53, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.0594748610290233, "tokens": 120000, "cumulative_loss_tokens": 6360000, "grad_norm": 0.328125, "lr": 3e-05, "finish_rate": 0.798, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.417, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.8, "frames": {"chat": 208}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 72 |
+
{"step": 54, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.045099887475029875, "tokens": 120000, "cumulative_loss_tokens": 6480000, "grad_norm": 0.275390625, "lr": 3e-05, "finish_rate": 0.733, "comp_len": 628.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.413, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 80.2, "frames": {"chat": 191}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 73 |
+
{"step": 55, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03569839329215077, "tokens": 120000, "cumulative_loss_tokens": 6600000, "grad_norm": 0.2451171875, "lr": 3e-05, "finish_rate": 0.845, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.523, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.0, "frames": {"chat": 219}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 74 |
+
{"step": 56, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04039377661425, "tokens": 120000, "cumulative_loss_tokens": 6720000, "grad_norm": 0.302734375, "lr": 3e-05, "finish_rate": 0.778, "comp_len": 579.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.459, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.0, "frames": {"chat": 207}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 75 |
+
{"step": 57, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.055602129854184265, "tokens": 120000, "cumulative_loss_tokens": 6840000, "grad_norm": 0.330078125, "lr": 3e-05, "finish_rate": 0.755, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.449, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.0, "frames": {"chat": 208}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 76 |
+
{"step": 58, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.035877808295966436, "tokens": 120000, "cumulative_loss_tokens": 6960000, "grad_norm": 0.279296875, "lr": 3e-05, "finish_rate": 0.799, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.288, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.8, "frames": {"chat": 219}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 77 |
+
{"step": 59, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03478414489501932, "tokens": 120000, "cumulative_loss_tokens": 7080000, "grad_norm": 0.2578125, "lr": 3e-05, "finish_rate": 0.915, "comp_len": 487.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.329, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 99.7, "frames": {"chat": 246}, "mem_gb": 15.92, "mem_gb_teacher": 15.92}
|
| 78 |
+
{"step": 60, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04739725781680706, "tokens": 120000, "cumulative_loss_tokens": 7200000, "grad_norm": 0.330078125, "lr": 3e-05, "finish_rate": 0.704, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.437, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.5, "frames": {"chat": 206}, "mem_gb": 16.07, "mem_gb_teacher": 16.07}
|
| 79 |
+
[eval step 60] sample: 'To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to determine the values of these variables such that each letter represents a non-zero digit.\n\nThe equations a'
|
| 80 |
+
{"step": 61, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03820183755345643, "tokens": 120000, "cumulative_loss_tokens": 7320000, "grad_norm": 0.275390625, "lr": 3e-05, "finish_rate": 0.876, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.375, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.5, "frames": {"chat": 233}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 81 |
+
{"step": 62, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04388709897000032, "tokens": 120000, "cumulative_loss_tokens": 7440000, "grad_norm": 0.275390625, "lr": 3e-05, "finish_rate": 0.847, "comp_len": 524.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.363, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.8, "frames": {"chat": 229}, "mem_gb": 15.92, "mem_gb_teacher": 15.92}
|
| 82 |
+
{"step": 63, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.032643947703313705, "tokens": 120000, "cumulative_loss_tokens": 7560000, "grad_norm": 0.236328125, "lr": 3e-05, "finish_rate": 0.864, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.285, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.4, "frames": {"chat": 236}, "mem_gb": 15.95, "mem_gb_teacher": 15.95}
|
| 83 |
+
{"step": 64, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04086883016227123, "tokens": 120000, "cumulative_loss_tokens": 7680000, "grad_norm": 0.2451171875, "lr": 3e-05, "finish_rate": 0.87, "comp_len": 502.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.37, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.3, "frames": {"chat": 239}, "mem_gb": 15.84, "mem_gb_teacher": 15.84}
|
| 84 |
+
{"step": 65, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03435394472128246, "tokens": 120000, "cumulative_loss_tokens": 7800000, "grad_norm": 0.2177734375, "lr": 3e-05, "finish_rate": 0.867, "comp_len": 497.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.349, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 99.1, "frames": {"chat": 241}, "mem_gb": 15.96, "mem_gb_teacher": 15.96}
|
| 85 |
+
{"step": 66, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.036759108127855385, "tokens": 120000, "cumulative_loss_tokens": 7920000, "grad_norm": 0.2294921875, "lr": 3e-05, "finish_rate": 0.863, "comp_len": 531.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.44, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.4, "frames": {"chat": 226}, "mem_gb": 15.92, "mem_gb_teacher": 15.92}
|
| 86 |
+
{"step": 67, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.031785604377323765, "tokens": 120000, "cumulative_loss_tokens": 8040000, "grad_norm": 0.224609375, "lr": 3e-05, "finish_rate": 0.893, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.32, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.3, "frames": {"chat": 234}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 87 |
+
{"step": 68, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03207274362700991, "tokens": 120000, "cumulative_loss_tokens": 8160000, "grad_norm": 0.22265625, "lr": 3e-05, "finish_rate": 0.914, "comp_len": 466.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.401, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 102.7, "frames": {"chat": 257}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 88 |
+
{"step": 69, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04908341010484534, "tokens": 120000, "cumulative_loss_tokens": 8280000, "grad_norm": 0.2890625, "lr": 3e-05, "finish_rate": 0.76, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.523, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.3, "frames": {"chat": 208}, "mem_gb": 16.1, "mem_gb_teacher": 16.1}
|
| 89 |
+
{"step": 70, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.043880132612407516, "tokens": 120000, "cumulative_loss_tokens": 8400000, "grad_norm": 0.267578125, "lr": 3e-05, "finish_rate": 0.763, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.522, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.2, "frames": {"chat": 211}, "mem_gb": 16.07, "mem_gb_teacher": 16.07}
|
| 90 |
+
[eval step 70] sample: "To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to ensure that each letter represents a non-zero digit. Let's break down the problem step-by-step and solve it"
|
| 91 |
+
{"step": 71, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04658220293604148, "tokens": 120000, "cumulative_loss_tokens": 8520000, "grad_norm": 0.302734375, "lr": 3e-05, "finish_rate": 0.806, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.407, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.8, "frames": {"chat": 227}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 92 |
+
{"step": 72, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04197514075435077, "tokens": 120000, "cumulative_loss_tokens": 8640000, "grad_norm": 0.275390625, "lr": 3e-05, "finish_rate": 0.796, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.434, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.1, "frames": {"chat": 211}, "mem_gb": 16.03, "mem_gb_teacher": 16.03}
|
| 93 |
+
{"step": 73, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03433373855294194, "tokens": 120000, "cumulative_loss_tokens": 8760000, "grad_norm": 0.248046875, "lr": 3e-05, "finish_rate": 0.861, "comp_len": 504.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.403, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.0, "frames": {"chat": 238}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 94 |
+
{"step": 74, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.035312130354298275, "tokens": 120000, "cumulative_loss_tokens": 8880000, "grad_norm": 0.2255859375, "lr": 3e-05, "finish_rate": 0.835, "comp_len": 506.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.517, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.2, "frames": {"chat": 237}, "mem_gb": 16.08, "mem_gb_teacher": 16.08}
|
| 95 |
+
{"step": 75, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04418459653495035, "tokens": 120000, "cumulative_loss_tokens": 9000000, "grad_norm": 0.265625, "lr": 3e-05, "finish_rate": 0.721, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.339, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.6, "frames": {"chat": 208}, "mem_gb": 16.08, "mem_gb_teacher": 16.08}
|
| 96 |
+
{"step": 76, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03462567985369048, "tokens": 120000, "cumulative_loss_tokens": 9120000, "grad_norm": 0.212890625, "lr": 3e-05, "finish_rate": 0.801, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.588, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.3, "frames": {"chat": 221}, "mem_gb": 16.17, "mem_gb_teacher": 16.17}
|
| 97 |
+
{"step": 77, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.0355419263230792, "tokens": 120000, "cumulative_loss_tokens": 9240000, "grad_norm": 0.244140625, "lr": 3e-05, "finish_rate": 0.853, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.479, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.6, "frames": {"chat": 232}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 98 |
+
{"step": 78, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03847126886160113, "tokens": 120000, "cumulative_loss_tokens": 9360000, "grad_norm": 0.25, "lr": 3e-05, "finish_rate": 0.764, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.43, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.7, "frames": {"chat": 208}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 99 |
+
{"step": 79, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03187043257508582, "tokens": 120000, "cumulative_loss_tokens": 9480000, "grad_norm": 0.232421875, "lr": 3e-05, "finish_rate": 0.837, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 93.2, "frames": {"chat": 227}, "mem_gb": 15.96, "mem_gb_teacher": 15.96}
|
| 100 |
+
{"step": 80, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03652716889477645, "tokens": 120000, "cumulative_loss_tokens": 9600000, "grad_norm": 0.251953125, "lr": 3e-05, "finish_rate": 0.824, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.387, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.2, "frames": {"chat": 221}, "mem_gb": 15.99, "mem_gb_teacher": 15.99}
|
| 101 |
+
[eval step 80] sample: 'To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to find the values of these variables such that each letter represents a non-zero digit.\n\nThe equations are:\n1'
|
| 102 |
+
{"step": 81, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03261745297779174, "tokens": 120000, "cumulative_loss_tokens": 9720000, "grad_norm": 0.2138671875, "lr": 3e-05, "finish_rate": 0.815, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.457, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.5, "frames": {"chat": 232}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 103 |
+
{"step": 82, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03819663266551991, "tokens": 120000, "cumulative_loss_tokens": 9840000, "grad_norm": 0.255859375, "lr": 3e-05, "finish_rate": 0.822, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.423, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.2, "frames": {"chat": 219}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 104 |
+
{"step": 83, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03785421463410991, "tokens": 120000, "cumulative_loss_tokens": 9960000, "grad_norm": 0.2265625, "lr": 3e-05, "finish_rate": 0.713, "comp_len": 615.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.399, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 82.7, "frames": {"chat": 195}, "mem_gb": 16.14, "mem_gb_teacher": 16.14}
|
| 105 |
+
{"step": 84, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03711687127229913, "tokens": 120000, "cumulative_loss_tokens": 10080000, "grad_norm": 0.244140625, "lr": 3e-05, "finish_rate": 0.833, "comp_len": 555.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.503, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.9, "frames": {"chat": 216}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 106 |
+
{"step": 85, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.042023429202785095, "tokens": 120000, "cumulative_loss_tokens": 10200000, "grad_norm": 0.275390625, "lr": 3e-05, "finish_rate": 0.788, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.37, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.7, "frames": {"chat": 208}, "mem_gb": 15.93, "mem_gb_teacher": 15.93}
|
| 107 |
+
{"step": 86, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03288566896258077, "tokens": 120000, "cumulative_loss_tokens": 10320000, "grad_norm": 0.2265625, "lr": 3e-05, "finish_rate": 0.919, "comp_len": 510.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.407, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.6, "frames": {"chat": 235}, "mem_gb": 15.93, "mem_gb_teacher": 15.93}
|
| 108 |
+
{"step": 87, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.033694713056855834, "tokens": 120000, "cumulative_loss_tokens": 10440000, "grad_norm": 0.2578125, "lr": 3e-05, "finish_rate": 0.853, "comp_len": 533.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.391, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.6, "frames": {"chat": 225}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 109 |
+
{"step": 88, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04422600561644261, "tokens": 120000, "cumulative_loss_tokens": 10560000, "grad_norm": 0.2451171875, "lr": 3e-05, "finish_rate": 0.77, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.483, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.2, "frames": {"chat": 213}, "mem_gb": 16.13, "mem_gb_teacher": 16.13}
|
| 110 |
+
{"step": 89, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.029030231156169126, "tokens": 120000, "cumulative_loss_tokens": 10680000, "grad_norm": 0.2255859375, "lr": 3e-05, "finish_rate": 0.922, "comp_len": 466.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.372, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 104.0, "frames": {"chat": 257}, "mem_gb": 15.8, "mem_gb_teacher": 15.8}
|
| 111 |
+
{"step": 90, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.043001266495510934, "tokens": 120000, "cumulative_loss_tokens": 10800000, "grad_norm": 0.2578125, "lr": 3e-05, "finish_rate": 0.792, "comp_len": 566.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.497, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.1, "frames": {"chat": 212}, "mem_gb": 16.07, "mem_gb_teacher": 16.07}
|
| 112 |
+
[eval step 90] sample: 'To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to find the values of these variables such that each letter represents a non-zero digit.\n\nThe equations are:\n\\'
|
| 113 |
+
{"step": 91, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03456530287990657, "tokens": 120000, "cumulative_loss_tokens": 10920000, "grad_norm": 0.263671875, "lr": 3e-05, "finish_rate": 0.833, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.338, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.9, "frames": {"chat": 221}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 114 |
+
{"step": 92, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.030914492412268495, "tokens": 120000, "cumulative_loss_tokens": 11040000, "grad_norm": 0.203125, "lr": 3e-05, "finish_rate": 0.868, "comp_len": 495.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.442, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.2, "frames": {"chat": 242}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 115 |
+
{"step": 93, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.0329031198489829, "tokens": 120000, "cumulative_loss_tokens": 11160000, "grad_norm": 0.2216796875, "lr": 3e-05, "finish_rate": 0.836, "comp_len": 545.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.352, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.5, "frames": {"chat": 220}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 116 |
+
{"step": 94, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.029550562638859263, "tokens": 120000, "cumulative_loss_tokens": 11280000, "grad_norm": 0.2197265625, "lr": 3e-05, "finish_rate": 0.896, "comp_len": 500.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.291, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.4, "frames": {"chat": 240}, "mem_gb": 15.9, "mem_gb_teacher": 15.9}
|
| 117 |
+
{"step": 95, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.0336006456746875, "tokens": 120000, "cumulative_loss_tokens": 11400000, "grad_norm": 0.23046875, "lr": 3e-05, "finish_rate": 0.728, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.359, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.0, "frames": {"chat": 206}, "mem_gb": 16.03, "mem_gb_teacher": 16.03}
|
| 118 |
+
{"step": 96, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04226834708025368, "tokens": 120000, "cumulative_loss_tokens": 11520000, "grad_norm": 0.255859375, "lr": 3e-05, "finish_rate": 0.867, "comp_len": 531.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.402, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.9, "frames": {"chat": 226}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 119 |
+
{"step": 97, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.054896473065484314, "tokens": 120000, "cumulative_loss_tokens": 11640000, "grad_norm": 0.3046875, "lr": 3e-05, "finish_rate": 0.877, "comp_len": 491.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.382, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 99.8, "frames": {"chat": 244}, "mem_gb": 15.83, "mem_gb_teacher": 15.83}
|
| 120 |
+
{"step": 98, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.040829892701484884, "tokens": 120000, "cumulative_loss_tokens": 11760000, "grad_norm": 0.271484375, "lr": 3e-05, "finish_rate": 0.804, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.406, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.6, "frames": {"chat": 224}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 121 |
+
{"step": 99, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.031381215056039705, "tokens": 120000, "cumulative_loss_tokens": 11880000, "grad_norm": 0.240234375, "lr": 3e-05, "finish_rate": 0.923, "comp_len": 442.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.319, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 109.0, "frames": {"chat": 271}, "mem_gb": 15.78, "mem_gb_teacher": 15.78}
|
| 122 |
+
{"step": 100, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.036837965581729075, "tokens": 120000, "cumulative_loss_tokens": 12000000, "grad_norm": 0.265625, "lr": 3e-05, "finish_rate": 0.856, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.362, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.5, "frames": {"chat": 236}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 123 |
+
[eval step 100] sample: "To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to ensure that each letter represents a non-zero digit. Let's break down the problem step-by-step and solve it"
|
| 124 |
+
checkpoint snapshot queued -> outputs/healed/keep50_warmup_fixed_s1224/step0100
|
| 125 |
+
{"step": 101, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03681235469069021, "tokens": 120000, "cumulative_loss_tokens": 12120000, "grad_norm": 0.244140625, "lr": 3e-05, "finish_rate": 0.841, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.306, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.0, "frames": {"chat": 232}, "mem_gb": 15.93, "mem_gb_teacher": 15.93}
|
| 126 |
+
{"step": 102, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03435125927827321, "tokens": 120000, "cumulative_loss_tokens": 12240000, "grad_norm": 0.251953125, "lr": 3e-05, "finish_rate": 0.79, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.392, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.6, "frames": {"chat": 210}, "mem_gb": 15.98, "mem_gb_teacher": 15.98}
|
| 127 |
+
{"step": 103, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.033812837561887375, "tokens": 120000, "cumulative_loss_tokens": 12360000, "grad_norm": 0.275390625, "lr": 3e-05, "finish_rate": 0.811, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.431, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.9, "frames": {"chat": 217}, "mem_gb": 15.95, "mem_gb_teacher": 15.95}
|
| 128 |
+
{"step": 104, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.03568466838332825, "tokens": 120000, "cumulative_loss_tokens": 12480000, "grad_norm": 0.25390625, "lr": 3e-05, "finish_rate": 0.839, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.38, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 92.7, "frames": {"chat": 224}, "mem_gb": 16.07, "mem_gb_teacher": 16.07}
|
| 129 |
+
{"step": 105, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.04380085541328881, "tokens": 120000, "cumulative_loss_tokens": 12600000, "grad_norm": 0.287109375, "lr": 3e-05, "finish_rate": 0.749, "comp_len": 591.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.481, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.5, "frames": {"chat": 203}, "mem_gb": 15.92, "mem_gb_teacher": 15.92}
|
| 130 |
+
{"step": 106, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.0331037232719129, "tokens": 120000, "cumulative_loss_tokens": 12720000, "grad_norm": 0.2197265625, "lr": 3e-05, "finish_rate": 0.887, "comp_len": 502.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.326, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 97.2, "frames": {"chat": 239}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 131 |
+
{"step": 107, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.022136363052297384, "tokens": 120000, "cumulative_loss_tokens": 12840000, "grad_norm": 0.1875, "lr": 3e-05, "finish_rate": 0.902, "comp_len": 472.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.301, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 102.8, "frames": {"chat": 254}, "mem_gb": 15.93, "mem_gb_teacher": 15.93}
|
| 132 |
+
{"step": 108, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02345696447007358, "tokens": 120000, "cumulative_loss_tokens": 12960000, "grad_norm": 0.21875, "lr": 3e-05, "finish_rate": 0.876, "comp_len": 497.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.421, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.5, "frames": {"chat": 241}, "mem_gb": 16.03, "mem_gb_teacher": 16.03}
|
| 133 |
+
{"step": 109, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.03220615579979494, "tokens": 120000, "cumulative_loss_tokens": 13080000, "grad_norm": 0.2294921875, "lr": 3e-05, "finish_rate": 0.746, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.419, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.1, "frames": {"chat": 213}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 134 |
+
{"step": 110, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.028369275209781095, "tokens": 120000, "cumulative_loss_tokens": 13200000, "grad_norm": 0.205078125, "lr": 3e-05, "finish_rate": 0.864, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.641, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.4, "frames": {"chat": 221}, "mem_gb": 16.1, "mem_gb_teacher": 16.1}
|
| 135 |
+
[eval step 110] sample: "To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to ensure that each letter represents a non-zero digit. Let's break down the problem step-by-step and solve it"
|
| 136 |
+
{"step": 111, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.030552633555675855, "tokens": 120000, "cumulative_loss_tokens": 13320000, "grad_norm": 0.201171875, "lr": 3e-05, "finish_rate": 0.745, "comp_len": 612.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.334, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 83.1, "frames": {"chat": 196}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 137 |
+
{"step": 112, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02257079966662762, "tokens": 120000, "cumulative_loss_tokens": 13440000, "grad_norm": 0.1689453125, "lr": 3e-05, "finish_rate": 0.926, "comp_len": 444.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.427, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 108.7, "frames": {"chat": 270}, "mem_gb": 15.86, "mem_gb_teacher": 15.86}
|
| 138 |
+
{"step": 113, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.024793952927171875, "tokens": 120000, "cumulative_loss_tokens": 13560000, "grad_norm": 0.2041015625, "lr": 3e-05, "finish_rate": 0.815, "comp_len": 555.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.327, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.5, "frames": {"chat": 216}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 139 |
+
{"step": 114, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02779970950682958, "tokens": 120000, "cumulative_loss_tokens": 13680000, "grad_norm": 0.1923828125, "lr": 3e-05, "finish_rate": 0.775, "comp_len": 600.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.314, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 83.9, "frames": {"chat": 200}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 140 |
+
{"step": 115, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.025435146312182768, "tokens": 120000, "cumulative_loss_tokens": 13800000, "grad_norm": 0.19921875, "lr": 3e-05, "finish_rate": 0.767, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.406, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.4, "frames": {"chat": 206}, "mem_gb": 15.96, "mem_gb_teacher": 15.96}
|
| 141 |
+
{"step": 116, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.021958818318624982, "tokens": 120000, "cumulative_loss_tokens": 13920000, "grad_norm": 0.1650390625, "lr": 3e-05, "finish_rate": 0.902, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 94.8, "frames": {"chat": 234}, "mem_gb": 15.99, "mem_gb_teacher": 15.99}
|
| 142 |
+
{"step": 117, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.024690080278979926, "tokens": 120000, "cumulative_loss_tokens": 14040000, "grad_norm": 0.171875, "lr": 3e-05, "finish_rate": 0.823, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.325, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.4, "frames": {"chat": 215}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 143 |
+
{"step": 118, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02221767870101612, "tokens": 120000, "cumulative_loss_tokens": 14160000, "grad_norm": 0.2021484375, "lr": 3e-05, "finish_rate": 0.922, "comp_len": 470.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.447, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 101.5, "frames": {"chat": 255}, "mem_gb": 15.99, "mem_gb_teacher": 15.99}
|
| 144 |
+
{"step": 119, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.021592201069470806, "tokens": 120000, "cumulative_loss_tokens": 14280000, "grad_norm": 0.1708984375, "lr": 3e-05, "finish_rate": 0.892, "comp_len": 480.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.377, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 101.8, "frames": {"chat": 250}, "mem_gb": 15.87, "mem_gb_teacher": 15.87}
|
| 145 |
+
{"step": 120, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.022036931684900386, "tokens": 120000, "cumulative_loss_tokens": 14400000, "grad_norm": 0.1826171875, "lr": 3e-05, "finish_rate": 0.884, "comp_len": 495.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.525, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 97.8, "frames": {"chat": 242}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 146 |
+
[eval step 120] sample: 'To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to find the values of these variables such that each letter represents a non-zero digit.\n\nThe equations are:\n\\'
|
| 147 |
+
{"step": 121, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.027385966173838823, "tokens": 120000, "cumulative_loss_tokens": 14520000, "grad_norm": 0.177734375, "lr": 3e-05, "finish_rate": 0.729, "comp_len": 603.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.517, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 85.1, "frames": {"chat": 199}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 148 |
+
{"step": 122, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.037581453007894255, "tokens": 120000, "cumulative_loss_tokens": 14640000, "grad_norm": 0.2138671875, "lr": 3e-05, "finish_rate": 0.784, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.386, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.8, "frames": {"chat": 208}, "mem_gb": 16.08, "mem_gb_teacher": 16.08}
|
| 149 |
+
{"step": 123, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02500725610067602, "tokens": 120000, "cumulative_loss_tokens": 14760000, "grad_norm": 0.212890625, "lr": 3e-05, "finish_rate": 0.764, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.304, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 86.8, "frames": {"chat": 208}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 150 |
+
{"step": 124, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.029994825281358013, "tokens": 120000, "cumulative_loss_tokens": 14880000, "grad_norm": 0.2041015625, "lr": 3e-05, "finish_rate": 0.732, "comp_len": 574.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.473, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.1, "frames": {"chat": 209}, "mem_gb": 16.17, "mem_gb_teacher": 16.17}
|
| 151 |
+
{"step": 125, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.021332296466493667, "tokens": 120000, "cumulative_loss_tokens": 15000000, "grad_norm": 0.1728515625, "lr": 3e-05, "finish_rate": 0.855, "comp_len": 510.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.321, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 97.2, "frames": {"chat": 235}, "mem_gb": 16.0, "mem_gb_teacher": 16.0}
|
| 152 |
+
{"step": 126, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02423879373523717, "tokens": 120000, "cumulative_loss_tokens": 15120000, "grad_norm": 0.2138671875, "lr": 3e-05, "finish_rate": 0.74, "comp_len": 588.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.503, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 85.5, "frames": {"chat": 204}, "mem_gb": 16.0, "mem_gb_teacher": 16.0}
|
| 153 |
+
{"step": 127, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.03143483543585365, "tokens": 120000, "cumulative_loss_tokens": 15240000, "grad_norm": 0.24609375, "lr": 3e-05, "finish_rate": 0.745, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.498, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.5, "frames": {"chat": 208}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 154 |
+
{"step": 128, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.022677327596287555, "tokens": 120000, "cumulative_loss_tokens": 15360000, "grad_norm": 0.1748046875, "lr": 3e-05, "finish_rate": 0.825, "comp_len": 500.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.456, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.6, "frames": {"chat": 240}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 155 |
+
{"step": 129, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02317165856284555, "tokens": 120000, "cumulative_loss_tokens": 15480000, "grad_norm": 0.18359375, "lr": 3e-05, "finish_rate": 0.89, "comp_len": 487.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.425, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 99.3, "frames": {"chat": 246}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 156 |
+
{"step": 130, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02553549518882452, "tokens": 120000, "cumulative_loss_tokens": 15600000, "grad_norm": 0.16796875, "lr": 3e-05, "finish_rate": 0.909, "comp_len": 493.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.299, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 98.1, "frames": {"chat": 243}, "mem_gb": 15.86, "mem_gb_teacher": 15.86}
|
| 157 |
+
[eval step 130] sample: "To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to ensure that each letter represents a non-zero digit. Let's break down the problem step-by-step and solve it"
|
| 158 |
+
{"step": 131, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.03025520235665608, "tokens": 120000, "cumulative_loss_tokens": 15720000, "grad_norm": 0.193359375, "lr": 3e-05, "finish_rate": 0.745, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.449, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.0, "frames": {"chat": 208}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 159 |
+
{"step": 132, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.033440696114464666, "tokens": 120000, "cumulative_loss_tokens": 15840000, "grad_norm": 0.20703125, "lr": 3e-05, "finish_rate": 0.817, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.352, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.4, "frames": {"chat": 219}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 160 |
+
{"step": 133, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.030961406842339785, "tokens": 120000, "cumulative_loss_tokens": 15960000, "grad_norm": 0.205078125, "lr": 3e-05, "finish_rate": 0.782, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.447, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 89.4, "frames": {"chat": 211}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 161 |
+
{"step": 134, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.030365196120288845, "tokens": 120000, "cumulative_loss_tokens": 16080000, "grad_norm": 0.25, "lr": 3e-05, "finish_rate": 0.862, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.283, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.3, "frames": {"chat": 232}, "mem_gb": 16.02, "mem_gb_teacher": 16.02}
|
| 162 |
+
{"step": 135, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.03637079153128434, "tokens": 120000, "cumulative_loss_tokens": 16200000, "grad_norm": 0.201171875, "lr": 3e-05, "finish_rate": 0.804, "comp_len": 560.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.403, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 90.4, "frames": {"chat": 214}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 163 |
+
{"step": 136, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.024788761290698312, "tokens": 120000, "cumulative_loss_tokens": 16320000, "grad_norm": 0.173828125, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 531.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.395, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 94.4, "frames": {"chat": 226}, "mem_gb": 15.94, "mem_gb_teacher": 15.94}
|
| 164 |
+
{"step": 137, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02415202263732596, "tokens": 120000, "cumulative_loss_tokens": 16440000, "grad_norm": 0.171875, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.404, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.7, "frames": {"chat": 210}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 165 |
+
{"step": 138, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.023906889412474507, "tokens": 120000, "cumulative_loss_tokens": 16560000, "grad_norm": 0.1884765625, "lr": 3e-05, "finish_rate": 0.858, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.436, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.6, "frames": {"chat": 218}, "mem_gb": 15.88, "mem_gb_teacher": 15.88}
|
| 166 |
+
{"step": 139, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02281373731412459, "tokens": 120000, "cumulative_loss_tokens": 16680000, "grad_norm": 0.185546875, "lr": 3e-05, "finish_rate": 0.858, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.354, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 96.0, "frames": {"chat": 233}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 167 |
+
{"step": 140, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.029389094779423128, "tokens": 120000, "cumulative_loss_tokens": 16800000, "grad_norm": 0.1962890625, "lr": 3e-05, "finish_rate": 0.786, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.221, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.1, "frames": {"chat": 215}, "mem_gb": 16.05, "mem_gb_teacher": 16.05}
|
| 168 |
+
[eval step 140] sample: 'To solve the given system of equations with the constraint that each letter represents a non-zero digit, we need to find the values of \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\) that satisfy all the equati'
|
| 169 |
+
{"step": 141, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02496639485837271, "tokens": 120000, "cumulative_loss_tokens": 16920000, "grad_norm": 0.1826171875, "lr": 3e-05, "finish_rate": 0.845, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.428, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.0, "frames": {"chat": 233}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 170 |
+
{"step": 142, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.024896287856064736, "tokens": 120000, "cumulative_loss_tokens": 17040000, "grad_norm": 0.2138671875, "lr": 3e-05, "finish_rate": 0.766, "comp_len": 574.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.353, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.5, "frames": {"chat": 209}, "mem_gb": 15.99, "mem_gb_teacher": 15.99}
|
| 171 |
+
{"step": 143, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.0202058710468933, "tokens": 120000, "cumulative_loss_tokens": 17160000, "grad_norm": 0.166015625, "lr": 3e-05, "finish_rate": 0.908, "comp_len": 458.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.308, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 105.8, "frames": {"chat": 262}, "mem_gb": 15.92, "mem_gb_teacher": 15.92}
|
| 172 |
+
{"step": 144, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.0228134301078273, "tokens": 120000, "cumulative_loss_tokens": 17280000, "grad_norm": 0.171875, "lr": 3e-05, "finish_rate": 0.9, "comp_len": 481.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.241, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 101.0, "frames": {"chat": 249}, "mem_gb": 16.01, "mem_gb_teacher": 16.01}
|
| 173 |
+
{"step": 145, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.030403959429240787, "tokens": 120000, "cumulative_loss_tokens": 17400000, "grad_norm": 0.18359375, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.364, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 94.0, "frames": {"chat": 227}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 174 |
+
{"step": 146, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.022969909678919553, "tokens": 120000, "cumulative_loss_tokens": 17520000, "grad_norm": 0.1796875, "lr": 3e-05, "finish_rate": 0.814, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 91.2, "frames": {"chat": 221}, "mem_gb": 16.04, "mem_gb_teacher": 16.04}
|
| 175 |
+
{"step": 147, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.02228280872052225, "tokens": 120000, "cumulative_loss_tokens": 17640000, "grad_norm": 0.171875, "lr": 3e-05, "finish_rate": 0.859, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.473, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.0, "frames": {"chat": 234}, "mem_gb": 16.06, "mem_gb_teacher": 16.06}
|
| 176 |
+
{"step": 148, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.023852225604599032, "tokens": 120000, "cumulative_loss_tokens": 17760000, "grad_norm": 0.212890625, "lr": 3e-05, "finish_rate": 0.817, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.29, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 87.8, "frames": {"chat": 213}, "mem_gb": 16.0, "mem_gb_teacher": 16.0}
|
| 177 |
+
{"step": 149, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.022865247969034438, "tokens": 120000, "cumulative_loss_tokens": 17880000, "grad_norm": 0.1748046875, "lr": 3e-05, "finish_rate": 0.836, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.455, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 88.1, "frames": {"chat": 213}, "mem_gb": 15.94, "mem_gb_teacher": 15.94}
|
| 178 |
+
{"step": 150, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.021284172641811892, "tokens": 120000, "cumulative_loss_tokens": 18000000, "grad_norm": 0.1669921875, "lr": 3e-05, "finish_rate": 0.906, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.392, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 95.1, "frames": {"chat": 234}, "mem_gb": 15.97, "mem_gb_teacher": 15.97}
|
| 179 |
+
[eval step 150] sample: "To solve the given system of equations for \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\), we need to find the values of these variables such that each letter represents a non-zero digit.\n\nLet's break down the"
|
| 180 |
+
checkpoint snapshot queued -> outputs/healed/keep50_warmup_fixed_s1224/step0150
|
| 181 |
+
wandb: updating run metadata
|
| 182 |
+
wandb: uploading output.log; uploading wandb-summary.json; uploading config.yaml
|
| 183 |
+
wandb:
|
| 184 |
+
wandb: Run history:
|
| 185 |
+
wandb: comp_len ▆▃▆▃▄▄▆▃▃▅▆▅▄█▅▄▄▆▅▆▅▅▂▃▄▃▆▅▇▃▁▇▆▄▂▃▅▅▂▅
|
| 186 |
+
wandb: cumulative_loss_tokens ▁▁▁▂▂▂▂▃▃▃▃▄▄▄▄▄▄▄▄▄▅▅▅▆▆▆▆▇▇▇▇▇▇▇▇▇████
|
| 187 |
+
wandb: dropped_truncated ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 188 |
+
wandb: epoch ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▅▅▅▅▅▅▅▅▅▅▅▅▅██████████
|
| 189 |
+
wandb: finish_rate ▅▄▂▃▆▆▅▃▇▅█▆▆▇█▂▄▄█▆▃▅▆▄▅▃▂▇▇▁▂▇█▂▆▄▆▅█▄
|
| 190 |
+
wandb: forward_topk_kl █▆▄▄▃▃▄▂▂▃▂▂▂▂▂▂▂▁▂▂▁▁▂▁▁▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 191 |
+
wandb: grad_norm █▂▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 192 |
+
wandb: lr ▁███████████████████████████████████████
|
| 193 |
+
wandb: mem_gb ▃▆▆▄▂▄▇▆▇▃▆▆▆▅▇▆▅▅▆█▆█▆▅▆▁▄▆▆▅▃▆▅▃▆▆▄▅▆▅
|
| 194 |
+
wandb: mem_gb_teacher ▅▄▆▇▆▂▆▆▆▇▆▅▃█▆▆▆▅▆▃▆▄▂▃▆█▄▄█▁▆▇▂▆▅▅▆▆▆▃
|
| 195 |
+
wandb: +6 ...
|
| 196 |
+
wandb:
|
| 197 |
+
wandb: Run summary:
|
| 198 |
+
wandb: comp_len 512.8
|
| 199 |
+
wandb: cumulative_loss_tokens 18000000
|
| 200 |
+
wandb: dropped_truncated 0
|
| 201 |
+
wandb: epoch 2
|
| 202 |
+
wandb: finish_rate 0.906
|
| 203 |
+
wandb: forward_topk_kl 0.02128
|
| 204 |
+
wandb: grad_norm 0.16699
|
| 205 |
+
wandb: lr 3e-05
|
| 206 |
+
wandb: mem_gb 15.97
|
| 207 |
+
wandb: mem_gb_teacher 15.97
|
| 208 |
+
wandb: +7 ...
|
| 209 |
+
wandb:
|
| 210 |
+
wandb: 🚀 View run warmup-fixed-keep50-s1224 at: https://wandb.ai/hbfreed/glean-heal/runs/sep45w2j
|
| 211 |
+
wandb: ⭐️ View project at: https://wandb.ai/hbfreed/glean-heal
|
| 212 |
+
wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
|
| 213 |
+
wandb: Find logs at: outputs/healed/keep50_warmup_fixed_s1224/wandb/run-20260802_025702-sep45w2j/logs
|
healed/warmup_gate.log
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
expert max|delta| = 1.524e-03
|
| 2 |
+
|
| 3 |
+
Let's break down the problem step by step:
|
| 4 |
+
|
| 5 |
+
1. Natalia sold 48 clips in April.
|
| 6 |
+
2. In May, she sold half as many clips as in April. So, the number of clips sold in May is \( \frac{48}{2} = 24 \).
|
| 7 |
+
|
| 8 |
+
To find the total number of clips sold in both months, we add the number of clips sold in April and May:
|
| 9 |
+
|
| 10 |
+
\[ 48 + 24 = 72 \]
|
| 11 |
+
|
| 12 |
+
Thus, Natalia sold a total of 72 clips in April and May.
|
| 13 |
+
|
| 14 |
+
Let's confirm this with Python code.
|
| 15 |
+
```python
|
| 16 |
+
# Number of clips sold in April
|
| 17 |
+
clips_April = 48
|
| 18 |
+
|
| 19 |
+
# Number of clips sold in May (half of April)
|
| 20 |
+
clips_May = clips_April / 2
|
| 21 |
+
|
| 22 |
+
# Total number of clips sold in April and May
|
| 23 |
+
total_clips = clips_April + clips_May
|
| 24 |
+
print(total_clips)
|
| 25 |
+
|
| 26 |
+
GATE PASSED
|
healed/warmup_keep50.log
ADDED
|
@@ -0,0 +1,213 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from /home/henry/.netrc.
|
| 2 |
+
wandb: Currently logged in as: hbfreed to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
|
| 3 |
+
wandb: Tracking run with wandb version 0.28.0
|
| 4 |
+
wandb: Run data is saved locally in outputs/healed/keep50_offpolicy_warmup_s1224/wandb/run-20260801_230924-9td6b5cn
|
| 5 |
+
wandb: Run `wandb offline` to turn off syncing.
|
| 6 |
+
wandb: Syncing run offpolicy-warmup-keep50-s1224
|
| 7 |
+
wandb: ⭐️ View project at https://wandb.ai/hbfreed/glean-heal
|
| 8 |
+
wandb: 🚀 View run at https://wandb.ai/hbfreed/glean-heal/runs/9td6b5cn
|
| 9 |
+
|
| 10 |
+
12115 cached top-128 chat trajectories / 6,476,634 unique tokens | 53 steps/epoch | 150 total steps | student params 3.70B | teacher overlap=False
|
| 11 |
+
{"step": 1, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.21866693885562322, "tokens": 120000, "cumulative_loss_tokens": 120000, "grad_norm": 0.703125, "lr": 6e-06, "finish_rate": 0.907, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.337, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.4, "frames": {"chat": 236}, "mem_gb": 9.77, "mem_gb_teacher": 9.77}
|
| 12 |
+
The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
|
| 13 |
+
[eval step 1] sample: 'To solve the given system of equations:\n\\[\n\\begin{align*}\na + b &= k, \\\\\nk + m &= p, \\\\\np + a &= r, \\\\\nb + m + r &= 18,\n\\end{align*}\n\\]\nwe need to determine the values'
|
| 14 |
+
{"step": 2, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.27999618121907116, "tokens": 120000, "cumulative_loss_tokens": 240000, "grad_norm": 0.80078125, "lr": 9e-06, "finish_rate": 0.781, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.474, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.1, "frames": {"chat": 215}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 15 |
+
{"step": 3, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3080657049433639, "tokens": 120000, "cumulative_loss_tokens": 360000, "grad_norm": 0.89453125, "lr": 1.2e-05, "finish_rate": 0.825, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.376, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 217}, "mem_gb": 9.83, "mem_gb_teacher": 9.83}
|
| 16 |
+
{"step": 4, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.27968517109975216, "tokens": 120000, "cumulative_loss_tokens": 480000, "grad_norm": 0.80078125, "lr": 1.5e-05, "finish_rate": 0.8, "comp_len": 585.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.366, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.6, "frames": {"chat": 205}, "mem_gb": 9.89, "mem_gb_teacher": 9.89}
|
| 17 |
+
{"step": 5, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2137425679458926, "tokens": 120000, "cumulative_loss_tokens": 600000, "grad_norm": 0.62890625, "lr": 1.8e-05, "finish_rate": 0.834, "comp_len": 524.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.318, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 229}, "mem_gb": 9.86, "mem_gb_teacher": 9.86}
|
| 18 |
+
{"step": 6, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.34967619865822297, "tokens": 120000, "cumulative_loss_tokens": 720000, "grad_norm": 1.3125, "lr": 2.1e-05, "finish_rate": 0.812, "comp_len": 538.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.336, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 223}, "mem_gb": 9.93, "mem_gb_teacher": 9.93}
|
| 19 |
+
{"step": 7, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.23986013823635877, "tokens": 120000, "cumulative_loss_tokens": 840000, "grad_norm": 0.5546875, "lr": 2.4e-05, "finish_rate": 0.708, "comp_len": 594.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.42, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.6, "frames": {"chat": 202}, "mem_gb": 9.97, "mem_gb_teacher": 9.97}
|
| 20 |
+
{"step": 8, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3001840955584, "tokens": 120000, "cumulative_loss_tokens": 960000, "grad_norm": 0.78515625, "lr": 2.7000000000000002e-05, "finish_rate": 0.77, "comp_len": 574.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.453, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 209}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 21 |
+
{"step": 9, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.21187542014177888, "tokens": 120000, "cumulative_loss_tokens": 1080000, "grad_norm": 0.57421875, "lr": 3e-05, "finish_rate": 0.885, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.397, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 227}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 22 |
+
{"step": 10, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.21670206268125525, "tokens": 120000, "cumulative_loss_tokens": 1200000, "grad_norm": 0.6328125, "lr": 3e-05, "finish_rate": 0.848, "comp_len": 521.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.546, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.0, "frames": {"chat": 230}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 23 |
+
[eval step 10] sample: "To solve this problem, we need to find the values of \\(a\\), \\(b\\), \\(k\\), \\(m\\), and \\(p\\) that satisfy the given equations. Let's break down the problem step-by-step:\n\n1. **Understand the Equations:*"
|
| 24 |
+
{"step": 11, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.21374244357372324, "tokens": 120000, "cumulative_loss_tokens": 1320000, "grad_norm": 0.52734375, "lr": 3e-05, "finish_rate": 0.879, "comp_len": 519.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.426, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 26.0, "frames": {"chat": 231}, "mem_gb": 9.84, "mem_gb_teacher": 9.84}
|
| 25 |
+
{"step": 12, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.23642759951651096, "tokens": 120000, "cumulative_loss_tokens": 1440000, "grad_norm": 0.625, "lr": 3e-05, "finish_rate": 0.882, "comp_len": 489.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.246, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 245}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 26 |
+
{"step": 13, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2684279385884603, "tokens": 120000, "cumulative_loss_tokens": 1560000, "grad_norm": 0.73828125, "lr": 3e-05, "finish_rate": 0.81, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.375, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.7, "frames": {"chat": 210}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 27 |
+
{"step": 14, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2720188724226008, "tokens": 120000, "cumulative_loss_tokens": 1680000, "grad_norm": 0.69140625, "lr": 3e-05, "finish_rate": 0.758, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.312, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 211}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 28 |
+
{"step": 15, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2650659183566769, "tokens": 120000, "cumulative_loss_tokens": 1800000, "grad_norm": 0.56640625, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.413, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.1, "frames": {"chat": 221}, "mem_gb": 9.98, "mem_gb_teacher": 9.98}
|
| 29 |
+
{"step": 16, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.22639379921114694, "tokens": 120000, "cumulative_loss_tokens": 1920000, "grad_norm": 0.609375, "lr": 3e-05, "finish_rate": 0.912, "comp_len": 480.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.366, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.1, "frames": {"chat": 250}, "mem_gb": 9.79, "mem_gb_teacher": 9.79}
|
| 30 |
+
{"step": 17, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2573891951084137, "tokens": 120000, "cumulative_loss_tokens": 2040000, "grad_norm": 0.796875, "lr": 3e-05, "finish_rate": 0.79, "comp_len": 524.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.402, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 26.9, "frames": {"chat": 229}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 31 |
+
{"step": 18, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.22218937695200244, "tokens": 120000, "cumulative_loss_tokens": 2160000, "grad_norm": 0.77734375, "lr": 3e-05, "finish_rate": 0.888, "comp_len": 480.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.479, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.7, "frames": {"chat": 250}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 32 |
+
{"step": 19, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.33289732446968556, "tokens": 120000, "cumulative_loss_tokens": 2280000, "grad_norm": 2.546875, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 519.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.363, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.6, "frames": {"chat": 231}, "mem_gb": 9.81, "mem_gb_teacher": 9.81}
|
| 33 |
+
{"step": 20, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.327336692000553, "tokens": 120000, "cumulative_loss_tokens": 2400000, "grad_norm": 1.3984375, "lr": 3e-05, "finish_rate": 0.844, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.433, "t_data_s": 0.1, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 224}, "mem_gb": 9.86, "mem_gb_teacher": 9.86}
|
| 34 |
+
[eval step 20] sample: '```python\ndef f(a, b, c, d, e, f, g, h):\n ax + by + cz + ey + fx + gy + hz = 0\n ```\n\nWe need to find the values of \\(a\\), \\(b\\), \\(c'
|
| 35 |
+
{"step": 21, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.33612352709385257, "tokens": 120000, "cumulative_loss_tokens": 2520000, "grad_norm": 1.640625, "lr": 3e-05, "finish_rate": 0.802, "comp_len": 566.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.329, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 212}, "mem_gb": 9.9, "mem_gb_teacher": 9.9}
|
| 36 |
+
{"step": 22, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2883151387684047, "tokens": 120000, "cumulative_loss_tokens": 2640000, "grad_norm": 1.3984375, "lr": 3e-05, "finish_rate": 0.87, "comp_len": 504.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.376, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.9, "frames": {"chat": 238}, "mem_gb": 9.85, "mem_gb_teacher": 9.85}
|
| 37 |
+
{"step": 23, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.25279294178610046, "tokens": 120000, "cumulative_loss_tokens": 2760000, "grad_norm": 1.3828125, "lr": 3e-05, "finish_rate": 0.903, "comp_len": 466.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.445, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.9, "frames": {"chat": 257}, "mem_gb": 9.73, "mem_gb_teacher": 9.73}
|
| 38 |
+
{"step": 24, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.2615377183983723, "tokens": 120000, "cumulative_loss_tokens": 2880000, "grad_norm": 1.5625, "lr": 3e-05, "finish_rate": 0.868, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.405, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 227}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 39 |
+
{"step": 25, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.32016109869256615, "tokens": 120000, "cumulative_loss_tokens": 3000000, "grad_norm": 2.546875, "lr": 3e-05, "finish_rate": 0.838, "comp_len": 526.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.359, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 228}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 40 |
+
{"step": 26, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.34886745701755084, "tokens": 120000, "cumulative_loss_tokens": 3120000, "grad_norm": 2.0625, "lr": 3e-05, "finish_rate": 0.803, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.542, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.1, "frames": {"chat": 233}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 41 |
+
{"step": 27, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3173991178593288, "tokens": 120000, "cumulative_loss_tokens": 3240000, "grad_norm": 2.671875, "lr": 3e-05, "finish_rate": 0.863, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.351, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 233}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 42 |
+
{"step": 28, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3661775833528489, "tokens": 120000, "cumulative_loss_tokens": 3360000, "grad_norm": 2.984375, "lr": 3e-05, "finish_rate": 0.731, "comp_len": 609.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.388, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 197}, "mem_gb": 10.03, "mem_gb_teacher": 10.03}
|
| 43 |
+
{"step": 29, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.36429248579877116, "tokens": 120000, "cumulative_loss_tokens": 3480000, "grad_norm": 5.625, "lr": 3e-05, "finish_rate": 0.862, "comp_len": 502.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.384, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.0, "frames": {"chat": 239}, "mem_gb": 9.79, "mem_gb_teacher": 9.79}
|
| 44 |
+
{"step": 30, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3706551998923222, "tokens": 120000, "cumulative_loss_tokens": 3600000, "grad_norm": 4.34375, "lr": 3e-05, "finish_rate": 0.83, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.302, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.1, "frames": {"chat": 224}, "mem_gb": 9.83, "mem_gb_teacher": 9.83}
|
| 45 |
+
[eval step 30] sample: 'To solve the problem, we need to determine the value of \\( p \\) given the equations:\n\n1. \\( a + b = k \\)\n2. \\( k + m = p \\)\n3. \\( p + a = r \\)\n4. \\( b + m + r ='
|
| 46 |
+
{"step": 31, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.35791126018886765, "tokens": 120000, "cumulative_loss_tokens": 3720000, "grad_norm": 2.03125, "lr": 3e-05, "finish_rate": 0.788, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.388, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 217}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 47 |
+
{"step": 32, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3755841711225609, "tokens": 120000, "cumulative_loss_tokens": 3840000, "grad_norm": 2.3125, "lr": 3e-05, "finish_rate": 0.876, "comp_len": 497.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.259, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.2, "frames": {"chat": 241}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 48 |
+
{"step": 33, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3561015821622064, "tokens": 120000, "cumulative_loss_tokens": 3960000, "grad_norm": 2.359375, "lr": 3e-05, "finish_rate": 0.835, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.407, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 218}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 49 |
+
{"step": 34, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.38959850126380724, "tokens": 120000, "cumulative_loss_tokens": 4080000, "grad_norm": 2.125, "lr": 3e-05, "finish_rate": 0.767, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.439, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 206}, "mem_gb": 9.93, "mem_gb_teacher": 9.93}
|
| 50 |
+
{"step": 35, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3970217802577963, "tokens": 120000, "cumulative_loss_tokens": 4200000, "grad_norm": 2.734375, "lr": 3e-05, "finish_rate": 0.845, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.512, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.0, "frames": {"chat": 232}, "mem_gb": 9.97, "mem_gb_teacher": 9.97}
|
| 51 |
+
{"step": 36, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.4204790102675557, "tokens": 120000, "cumulative_loss_tokens": 4320000, "grad_norm": 1.796875, "lr": 3e-05, "finish_rate": 0.771, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.432, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.6, "frames": {"chat": 218}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 52 |
+
{"step": 37, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.40933242611338694, "tokens": 120000, "cumulative_loss_tokens": 4440000, "grad_norm": 1.6015625, "lr": 3e-05, "finish_rate": 0.779, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.428, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.9, "frames": {"chat": 213}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 53 |
+
{"step": 38, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3901712652951479, "tokens": 120000, "cumulative_loss_tokens": 4560000, "grad_norm": 2.640625, "lr": 3e-05, "finish_rate": 0.887, "comp_len": 483.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.527, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.5, "frames": {"chat": 248}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 54 |
+
{"step": 39, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.3685633979354054, "tokens": 120000, "cumulative_loss_tokens": 4680000, "grad_norm": 1.921875, "lr": 3e-05, "finish_rate": 0.803, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.333, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.2, "frames": {"chat": 218}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 55 |
+
{"step": 40, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.39544522463083265, "tokens": 120000, "cumulative_loss_tokens": 4800000, "grad_norm": 2.3125, "lr": 3e-05, "finish_rate": 0.851, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.401, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 221}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 56 |
+
[eval step 40] sample: "To solve the problem, we need to determine the value of \\(p\\) given the constraints. Let's break down the problem step-by-step:\n\n1. **Define Variables:**\n - Let \\(d\\) be the digit \\(0, 1, 2, \\ldots,"
|
| 57 |
+
{"step": 41, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.38834569306795796, "tokens": 120000, "cumulative_loss_tokens": 4920000, "grad_norm": 1.640625, "lr": 3e-05, "finish_rate": 0.894, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.396, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 236}, "mem_gb": 9.87, "mem_gb_teacher": 9.87}
|
| 58 |
+
{"step": 42, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.40595541520963113, "tokens": 120000, "cumulative_loss_tokens": 5040000, "grad_norm": 2.390625, "lr": 3e-05, "finish_rate": 0.858, "comp_len": 487.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.338, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.6, "frames": {"chat": 246}, "mem_gb": 9.79, "mem_gb_teacher": 9.79}
|
| 59 |
+
{"step": 43, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.4013322958761205, "tokens": 120000, "cumulative_loss_tokens": 5160000, "grad_norm": 2.703125, "lr": 3e-05, "finish_rate": 0.838, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.48, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.9, "frames": {"chat": 234}, "mem_gb": 10.05, "mem_gb_teacher": 10.05}
|
| 60 |
+
{"step": 44, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.41921593125065165, "tokens": 120000, "cumulative_loss_tokens": 5280000, "grad_norm": 2.984375, "lr": 3e-05, "finish_rate": 0.748, "comp_len": 594.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.474, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.7, "frames": {"chat": 202}, "mem_gb": 9.93, "mem_gb_teacher": 9.93}
|
| 61 |
+
{"step": 45, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.45117179917966327, "tokens": 120000, "cumulative_loss_tokens": 5400000, "grad_norm": 1.953125, "lr": 3e-05, "finish_rate": 0.811, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.36, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.2, "frames": {"chat": 217}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 62 |
+
{"step": 46, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.45246317840516564, "tokens": 120000, "cumulative_loss_tokens": 5520000, "grad_norm": 4.0625, "lr": 3e-05, "finish_rate": 0.866, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.47, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 224}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 63 |
+
{"step": 47, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.49074055876086153, "tokens": 120000, "cumulative_loss_tokens": 5640000, "grad_norm": 2.265625, "lr": 3e-05, "finish_rate": 0.753, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.285, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.2, "frames": {"chat": 215}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 64 |
+
{"step": 48, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.502812573158741, "tokens": 120000, "cumulative_loss_tokens": 5760000, "grad_norm": 4.78125, "lr": 3e-05, "finish_rate": 0.884, "comp_len": 463.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.6, "frames": {"chat": 259}, "mem_gb": 9.87, "mem_gb_teacher": 9.87}
|
| 65 |
+
{"step": 49, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.4940076053115229, "tokens": 120000, "cumulative_loss_tokens": 5880000, "grad_norm": 2.875, "lr": 3e-05, "finish_rate": 0.829, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.475, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.5, "frames": {"chat": 210}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 66 |
+
{"step": 50, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.47275001460264127, "tokens": 120000, "cumulative_loss_tokens": 6000000, "grad_norm": 3.296875, "lr": 3e-05, "finish_rate": 0.77, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.304, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 213}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 67 |
+
[eval step 50] sample: 'To solve the problem, we need to determine the values of \\(p\\), \\(k\\), \\(r\\), and \\(m\\).\n\nGiven:\n1. \\(a + b = k\\)\n2. \\(k + m = p\\)\n3. \\(p + a = r\\)\n'
|
| 68 |
+
checkpoint snapshot queued -> outputs/healed/keep50_offpolicy_warmup_s1224/step0050
|
| 69 |
+
{"step": 51, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.4224179199380179, "tokens": 120000, "cumulative_loss_tokens": 6120000, "grad_norm": 1.75, "lr": 3e-05, "finish_rate": 0.815, "comp_len": 540.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.453, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.1, "frames": {"chat": 222}, "mem_gb": 9.9, "mem_gb_teacher": 9.9}
|
| 70 |
+
{"step": 52, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.4378351664955417, "tokens": 120000, "cumulative_loss_tokens": 6240000, "grad_norm": 2.421875, "lr": 3e-05, "finish_rate": 0.889, "comp_len": 510.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.439, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 235}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 71 |
+
{"step": 53, "epoch": 0, "training_mode": "off-policy", "forward_topk_kl": 0.44709739099716145, "tokens": 120000, "cumulative_loss_tokens": 6360000, "grad_norm": 6.625, "lr": 3e-05, "finish_rate": 0.798, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.417, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.4, "frames": {"chat": 208}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 72 |
+
{"step": 54, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4153756284924845, "tokens": 120000, "cumulative_loss_tokens": 6480000, "grad_norm": 5.4375, "lr": 3e-05, "finish_rate": 0.733, "comp_len": 628.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.413, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 23.5, "frames": {"chat": 191}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 73 |
+
{"step": 55, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.40591654521947107, "tokens": 120000, "cumulative_loss_tokens": 6600000, "grad_norm": 5.75, "lr": 3e-05, "finish_rate": 0.845, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.523, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.1, "frames": {"chat": 219}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 74 |
+
{"step": 56, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.43598461368133623, "tokens": 120000, "cumulative_loss_tokens": 6720000, "grad_norm": 7.0, "lr": 3e-05, "finish_rate": 0.778, "comp_len": 579.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.459, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.8, "frames": {"chat": 207}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 75 |
+
{"step": 57, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4643517450052003, "tokens": 120000, "cumulative_loss_tokens": 6840000, "grad_norm": 5.53125, "lr": 3e-05, "finish_rate": 0.755, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.449, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 208}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 76 |
+
{"step": 58, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.41939549018144606, "tokens": 120000, "cumulative_loss_tokens": 6960000, "grad_norm": 26.125, "lr": 3e-05, "finish_rate": 0.799, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.288, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 219}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 77 |
+
{"step": 59, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.44048424391622343, "tokens": 120000, "cumulative_loss_tokens": 7080000, "grad_norm": 58.5, "lr": 3e-05, "finish_rate": 0.915, "comp_len": 487.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.329, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.8, "frames": {"chat": 246}, "mem_gb": 9.82, "mem_gb_teacher": 9.82}
|
| 78 |
+
{"step": 60, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4594272028216471, "tokens": 120000, "cumulative_loss_tokens": 7200000, "grad_norm": 46.0, "lr": 3e-05, "finish_rate": 0.704, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.437, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 206}, "mem_gb": 9.97, "mem_gb_teacher": 9.97}
|
| 79 |
+
[eval step 60] sample: "To solve this problem, we need to determine the values of \\(p\\), \\(k\\), and \\(r\\) based on the given equations. Here's the step-by-step approach:\n\n1. **Understand the Given Equations:**\n \\[\n \\begi"
|
| 80 |
+
{"step": 61, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4421705829419196, "tokens": 120000, "cumulative_loss_tokens": 7320000, "grad_norm": 5.1875, "lr": 3e-05, "finish_rate": 0.876, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.375, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.2, "frames": {"chat": 233}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 81 |
+
{"step": 62, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.5114135434468587, "tokens": 120000, "cumulative_loss_tokens": 7440000, "grad_norm": 20.375, "lr": 3e-05, "finish_rate": 0.847, "comp_len": 524.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.363, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 229}, "mem_gb": 9.82, "mem_gb_teacher": 9.82}
|
| 82 |
+
{"step": 63, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4925492258039614, "tokens": 120000, "cumulative_loss_tokens": 7560000, "grad_norm": 22.0, "lr": 3e-05, "finish_rate": 0.864, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.285, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 236}, "mem_gb": 9.85, "mem_gb_teacher": 9.85}
|
| 83 |
+
{"step": 64, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4923259206386904, "tokens": 120000, "cumulative_loss_tokens": 7680000, "grad_norm": 21.875, "lr": 3e-05, "finish_rate": 0.87, "comp_len": 502.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.37, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.0, "frames": {"chat": 239}, "mem_gb": 9.74, "mem_gb_teacher": 9.74}
|
| 84 |
+
{"step": 65, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.41652837800706427, "tokens": 120000, "cumulative_loss_tokens": 7800000, "grad_norm": 8.875, "lr": 3e-05, "finish_rate": 0.867, "comp_len": 497.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.349, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.8, "frames": {"chat": 241}, "mem_gb": 9.86, "mem_gb_teacher": 9.86}
|
| 85 |
+
{"step": 66, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3965861890381823, "tokens": 120000, "cumulative_loss_tokens": 7920000, "grad_norm": 3.484375, "lr": 3e-05, "finish_rate": 0.863, "comp_len": 531.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.44, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.1, "frames": {"chat": 226}, "mem_gb": 9.82, "mem_gb_teacher": 9.82}
|
| 86 |
+
{"step": 67, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.36972922986969353, "tokens": 120000, "cumulative_loss_tokens": 8040000, "grad_norm": 17.0, "lr": 3e-05, "finish_rate": 0.893, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.32, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.0, "frames": {"chat": 234}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 87 |
+
{"step": 68, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.374694859992216, "tokens": 120000, "cumulative_loss_tokens": 8160000, "grad_norm": 21.125, "lr": 3e-05, "finish_rate": 0.914, "comp_len": 466.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.401, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.2, "frames": {"chat": 257}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 88 |
+
{"step": 69, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4051088455612461, "tokens": 120000, "cumulative_loss_tokens": 8280000, "grad_norm": 7.3125, "lr": 3e-05, "finish_rate": 0.76, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.523, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.1, "frames": {"chat": 208}, "mem_gb": 10.0, "mem_gb_teacher": 10.0}
|
| 89 |
+
{"step": 70, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4079768711109956, "tokens": 120000, "cumulative_loss_tokens": 8400000, "grad_norm": 2.046875, "lr": 3e-05, "finish_rate": 0.763, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.522, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.0, "frames": {"chat": 211}, "mem_gb": 9.97, "mem_gb_teacher": 9.97}
|
| 90 |
+
[eval step 70] sample: 'To determine the value of \\(p\\), we need to follow the steps outlined in the the problem:\n\n1. **Understand the Problem:**\n - \\(a + b = k\\)\n - \\(k + m = p\\)\n - \\(p + a = r\\)\n -'
|
| 91 |
+
{"step": 71, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3891906266813477, "tokens": 120000, "cumulative_loss_tokens": 8520000, "grad_norm": 3.484375, "lr": 3e-05, "finish_rate": 0.806, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.407, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.1, "frames": {"chat": 227}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 92 |
+
{"step": 72, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.4033234915149709, "tokens": 120000, "cumulative_loss_tokens": 8640000, "grad_norm": 5.03125, "lr": 3e-05, "finish_rate": 0.796, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.434, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.2, "frames": {"chat": 211}, "mem_gb": 9.93, "mem_gb_teacher": 9.93}
|
| 93 |
+
{"step": 73, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3784339854914695, "tokens": 120000, "cumulative_loss_tokens": 8760000, "grad_norm": 4.0, "lr": 3e-05, "finish_rate": 0.861, "comp_len": 504.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.403, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.6, "frames": {"chat": 238}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 94 |
+
{"step": 74, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.37151155275255443, "tokens": 120000, "cumulative_loss_tokens": 8880000, "grad_norm": 1.3515625, "lr": 3e-05, "finish_rate": 0.835, "comp_len": 506.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.517, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.8, "frames": {"chat": 237}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 95 |
+
{"step": 75, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.40700901261599115, "tokens": 120000, "cumulative_loss_tokens": 9000000, "grad_norm": 7.09375, "lr": 3e-05, "finish_rate": 0.721, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.339, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.5, "frames": {"chat": 208}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 96 |
+
{"step": 76, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3612343382894993, "tokens": 120000, "cumulative_loss_tokens": 9120000, "grad_norm": 6.28125, "lr": 3e-05, "finish_rate": 0.801, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.588, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 221}, "mem_gb": 10.07, "mem_gb_teacher": 10.07}
|
| 97 |
+
{"step": 77, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3821119113404304, "tokens": 120000, "cumulative_loss_tokens": 9240000, "grad_norm": 6.90625, "lr": 3e-05, "finish_rate": 0.853, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.479, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.9, "frames": {"chat": 232}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 98 |
+
{"step": 78, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3988335593829552, "tokens": 120000, "cumulative_loss_tokens": 9360000, "grad_norm": 1.796875, "lr": 3e-05, "finish_rate": 0.764, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.43, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 208}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 99 |
+
{"step": 79, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.36860200558168194, "tokens": 120000, "cumulative_loss_tokens": 9480000, "grad_norm": 3.09375, "lr": 3e-05, "finish_rate": 0.837, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.7, "frames": {"chat": 227}, "mem_gb": 9.86, "mem_gb_teacher": 9.86}
|
| 100 |
+
{"step": 80, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.39240696791845064, "tokens": 120000, "cumulative_loss_tokens": 9600000, "grad_norm": 1.9453125, "lr": 3e-05, "finish_rate": 0.824, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.387, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 221}, "mem_gb": 9.89, "mem_gb_teacher": 9.89}
|
| 101 |
+
[eval step 80] sample: "To solve this problem, we need to determine the values of \\(p\\), \\(r\\), and \\(m\\) based on the given equations. Here's the step-by-step approach:\n\n1. **Understand the Given Equations:**\n \\[\n \\begi"
|
| 102 |
+
{"step": 81, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.38983683857706686, "tokens": 120000, "cumulative_loss_tokens": 9720000, "grad_norm": 1.796875, "lr": 3e-05, "finish_rate": 0.815, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.457, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 232}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 103 |
+
{"step": 82, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3839597153416524, "tokens": 120000, "cumulative_loss_tokens": 9840000, "grad_norm": 1.390625, "lr": 3e-05, "finish_rate": 0.822, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.423, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 219}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 104 |
+
{"step": 83, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.40005449274579685, "tokens": 120000, "cumulative_loss_tokens": 9960000, "grad_norm": 1.015625, "lr": 3e-05, "finish_rate": 0.713, "comp_len": 615.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.399, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.8, "frames": {"chat": 195}, "mem_gb": 10.05, "mem_gb_teacher": 10.05}
|
| 105 |
+
{"step": 84, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.37729036068630717, "tokens": 120000, "cumulative_loss_tokens": 10080000, "grad_norm": 2.421875, "lr": 3e-05, "finish_rate": 0.833, "comp_len": 555.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.503, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 216}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 106 |
+
{"step": 85, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.39155043416718643, "tokens": 120000, "cumulative_loss_tokens": 10200000, "grad_norm": 1.640625, "lr": 3e-05, "finish_rate": 0.788, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.37, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 208}, "mem_gb": 9.84, "mem_gb_teacher": 9.84}
|
| 107 |
+
{"step": 86, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3371589448125412, "tokens": 120000, "cumulative_loss_tokens": 10320000, "grad_norm": 1.625, "lr": 3e-05, "finish_rate": 0.919, "comp_len": 510.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.407, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 235}, "mem_gb": 9.83, "mem_gb_teacher": 9.83}
|
| 108 |
+
{"step": 87, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3228179054065297, "tokens": 120000, "cumulative_loss_tokens": 10440000, "grad_norm": 1.015625, "lr": 3e-05, "finish_rate": 0.853, "comp_len": 533.3, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.391, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 225}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 109 |
+
{"step": 88, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3611420020165543, "tokens": 120000, "cumulative_loss_tokens": 10560000, "grad_norm": 2.078125, "lr": 3e-05, "finish_rate": 0.77, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.483, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 213}, "mem_gb": 10.03, "mem_gb_teacher": 10.03}
|
| 110 |
+
{"step": 89, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3108938364227613, "tokens": 120000, "cumulative_loss_tokens": 10680000, "grad_norm": 1.25, "lr": 3e-05, "finish_rate": 0.922, "comp_len": 466.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.372, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.4, "frames": {"chat": 257}, "mem_gb": 9.71, "mem_gb_teacher": 9.71}
|
| 111 |
+
{"step": 90, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3567947539317111, "tokens": 120000, "cumulative_loss_tokens": 10800000, "grad_norm": 2.515625, "lr": 3e-05, "finish_rate": 0.792, "comp_len": 566.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.497, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.9, "frames": {"chat": 212}, "mem_gb": 9.98, "mem_gb_teacher": 9.98}
|
| 112 |
+
[eval step 90] sample: 'To determine the value of \\( p \\), we need to follow the steps outlined in thepy:\n\n1. **Understand the Problem:**\n - \\( p \\) is the value of \\( k \\) when \\( k + m = 18 \\).\n - \\( k \\) is the value'
|
| 113 |
+
{"step": 91, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.35618535781440636, "tokens": 120000, "cumulative_loss_tokens": 10920000, "grad_norm": 2.65625, "lr": 3e-05, "finish_rate": 0.833, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.338, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.2, "frames": {"chat": 221}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 114 |
+
{"step": 92, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3354658261674146, "tokens": 120000, "cumulative_loss_tokens": 11040000, "grad_norm": 2.390625, "lr": 3e-05, "finish_rate": 0.868, "comp_len": 495.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.442, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.0, "frames": {"chat": 242}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 115 |
+
{"step": 93, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3363398057249685, "tokens": 120000, "cumulative_loss_tokens": 11160000, "grad_norm": 1.53125, "lr": 3e-05, "finish_rate": 0.836, "comp_len": 545.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.352, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.6, "frames": {"chat": 220}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 116 |
+
{"step": 94, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.30306674740935363, "tokens": 120000, "cumulative_loss_tokens": 11280000, "grad_norm": 0.7734375, "lr": 3e-05, "finish_rate": 0.896, "comp_len": 500.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.291, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 240}, "mem_gb": 9.81, "mem_gb_teacher": 9.81}
|
| 117 |
+
{"step": 95, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.29799054561704397, "tokens": 120000, "cumulative_loss_tokens": 11400000, "grad_norm": 1.40625, "lr": 3e-05, "finish_rate": 0.728, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.359, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.8, "frames": {"chat": 206}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 118 |
+
{"step": 96, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3275977665552249, "tokens": 120000, "cumulative_loss_tokens": 11520000, "grad_norm": 1.4921875, "lr": 3e-05, "finish_rate": 0.867, "comp_len": 531.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.402, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.6, "frames": {"chat": 226}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 119 |
+
{"step": 97, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.34486291259291274, "tokens": 120000, "cumulative_loss_tokens": 11640000, "grad_norm": 1.25, "lr": 3e-05, "finish_rate": 0.877, "comp_len": 491.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.382, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.8, "frames": {"chat": 244}, "mem_gb": 9.74, "mem_gb_teacher": 9.74}
|
| 120 |
+
{"step": 98, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.31863660610305766, "tokens": 120000, "cumulative_loss_tokens": 11760000, "grad_norm": 1.09375, "lr": 3e-05, "finish_rate": 0.804, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.406, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.9, "frames": {"chat": 224}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 121 |
+
{"step": 99, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.313539165522034, "tokens": 120000, "cumulative_loss_tokens": 11880000, "grad_norm": 0.99609375, "lr": 3e-05, "finish_rate": 0.923, "comp_len": 442.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.319, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.9, "frames": {"chat": 271}, "mem_gb": 9.68, "mem_gb_teacher": 9.68}
|
| 122 |
+
{"step": 100, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.30199915543012323, "tokens": 120000, "cumulative_loss_tokens": 12000000, "grad_norm": 0.80078125, "lr": 3e-05, "finish_rate": 0.856, "comp_len": 508.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.362, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.5, "frames": {"chat": 236}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 123 |
+
[eval step 100] sample: "To solve the problem, we need to determine the values of \\(p\\) and \\(k\\) given the constraints. Let's break down the problem step-by-step:\n\n1. **Understand the Constraints:**\n - Each letter represen"
|
| 124 |
+
checkpoint snapshot queued -> outputs/healed/keep50_offpolicy_warmup_s1224/step0100
|
| 125 |
+
{"step": 101, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.30484250679599745, "tokens": 120000, "cumulative_loss_tokens": 12120000, "grad_norm": 0.75, "lr": 3e-05, "finish_rate": 0.841, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.306, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.5, "frames": {"chat": 232}, "mem_gb": 9.83, "mem_gb_teacher": 9.83}
|
| 126 |
+
{"step": 102, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.30012307230867447, "tokens": 120000, "cumulative_loss_tokens": 12240000, "grad_norm": 1.1640625, "lr": 3e-05, "finish_rate": 0.79, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.392, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 210}, "mem_gb": 9.89, "mem_gb_teacher": 9.89}
|
| 127 |
+
{"step": 103, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.2981501909478257, "tokens": 120000, "cumulative_loss_tokens": 12360000, "grad_norm": 1.2421875, "lr": 3e-05, "finish_rate": 0.811, "comp_len": 553.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.431, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.0, "frames": {"chat": 217}, "mem_gb": 9.85, "mem_gb_teacher": 9.85}
|
| 128 |
+
{"step": 104, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.29460206581093373, "tokens": 120000, "cumulative_loss_tokens": 12480000, "grad_norm": 0.83203125, "lr": 3e-05, "finish_rate": 0.839, "comp_len": 535.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.38, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.1, "frames": {"chat": 224}, "mem_gb": 9.97, "mem_gb_teacher": 9.97}
|
| 129 |
+
{"step": 105, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.3155513667286684, "tokens": 120000, "cumulative_loss_tokens": 12600000, "grad_norm": 0.83203125, "lr": 3e-05, "finish_rate": 0.749, "comp_len": 591.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.481, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 203}, "mem_gb": 9.82, "mem_gb_teacher": 9.82}
|
| 130 |
+
{"step": 106, "epoch": 1, "training_mode": "off-policy", "forward_topk_kl": 0.2852651763110111, "tokens": 120000, "cumulative_loss_tokens": 12720000, "grad_norm": 0.75, "lr": 3e-05, "finish_rate": 0.887, "comp_len": 502.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.326, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 239}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 131 |
+
{"step": 107, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2750922793724885, "tokens": 120000, "cumulative_loss_tokens": 12840000, "grad_norm": 0.93359375, "lr": 3e-05, "finish_rate": 0.902, "comp_len": 472.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.301, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.9, "frames": {"chat": 254}, "mem_gb": 9.83, "mem_gb_teacher": 9.83}
|
| 132 |
+
{"step": 108, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27038282493477067, "tokens": 120000, "cumulative_loss_tokens": 12960000, "grad_norm": 0.91796875, "lr": 3e-05, "finish_rate": 0.876, "comp_len": 497.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.421, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.4, "frames": {"chat": 241}, "mem_gb": 9.93, "mem_gb_teacher": 9.93}
|
| 133 |
+
{"step": 109, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.30530283329064645, "tokens": 120000, "cumulative_loss_tokens": 13080000, "grad_norm": 0.8671875, "lr": 3e-05, "finish_rate": 0.746, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.419, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.2, "frames": {"chat": 213}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 134 |
+
{"step": 110, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2827595801195751, "tokens": 120000, "cumulative_loss_tokens": 13200000, "grad_norm": 0.78125, "lr": 3e-05, "finish_rate": 0.864, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.641, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.6, "frames": {"chat": 221}, "mem_gb": 10.0, "mem_gb_teacher": 10.0}
|
| 135 |
+
[eval step 110] sample: "To solve the problem, we need to determine the digits \\(p\\), \\(a\\), and \\(b\\) that satisfy the given conditions. Let's break down the problem step-by-step:\n\n1. **Understand the Constraints:**\n - \\(p"
|
| 136 |
+
{"step": 111, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.3139219396378845, "tokens": 120000, "cumulative_loss_tokens": 13320000, "grad_norm": 0.9375, "lr": 3e-05, "finish_rate": 0.745, "comp_len": 612.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.334, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.6, "frames": {"chat": 196}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 137 |
+
{"step": 112, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.29290350563563405, "tokens": 120000, "cumulative_loss_tokens": 13440000, "grad_norm": 1.2109375, "lr": 3e-05, "finish_rate": 0.926, "comp_len": 444.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.427, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 28.5, "frames": {"chat": 270}, "mem_gb": 9.77, "mem_gb_teacher": 9.77}
|
| 138 |
+
{"step": 113, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2911341037095835, "tokens": 120000, "cumulative_loss_tokens": 13560000, "grad_norm": 1.2578125, "lr": 3e-05, "finish_rate": 0.815, "comp_len": 555.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.327, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 216}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 139 |
+
{"step": 114, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.30757556294202804, "tokens": 120000, "cumulative_loss_tokens": 13680000, "grad_norm": 0.97265625, "lr": 3e-05, "finish_rate": 0.775, "comp_len": 600.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.314, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.2, "frames": {"chat": 200}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 140 |
+
{"step": 115, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27265539040267467, "tokens": 120000, "cumulative_loss_tokens": 13800000, "grad_norm": 1.046875, "lr": 3e-05, "finish_rate": 0.767, "comp_len": 582.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.406, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.9, "frames": {"chat": 206}, "mem_gb": 9.86, "mem_gb_teacher": 9.86}
|
| 141 |
+
{"step": 116, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.25661204309028884, "tokens": 120000, "cumulative_loss_tokens": 13920000, "grad_norm": 1.0703125, "lr": 3e-05, "finish_rate": 0.902, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.5, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 234}, "mem_gb": 9.9, "mem_gb_teacher": 9.9}
|
| 142 |
+
{"step": 117, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.28587267751296364, "tokens": 120000, "cumulative_loss_tokens": 14040000, "grad_norm": 1.078125, "lr": 3e-05, "finish_rate": 0.823, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.325, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.5, "frames": {"chat": 215}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 143 |
+
{"step": 118, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.24581487802788615, "tokens": 120000, "cumulative_loss_tokens": 14160000, "grad_norm": 0.8515625, "lr": 3e-05, "finish_rate": 0.922, "comp_len": 470.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.447, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.0, "frames": {"chat": 255}, "mem_gb": 9.89, "mem_gb_teacher": 9.89}
|
| 144 |
+
{"step": 119, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2630173706655701, "tokens": 120000, "cumulative_loss_tokens": 14280000, "grad_norm": 1.0390625, "lr": 3e-05, "finish_rate": 0.892, "comp_len": 480.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.377, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.9, "frames": {"chat": 250}, "mem_gb": 9.77, "mem_gb_teacher": 9.77}
|
| 145 |
+
{"step": 120, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.26195900368392466, "tokens": 120000, "cumulative_loss_tokens": 14400000, "grad_norm": 0.85546875, "lr": 3e-05, "finish_rate": 0.884, "comp_len": 495.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.525, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 242}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 146 |
+
[eval step 120] sample: "To solve this problem, we need to determine the values of \\(p\\) and \\(k\\) based on the given equations. Let's break down the problem step-by-step:\n\n1. **Understand the Equations:**\n - \\(a + b = k\\)\n"
|
| 147 |
+
{"step": 121, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27887726591676476, "tokens": 120000, "cumulative_loss_tokens": 14520000, "grad_norm": 0.98828125, "lr": 3e-05, "finish_rate": 0.729, "comp_len": 603.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.517, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 199}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 148 |
+
{"step": 122, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.31573768441453576, "tokens": 120000, "cumulative_loss_tokens": 14640000, "grad_norm": 1.15625, "lr": 3e-05, "finish_rate": 0.784, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.386, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.7, "frames": {"chat": 208}, "mem_gb": 9.99, "mem_gb_teacher": 9.99}
|
| 149 |
+
{"step": 123, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2738492341738194, "tokens": 120000, "cumulative_loss_tokens": 14760000, "grad_norm": 0.859375, "lr": 3e-05, "finish_rate": 0.764, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.304, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.6, "frames": {"chat": 208}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 150 |
+
{"step": 124, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.3032253828023871, "tokens": 120000, "cumulative_loss_tokens": 14880000, "grad_norm": 1.21875, "lr": 3e-05, "finish_rate": 0.732, "comp_len": 574.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.473, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.8, "frames": {"chat": 209}, "mem_gb": 10.07, "mem_gb_teacher": 10.07}
|
| 151 |
+
{"step": 125, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27386389810865125, "tokens": 120000, "cumulative_loss_tokens": 15000000, "grad_norm": 1.5859375, "lr": 3e-05, "finish_rate": 0.855, "comp_len": 510.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.321, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.6, "frames": {"chat": 235}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 152 |
+
{"step": 126, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2811740072357158, "tokens": 120000, "cumulative_loss_tokens": 15120000, "grad_norm": 1.4453125, "lr": 3e-05, "finish_rate": 0.74, "comp_len": 588.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.503, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.8, "frames": {"chat": 204}, "mem_gb": 9.9, "mem_gb_teacher": 9.9}
|
| 153 |
+
{"step": 127, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.32506899852765103, "tokens": 120000, "cumulative_loss_tokens": 15240000, "grad_norm": 2.453125, "lr": 3e-05, "finish_rate": 0.745, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.498, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.8, "frames": {"chat": 208}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 154 |
+
{"step": 128, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27416869887411593, "tokens": 120000, "cumulative_loss_tokens": 15360000, "grad_norm": 1.375, "lr": 3e-05, "finish_rate": 0.825, "comp_len": 500.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.456, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.2, "frames": {"chat": 240}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 155 |
+
{"step": 129, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27367745394359033, "tokens": 120000, "cumulative_loss_tokens": 15480000, "grad_norm": 1.390625, "lr": 3e-05, "finish_rate": 0.89, "comp_len": 487.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.425, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.4, "frames": {"chat": 246}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 156 |
+
{"step": 130, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27279284177869556, "tokens": 120000, "cumulative_loss_tokens": 15600000, "grad_norm": 1.1171875, "lr": 3e-05, "finish_rate": 0.909, "comp_len": 493.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.299, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.1, "frames": {"chat": 243}, "mem_gb": 9.76, "mem_gb_teacher": 9.76}
|
| 157 |
+
[eval step 130] sample: "To solve the problem, we need to determine the values of \\(p\\), \\(r\\), and \\(k\\) given the constraints. Let's break down the problem step-by-step:\n\n1. **Understand the Constraints:**\n - \\(a + b = k\\"
|
| 158 |
+
{"step": 131, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2835182323958725, "tokens": 120000, "cumulative_loss_tokens": 15720000, "grad_norm": 0.953125, "lr": 3e-05, "finish_rate": 0.745, "comp_len": 576.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.449, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.8, "frames": {"chat": 208}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 159 |
+
{"step": 132, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2755484388658156, "tokens": 120000, "cumulative_loss_tokens": 15840000, "grad_norm": 0.8203125, "lr": 3e-05, "finish_rate": 0.817, "comp_len": 547.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.352, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 219}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 160 |
+
{"step": 133, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.27247595444793504, "tokens": 120000, "cumulative_loss_tokens": 15960000, "grad_norm": 0.796875, "lr": 3e-05, "finish_rate": 0.782, "comp_len": 568.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.447, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.3, "frames": {"chat": 211}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 161 |
+
{"step": 134, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.252491025553147, "tokens": 120000, "cumulative_loss_tokens": 16080000, "grad_norm": 0.67578125, "lr": 3e-05, "finish_rate": 0.862, "comp_len": 517.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.283, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.0, "frames": {"chat": 232}, "mem_gb": 9.92, "mem_gb_teacher": 9.92}
|
| 162 |
+
{"step": 135, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2650780773670723, "tokens": 120000, "cumulative_loss_tokens": 16200000, "grad_norm": 0.71875, "lr": 3e-05, "finish_rate": 0.804, "comp_len": 560.7, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.403, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 214}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 163 |
+
{"step": 136, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2518176361516118, "tokens": 120000, "cumulative_loss_tokens": 16320000, "grad_norm": 0.890625, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 531.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.395, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 226}, "mem_gb": 9.85, "mem_gb_teacher": 9.85}
|
| 164 |
+
{"step": 137, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.23503943474429348, "tokens": 120000, "cumulative_loss_tokens": 16440000, "grad_norm": 0.75, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 571.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.404, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 210}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 165 |
+
{"step": 138, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2334536761138588, "tokens": 120000, "cumulative_loss_tokens": 16560000, "grad_norm": 0.6796875, "lr": 3e-05, "finish_rate": 0.858, "comp_len": 550.5, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.436, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 218}, "mem_gb": 9.78, "mem_gb_teacher": 9.78}
|
| 166 |
+
{"step": 139, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2328599476976941, "tokens": 120000, "cumulative_loss_tokens": 16680000, "grad_norm": 0.67578125, "lr": 3e-05, "finish_rate": 0.858, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.354, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.5, "frames": {"chat": 233}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 167 |
+
{"step": 140, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.26084051485359666, "tokens": 120000, "cumulative_loss_tokens": 16800000, "grad_norm": 0.70703125, "lr": 3e-05, "finish_rate": 0.786, "comp_len": 558.1, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.221, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.0, "frames": {"chat": 215}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 168 |
+
[eval step 140] sample: "To solve this problem, we need to determine the values of \\(p\\), \\(a\\), \\(b\\), \\(m\\), and \\(r\\) that satisfy the given equations. Let's break down the problem step-by-step:\n\n1. **Understand the Equati"
|
| 169 |
+
{"step": 141, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.26040056609710055, "tokens": 120000, "cumulative_loss_tokens": 16920000, "grad_norm": 0.83203125, "lr": 3e-05, "finish_rate": 0.845, "comp_len": 515.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.428, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.3, "frames": {"chat": 233}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 170 |
+
{"step": 142, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2547849820467333, "tokens": 120000, "cumulative_loss_tokens": 17040000, "grad_norm": 0.91015625, "lr": 3e-05, "finish_rate": 0.766, "comp_len": 574.2, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.353, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.2, "frames": {"chat": 209}, "mem_gb": 9.89, "mem_gb_teacher": 9.89}
|
| 171 |
+
{"step": 143, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2485178017048786, "tokens": 120000, "cumulative_loss_tokens": 17160000, "grad_norm": 0.83203125, "lr": 3e-05, "finish_rate": 0.908, "comp_len": 458.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.308, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 27.5, "frames": {"chat": 262}, "mem_gb": 9.82, "mem_gb_teacher": 9.82}
|
| 172 |
+
{"step": 144, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.25363729545498886, "tokens": 120000, "cumulative_loss_tokens": 17280000, "grad_norm": 0.7578125, "lr": 3e-05, "finish_rate": 0.9, "comp_len": 481.9, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.241, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.7, "frames": {"chat": 249}, "mem_gb": 9.91, "mem_gb_teacher": 9.91}
|
| 173 |
+
{"step": 145, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.29562477170241375, "tokens": 120000, "cumulative_loss_tokens": 17400000, "grad_norm": 0.9453125, "lr": 3e-05, "finish_rate": 0.819, "comp_len": 528.6, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.364, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 26.4, "frames": {"chat": 227}, "mem_gb": 9.95, "mem_gb_teacher": 9.95}
|
| 174 |
+
{"step": 146, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.25183481702382365, "tokens": 120000, "cumulative_loss_tokens": 17520000, "grad_norm": 0.98828125, "lr": 3e-05, "finish_rate": 0.814, "comp_len": 543.0, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.356, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.5, "frames": {"chat": 221}, "mem_gb": 9.94, "mem_gb_teacher": 9.94}
|
| 175 |
+
{"step": 147, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.2600625433813781, "tokens": 120000, "cumulative_loss_tokens": 17640000, "grad_norm": 0.89453125, "lr": 3e-05, "finish_rate": 0.859, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.473, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.4, "frames": {"chat": 234}, "mem_gb": 9.96, "mem_gb_teacher": 9.96}
|
| 176 |
+
{"step": 148, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.24899872875362636, "tokens": 120000, "cumulative_loss_tokens": 17760000, "grad_norm": 0.7265625, "lr": 3e-05, "finish_rate": 0.817, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.29, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.5, "frames": {"chat": 213}, "mem_gb": 9.9, "mem_gb_teacher": 9.9}
|
| 177 |
+
{"step": 149, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.22898227033279836, "tokens": 120000, "cumulative_loss_tokens": 17880000, "grad_norm": 0.87890625, "lr": 3e-05, "finish_rate": 0.836, "comp_len": 563.4, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.455, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 24.7, "frames": {"chat": 213}, "mem_gb": 9.84, "mem_gb_teacher": 9.84}
|
| 178 |
+
{"step": 150, "epoch": 2, "training_mode": "off-policy", "forward_topk_kl": 0.23123409348068139, "tokens": 120000, "cumulative_loss_tokens": 18000000, "grad_norm": 0.82421875, "lr": 3e-05, "finish_rate": 0.906, "comp_len": 512.8, "dropped_truncated": 0, "gold_loss": null, "gold_lambda": null, "rep_ratio": 2.392, "t_data_s": 0.0, "t_rollout_s": 0.0, "t_step_s": 25.8, "frames": {"chat": 234}, "mem_gb": 9.87, "mem_gb_teacher": 9.87}
|
| 179 |
+
[eval step 150] sample: "To solve this problem, we need to determine the values of \\(p\\), \\(a\\), \\(b\\), \\(m\\), and \\(r\\) that satisfy the given equations. Let's break down the problem step-by-step:\n\n1. **Understand the Constr"
|
| 180 |
+
checkpoint snapshot queued -> outputs/healed/keep50_offpolicy_warmup_s1224/step0150
|
| 181 |
+
wandb: updating run metadata
|
| 182 |
+
wandb: uploading summary
|
| 183 |
+
wandb:
|
| 184 |
+
wandb: Run history:
|
| 185 |
+
wandb: comp_len ▆▅▅▆▄█▆▇▆▅▇▄▅▄▂▇▄▆▃▃▁▄▄▇▅█▇▄▆█▄▇▇▇▄▇▆▃▅▆
|
| 186 |
+
wandb: cumulative_loss_tokens ▁▁▁▂▂▂▂▃▃▃▃▃▃▃▃▄▄▄▄▄▄▄▅▅▅▅▆▆▆▆▇▇▇▇▇█████
|
| 187 |
+
wandb: dropped_truncated ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 188 |
+
wandb: epoch ▁▁▁▁▁▁▁▁▁▁▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅██████████████
|
| 189 |
+
wandb: finish_rate ▁▆▇▆▄▂▆▇▆▃▇▃▁▆▇▃▃▅▅▆▅▅▁▅▃▇▆▄▆▃▃█▇▂▂▆▃█▅█
|
| 190 |
+
wandb: forward_topk_kl ▃▃▁▂▁▅▄▆▅▅▅▆█▇▆▇▇█▅▅▅▅▄▅▃▄▃▄▃▃▃▃▂▃▂▂▂▃▂▁
|
| 191 |
+
wandb: grad_norm ▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▂▂▂▂█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
|
| 192 |
+
wandb: lr ▁▃▅█████████████████████████████████████
|
| 193 |
+
wandb: mem_gb ▅▆▇▆▇█▆▆▇▃▆▆▆▆▄▆▆▆▆▅█▄▆▁▅▄▆▄▃▆▅▆▅▆▅▆▇▄▆▇
|
| 194 |
+
wandb: mem_gb_teacher ▆▇▆▂▆▆▃▆▆▅█▅▆▆▆▁▃▆▆▇▅▄▆█▃▆▆▆▃▅▄▆▆▅▅▆▆▅▆▆
|
| 195 |
+
wandb: +6 ...
|
| 196 |
+
wandb:
|
| 197 |
+
wandb: Run summary:
|
| 198 |
+
wandb: comp_len 512.8
|
| 199 |
+
wandb: cumulative_loss_tokens 18000000
|
| 200 |
+
wandb: dropped_truncated 0
|
| 201 |
+
wandb: epoch 2
|
| 202 |
+
wandb: finish_rate 0.906
|
| 203 |
+
wandb: forward_topk_kl 0.23123
|
| 204 |
+
wandb: grad_norm 0.82422
|
| 205 |
+
wandb: lr 3e-05
|
| 206 |
+
wandb: mem_gb 9.87
|
| 207 |
+
wandb: mem_gb_teacher 9.87
|
| 208 |
+
wandb: +7 ...
|
| 209 |
+
wandb:
|
| 210 |
+
wandb: 🚀 View run offpolicy-warmup-keep50-s1224 at: https://wandb.ai/hbfreed/glean-heal/runs/9td6b5cn
|
| 211 |
+
wandb: ⭐️ View project at: https://wandb.ai/hbfreed/glean-heal
|
| 212 |
+
wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
|
| 213 |
+
wandb: Find logs at: outputs/healed/keep50_offpolicy_warmup_s1224/wandb/run-20260801_230924-9td6b5cn/logs
|
pruned/knee0924_keep40_save.log
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
saved 3.04B params (233/1024 experts deleted) -> outputs/pruned/knee0924/keep40 (6.1 GB safetensors)
|
pruned/uniform_keep2575.materialize.log
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
baseline c4=4.3505
|
| 3 |
+
|
| 4 |
+
uniform_keep25 c4=5.0687 [dead 0/1024, kept 262144, params 2.09B]
|
| 5 |
+
|
| 6 |
+
uniform_keep75 c4=4.6639 [dead 0/1024, kept 786432, params 5.31B]
|
| 7 |
+
|
| 8 |
+
decision gate (variant NLL - glean NLL; positive = glean better):
|
| 9 |
+
saved -> outputs/uniform_control_materialize/results.json
|
pruned/uniform_keep50.materialize.log
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
baseline c4=4.3505
|
| 3 |
+
|
| 4 |
+
uniform_keep50 c4=5.1110 [dead 0/1024, kept 524288, params 3.70B]
|
| 5 |
+
|
| 6 |
+
decision gate (variant NLL - glean NLL; positive = glean better):
|
| 7 |
+
saved -> outputs/uniform_control_materialize/results.json
|
quant_ab/bf16.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"quant": "bf16",
|
| 3 |
+
"shards": 3,
|
| 4 |
+
"tokens": 221592,
|
| 5 |
+
"kl_mean_nats": 1.2805973847606442e-08,
|
| 6 |
+
"kl_median_nats": 5.440404030054857e-11,
|
| 7 |
+
"kl_p95_nats": 1.516273187007755e-07,
|
| 8 |
+
"kl_max_nats": 6.564368959516287e-07,
|
| 9 |
+
"top128_jaccard_mean": 1.0,
|
| 10 |
+
"top1_agreement": 1.0,
|
| 11 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 12 |
+
"captured_mass_quant_at_bf16_support": 0.9997189014740139
|
| 13 |
+
}
|
quant_ab/int8.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"quant": "int8",
|
| 3 |
+
"shards": 3,
|
| 4 |
+
"tokens": 221592,
|
| 5 |
+
"kl_mean_nats": 0.005379186076306062,
|
| 6 |
+
"kl_median_nats": 1.4354211089084856e-05,
|
| 7 |
+
"kl_p95_nats": 0.02423230931162834,
|
| 8 |
+
"kl_max_nats": 2.3649048805236816,
|
| 9 |
+
"top128_jaccard_mean": 0.8820737534866655,
|
| 10 |
+
"top1_agreement": 0.983817105310661,
|
| 11 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 12 |
+
"captured_mass_quant_at_bf16_support": 0.9997208774759044
|
| 13 |
+
}
|
quant_ab/nf4.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"quant": "nf4",
|
| 3 |
+
"shards": 3,
|
| 4 |
+
"tokens": 221592,
|
| 5 |
+
"kl_mean_nats": 0.03224208885256773,
|
| 6 |
+
"kl_median_nats": 0.00010718336125137284,
|
| 7 |
+
"kl_p95_nats": 0.15037551522254944,
|
| 8 |
+
"kl_max_nats": 14.360836029052734,
|
| 9 |
+
"top128_jaccard_mean": 0.7352590498594933,
|
| 10 |
+
"top1_agreement": 0.9612215242427524,
|
| 11 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 12 |
+
"captured_mass_quant_at_bf16_support": 0.9996136682180469
|
| 13 |
+
}
|
quant_ab/run_bf16.log
ADDED
|
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
shard shard_00000.pt: cumulative 73031 tokens
|
| 3 |
+
shard shard_00001.pt: cumulative 142706 tokens
|
| 4 |
+
shard shard_00002.pt: cumulative 221592 tokens
|
| 5 |
+
{
|
| 6 |
+
"quant": "bf16",
|
| 7 |
+
"shards": 3,
|
| 8 |
+
"tokens": 221592,
|
| 9 |
+
"kl_mean_nats": 1.2805973847606442e-08,
|
| 10 |
+
"kl_median_nats": 5.440404030054857e-11,
|
| 11 |
+
"kl_p95_nats": 1.516273187007755e-07,
|
| 12 |
+
"kl_max_nats": 6.564368959516287e-07,
|
| 13 |
+
"top128_jaccard_mean": 1.0,
|
| 14 |
+
"top1_agreement": 1.0,
|
| 15 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 16 |
+
"captured_mass_quant_at_bf16_support": 0.9997189014740139
|
| 17 |
+
}
|
quant_ab/run_int8.log
ADDED
|
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
shard shard_00000.pt: cumulative 73031 tokens
|
| 3 |
+
shard shard_00001.pt: cumulative 142706 tokens
|
| 4 |
+
shard shard_00002.pt: cumulative 221592 tokens
|
| 5 |
+
{
|
| 6 |
+
"quant": "int8",
|
| 7 |
+
"shards": 3,
|
| 8 |
+
"tokens": 221592,
|
| 9 |
+
"kl_mean_nats": 0.005379186076306062,
|
| 10 |
+
"kl_median_nats": 1.4354211089084856e-05,
|
| 11 |
+
"kl_p95_nats": 0.02423230931162834,
|
| 12 |
+
"kl_max_nats": 2.3649048805236816,
|
| 13 |
+
"top128_jaccard_mean": 0.8820737534866655,
|
| 14 |
+
"top1_agreement": 0.983817105310661,
|
| 15 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 16 |
+
"captured_mass_quant_at_bf16_support": 0.9997208774759044
|
| 17 |
+
}
|
quant_ab/run_nf4.log
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
torch._check_is_size(blocksize)
|
| 3 |
+
|
| 4 |
+
/home/henry/Documents/PythonProjects/variable-reap/.venv/lib/python3.12/site-packages/bitsandbytes/backends/cuda/ops.py:468: FutureWarning: _check_is_size will be removed in a future PyTorch release along with guard_size_oblivious. Use _check(i >= 0) instead.
|
| 5 |
+
torch._check_is_size(blocksize)
|
| 6 |
+
shard shard_00000.pt: cumulative 73031 tokens
|
| 7 |
+
shard shard_00001.pt: cumulative 142706 tokens
|
| 8 |
+
shard shard_00002.pt: cumulative 221592 tokens
|
| 9 |
+
{
|
| 10 |
+
"quant": "nf4",
|
| 11 |
+
"shards": 3,
|
| 12 |
+
"tokens": 221592,
|
| 13 |
+
"kl_mean_nats": 0.03224208885256773,
|
| 14 |
+
"kl_median_nats": 0.00010718336125137284,
|
| 15 |
+
"kl_p95_nats": 0.15037551522254944,
|
| 16 |
+
"kl_max_nats": 14.360836029052734,
|
| 17 |
+
"top128_jaccard_mean": 0.7352590498594933,
|
| 18 |
+
"top1_agreement": 0.9612215242427524,
|
| 19 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 20 |
+
"captured_mass_quant_at_bf16_support": 0.9996136682180469
|
| 21 |
+
}
|
quant_ab/run_w4a16.log
ADDED
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
/home/henry/.cache/uv/archive-v0/fRk9qAw51B-A84KDUWQdY/lib/python3.12/site-packages/transformers/quantizers/auto.py:239: UserWarning: You passed `quantization_config` or equivalent parameters to `from_pretrained` but the model you're loading already has a `quantization_config` attribute. The `quantization_config` from the model will be used.However, loading attributes (e.g. ['run_compressed']) will be overwritten with the one you passed to `from_pretrained`. The rest will be ignored.
|
| 2 |
+
warnings.warn(warning_msg)
|
| 3 |
+
|
| 4 |
+
|
| 5 |
+
shard shard_00000.pt: cumulative 73031 tokens
|
| 6 |
+
shard shard_00001.pt: cumulative 142706 tokens
|
| 7 |
+
[W720 13:34:51.273718740 CUDACachingAllocator.cpp:3933] memory allocation failed with OOM on device 0 while trying to allocate 618659840 bytes (free: 165085184, total: 25292898304).
|
| 8 |
+
shard shard_00002.pt: cumulative 221592 tokens
|
| 9 |
+
{
|
| 10 |
+
"quant": "w4a16",
|
| 11 |
+
"shards": 3,
|
| 12 |
+
"tokens": 221592,
|
| 13 |
+
"kl_mean_nats": 0.03984629407661169,
|
| 14 |
+
"kl_median_nats": 0.00012320266978349537,
|
| 15 |
+
"kl_p95_nats": 0.18111330270767212,
|
| 16 |
+
"kl_max_nats": 15.414010047912598,
|
| 17 |
+
"top128_jaccard_mean": 0.7149058585433935,
|
| 18 |
+
"top1_agreement": 0.9574262608758439,
|
| 19 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 20 |
+
"captured_mass_quant_at_bf16_support": 0.9995829765622533
|
| 21 |
+
}
|
quant_ab/w4a16.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"quant": "w4a16",
|
| 3 |
+
"shards": 3,
|
| 4 |
+
"tokens": 221592,
|
| 5 |
+
"kl_mean_nats": 0.03984629407661169,
|
| 6 |
+
"kl_median_nats": 0.00012320266978349537,
|
| 7 |
+
"kl_p95_nats": 0.18111330270767212,
|
| 8 |
+
"kl_max_nats": 15.414010047912598,
|
| 9 |
+
"top128_jaccard_mean": 0.7149058585433935,
|
| 10 |
+
"top1_agreement": 0.9574262608758439,
|
| 11 |
+
"captured_mass_bf16": 0.9997188871511677,
|
| 12 |
+
"captured_mass_quant_at_bf16_support": 0.9995829765622533
|
| 13 |
+
}
|
qwen35_reap_keep25/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if (preserve_thinking is defined and preserve_thinking is true) or (loop.index0 > ns.last_query_index) %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
qwen35_reap_keep25/config.json
ADDED
|
@@ -0,0 +1,2752 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"PrunedQwen3_5MoeForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"attn_output_gate": true,
|
| 8 |
+
"auto_map": {
|
| 9 |
+
"AutoConfig": "configuration_pruned_qwen3_5_moe.PrunedQwen3_5MoeTextConfig",
|
| 10 |
+
"AutoModelForCausalLM": "modeling_pruned_qwen3_5_moe.PrunedQwen3_5MoeForCausalLM"
|
| 11 |
+
},
|
| 12 |
+
"bos_token_id": 248044,
|
| 13 |
+
"dtype": "bfloat16",
|
| 14 |
+
"eos_token_id": 248044,
|
| 15 |
+
"expert_widths": [
|
| 16 |
+
[
|
| 17 |
+
512,
|
| 18 |
+
512,
|
| 19 |
+
512,
|
| 20 |
+
512,
|
| 21 |
+
512,
|
| 22 |
+
512,
|
| 23 |
+
512,
|
| 24 |
+
512,
|
| 25 |
+
512,
|
| 26 |
+
512,
|
| 27 |
+
512,
|
| 28 |
+
512,
|
| 29 |
+
512,
|
| 30 |
+
512,
|
| 31 |
+
512,
|
| 32 |
+
512,
|
| 33 |
+
512,
|
| 34 |
+
512,
|
| 35 |
+
512,
|
| 36 |
+
512,
|
| 37 |
+
512,
|
| 38 |
+
512,
|
| 39 |
+
512,
|
| 40 |
+
512,
|
| 41 |
+
512,
|
| 42 |
+
512,
|
| 43 |
+
512,
|
| 44 |
+
512,
|
| 45 |
+
512,
|
| 46 |
+
512,
|
| 47 |
+
512,
|
| 48 |
+
512,
|
| 49 |
+
512,
|
| 50 |
+
512,
|
| 51 |
+
512,
|
| 52 |
+
512,
|
| 53 |
+
512,
|
| 54 |
+
512,
|
| 55 |
+
512,
|
| 56 |
+
512,
|
| 57 |
+
512,
|
| 58 |
+
512,
|
| 59 |
+
512,
|
| 60 |
+
512,
|
| 61 |
+
512,
|
| 62 |
+
512,
|
| 63 |
+
512,
|
| 64 |
+
512,
|
| 65 |
+
512,
|
| 66 |
+
512,
|
| 67 |
+
512,
|
| 68 |
+
512,
|
| 69 |
+
512,
|
| 70 |
+
512,
|
| 71 |
+
512,
|
| 72 |
+
512,
|
| 73 |
+
512,
|
| 74 |
+
512,
|
| 75 |
+
512,
|
| 76 |
+
512,
|
| 77 |
+
512,
|
| 78 |
+
512,
|
| 79 |
+
512,
|
| 80 |
+
512
|
| 81 |
+
],
|
| 82 |
+
[
|
| 83 |
+
512,
|
| 84 |
+
512,
|
| 85 |
+
512,
|
| 86 |
+
512,
|
| 87 |
+
512,
|
| 88 |
+
512,
|
| 89 |
+
512,
|
| 90 |
+
512,
|
| 91 |
+
512,
|
| 92 |
+
512,
|
| 93 |
+
512,
|
| 94 |
+
512,
|
| 95 |
+
512,
|
| 96 |
+
512,
|
| 97 |
+
512,
|
| 98 |
+
512,
|
| 99 |
+
512,
|
| 100 |
+
512,
|
| 101 |
+
512,
|
| 102 |
+
512,
|
| 103 |
+
512,
|
| 104 |
+
512,
|
| 105 |
+
512,
|
| 106 |
+
512,
|
| 107 |
+
512,
|
| 108 |
+
512,
|
| 109 |
+
512,
|
| 110 |
+
512,
|
| 111 |
+
512,
|
| 112 |
+
512,
|
| 113 |
+
512,
|
| 114 |
+
512,
|
| 115 |
+
512,
|
| 116 |
+
512,
|
| 117 |
+
512,
|
| 118 |
+
512,
|
| 119 |
+
512,
|
| 120 |
+
512,
|
| 121 |
+
512,
|
| 122 |
+
512,
|
| 123 |
+
512,
|
| 124 |
+
512,
|
| 125 |
+
512,
|
| 126 |
+
512,
|
| 127 |
+
512,
|
| 128 |
+
512,
|
| 129 |
+
512,
|
| 130 |
+
512,
|
| 131 |
+
512,
|
| 132 |
+
512,
|
| 133 |
+
512,
|
| 134 |
+
512,
|
| 135 |
+
512,
|
| 136 |
+
512,
|
| 137 |
+
512,
|
| 138 |
+
512,
|
| 139 |
+
512,
|
| 140 |
+
512,
|
| 141 |
+
512,
|
| 142 |
+
512,
|
| 143 |
+
512,
|
| 144 |
+
512,
|
| 145 |
+
512,
|
| 146 |
+
512
|
| 147 |
+
],
|
| 148 |
+
[
|
| 149 |
+
512,
|
| 150 |
+
512,
|
| 151 |
+
512,
|
| 152 |
+
512,
|
| 153 |
+
512,
|
| 154 |
+
512,
|
| 155 |
+
512,
|
| 156 |
+
512,
|
| 157 |
+
512,
|
| 158 |
+
512,
|
| 159 |
+
512,
|
| 160 |
+
512,
|
| 161 |
+
512,
|
| 162 |
+
512,
|
| 163 |
+
512,
|
| 164 |
+
512,
|
| 165 |
+
512,
|
| 166 |
+
512,
|
| 167 |
+
512,
|
| 168 |
+
512,
|
| 169 |
+
512,
|
| 170 |
+
512,
|
| 171 |
+
512,
|
| 172 |
+
512,
|
| 173 |
+
512,
|
| 174 |
+
512,
|
| 175 |
+
512,
|
| 176 |
+
512,
|
| 177 |
+
512,
|
| 178 |
+
512,
|
| 179 |
+
512,
|
| 180 |
+
512,
|
| 181 |
+
512,
|
| 182 |
+
512,
|
| 183 |
+
512,
|
| 184 |
+
512,
|
| 185 |
+
512,
|
| 186 |
+
512,
|
| 187 |
+
512,
|
| 188 |
+
512,
|
| 189 |
+
512,
|
| 190 |
+
512,
|
| 191 |
+
512,
|
| 192 |
+
512,
|
| 193 |
+
512,
|
| 194 |
+
512,
|
| 195 |
+
512,
|
| 196 |
+
512,
|
| 197 |
+
512,
|
| 198 |
+
512,
|
| 199 |
+
512,
|
| 200 |
+
512,
|
| 201 |
+
512,
|
| 202 |
+
512,
|
| 203 |
+
512,
|
| 204 |
+
512,
|
| 205 |
+
512,
|
| 206 |
+
512,
|
| 207 |
+
512,
|
| 208 |
+
512,
|
| 209 |
+
512,
|
| 210 |
+
512,
|
| 211 |
+
512,
|
| 212 |
+
512
|
| 213 |
+
],
|
| 214 |
+
[
|
| 215 |
+
512,
|
| 216 |
+
512,
|
| 217 |
+
512,
|
| 218 |
+
512,
|
| 219 |
+
512,
|
| 220 |
+
512,
|
| 221 |
+
512,
|
| 222 |
+
512,
|
| 223 |
+
512,
|
| 224 |
+
512,
|
| 225 |
+
512,
|
| 226 |
+
512,
|
| 227 |
+
512,
|
| 228 |
+
512,
|
| 229 |
+
512,
|
| 230 |
+
512,
|
| 231 |
+
512,
|
| 232 |
+
512,
|
| 233 |
+
512,
|
| 234 |
+
512,
|
| 235 |
+
512,
|
| 236 |
+
512,
|
| 237 |
+
512,
|
| 238 |
+
512,
|
| 239 |
+
512,
|
| 240 |
+
512,
|
| 241 |
+
512,
|
| 242 |
+
512,
|
| 243 |
+
512,
|
| 244 |
+
512,
|
| 245 |
+
512,
|
| 246 |
+
512,
|
| 247 |
+
512,
|
| 248 |
+
512,
|
| 249 |
+
512,
|
| 250 |
+
512,
|
| 251 |
+
512,
|
| 252 |
+
512,
|
| 253 |
+
512,
|
| 254 |
+
512,
|
| 255 |
+
512,
|
| 256 |
+
512,
|
| 257 |
+
512,
|
| 258 |
+
512,
|
| 259 |
+
512,
|
| 260 |
+
512,
|
| 261 |
+
512,
|
| 262 |
+
512,
|
| 263 |
+
512,
|
| 264 |
+
512,
|
| 265 |
+
512,
|
| 266 |
+
512,
|
| 267 |
+
512,
|
| 268 |
+
512,
|
| 269 |
+
512,
|
| 270 |
+
512,
|
| 271 |
+
512,
|
| 272 |
+
512,
|
| 273 |
+
512,
|
| 274 |
+
512,
|
| 275 |
+
512,
|
| 276 |
+
512,
|
| 277 |
+
512,
|
| 278 |
+
512
|
| 279 |
+
],
|
| 280 |
+
[
|
| 281 |
+
512,
|
| 282 |
+
512,
|
| 283 |
+
512,
|
| 284 |
+
512,
|
| 285 |
+
512,
|
| 286 |
+
512,
|
| 287 |
+
512,
|
| 288 |
+
512,
|
| 289 |
+
512,
|
| 290 |
+
512,
|
| 291 |
+
512,
|
| 292 |
+
512,
|
| 293 |
+
512,
|
| 294 |
+
512,
|
| 295 |
+
512,
|
| 296 |
+
512,
|
| 297 |
+
512,
|
| 298 |
+
512,
|
| 299 |
+
512,
|
| 300 |
+
512,
|
| 301 |
+
512,
|
| 302 |
+
512,
|
| 303 |
+
512,
|
| 304 |
+
512,
|
| 305 |
+
512,
|
| 306 |
+
512,
|
| 307 |
+
512,
|
| 308 |
+
512,
|
| 309 |
+
512,
|
| 310 |
+
512,
|
| 311 |
+
512,
|
| 312 |
+
512,
|
| 313 |
+
512,
|
| 314 |
+
512,
|
| 315 |
+
512,
|
| 316 |
+
512,
|
| 317 |
+
512,
|
| 318 |
+
512,
|
| 319 |
+
512,
|
| 320 |
+
512,
|
| 321 |
+
512,
|
| 322 |
+
512,
|
| 323 |
+
512,
|
| 324 |
+
512,
|
| 325 |
+
512,
|
| 326 |
+
512,
|
| 327 |
+
512,
|
| 328 |
+
512,
|
| 329 |
+
512,
|
| 330 |
+
512,
|
| 331 |
+
512,
|
| 332 |
+
512,
|
| 333 |
+
512,
|
| 334 |
+
512,
|
| 335 |
+
512,
|
| 336 |
+
512,
|
| 337 |
+
512,
|
| 338 |
+
512,
|
| 339 |
+
512,
|
| 340 |
+
512,
|
| 341 |
+
512,
|
| 342 |
+
512,
|
| 343 |
+
512,
|
| 344 |
+
512
|
| 345 |
+
],
|
| 346 |
+
[
|
| 347 |
+
512,
|
| 348 |
+
512,
|
| 349 |
+
512,
|
| 350 |
+
512,
|
| 351 |
+
512,
|
| 352 |
+
512,
|
| 353 |
+
512,
|
| 354 |
+
512,
|
| 355 |
+
512,
|
| 356 |
+
512,
|
| 357 |
+
512,
|
| 358 |
+
512,
|
| 359 |
+
512,
|
| 360 |
+
512,
|
| 361 |
+
512,
|
| 362 |
+
512,
|
| 363 |
+
512,
|
| 364 |
+
512,
|
| 365 |
+
512,
|
| 366 |
+
512,
|
| 367 |
+
512,
|
| 368 |
+
512,
|
| 369 |
+
512,
|
| 370 |
+
512,
|
| 371 |
+
512,
|
| 372 |
+
512,
|
| 373 |
+
512,
|
| 374 |
+
512,
|
| 375 |
+
512,
|
| 376 |
+
512,
|
| 377 |
+
512,
|
| 378 |
+
512,
|
| 379 |
+
512,
|
| 380 |
+
512,
|
| 381 |
+
512,
|
| 382 |
+
512,
|
| 383 |
+
512,
|
| 384 |
+
512,
|
| 385 |
+
512,
|
| 386 |
+
512,
|
| 387 |
+
512,
|
| 388 |
+
512,
|
| 389 |
+
512,
|
| 390 |
+
512,
|
| 391 |
+
512,
|
| 392 |
+
512,
|
| 393 |
+
512,
|
| 394 |
+
512,
|
| 395 |
+
512,
|
| 396 |
+
512,
|
| 397 |
+
512,
|
| 398 |
+
512,
|
| 399 |
+
512,
|
| 400 |
+
512,
|
| 401 |
+
512,
|
| 402 |
+
512,
|
| 403 |
+
512,
|
| 404 |
+
512,
|
| 405 |
+
512,
|
| 406 |
+
512,
|
| 407 |
+
512,
|
| 408 |
+
512,
|
| 409 |
+
512,
|
| 410 |
+
512
|
| 411 |
+
],
|
| 412 |
+
[
|
| 413 |
+
512,
|
| 414 |
+
512,
|
| 415 |
+
512,
|
| 416 |
+
512,
|
| 417 |
+
512,
|
| 418 |
+
512,
|
| 419 |
+
512,
|
| 420 |
+
512,
|
| 421 |
+
512,
|
| 422 |
+
512,
|
| 423 |
+
512,
|
| 424 |
+
512,
|
| 425 |
+
512,
|
| 426 |
+
512,
|
| 427 |
+
512,
|
| 428 |
+
512,
|
| 429 |
+
512,
|
| 430 |
+
512,
|
| 431 |
+
512,
|
| 432 |
+
512,
|
| 433 |
+
512,
|
| 434 |
+
512,
|
| 435 |
+
512,
|
| 436 |
+
512,
|
| 437 |
+
512,
|
| 438 |
+
512,
|
| 439 |
+
512,
|
| 440 |
+
512,
|
| 441 |
+
512,
|
| 442 |
+
512,
|
| 443 |
+
512,
|
| 444 |
+
512,
|
| 445 |
+
512,
|
| 446 |
+
512,
|
| 447 |
+
512,
|
| 448 |
+
512,
|
| 449 |
+
512,
|
| 450 |
+
512,
|
| 451 |
+
512,
|
| 452 |
+
512,
|
| 453 |
+
512,
|
| 454 |
+
512,
|
| 455 |
+
512,
|
| 456 |
+
512,
|
| 457 |
+
512,
|
| 458 |
+
512,
|
| 459 |
+
512,
|
| 460 |
+
512,
|
| 461 |
+
512,
|
| 462 |
+
512,
|
| 463 |
+
512,
|
| 464 |
+
512,
|
| 465 |
+
512,
|
| 466 |
+
512,
|
| 467 |
+
512,
|
| 468 |
+
512,
|
| 469 |
+
512,
|
| 470 |
+
512,
|
| 471 |
+
512,
|
| 472 |
+
512,
|
| 473 |
+
512,
|
| 474 |
+
512,
|
| 475 |
+
512,
|
| 476 |
+
512
|
| 477 |
+
],
|
| 478 |
+
[
|
| 479 |
+
512,
|
| 480 |
+
512,
|
| 481 |
+
512,
|
| 482 |
+
512,
|
| 483 |
+
512,
|
| 484 |
+
512,
|
| 485 |
+
512,
|
| 486 |
+
512,
|
| 487 |
+
512,
|
| 488 |
+
512,
|
| 489 |
+
512,
|
| 490 |
+
512,
|
| 491 |
+
512,
|
| 492 |
+
512,
|
| 493 |
+
512,
|
| 494 |
+
512,
|
| 495 |
+
512,
|
| 496 |
+
512,
|
| 497 |
+
512,
|
| 498 |
+
512,
|
| 499 |
+
512,
|
| 500 |
+
512,
|
| 501 |
+
512,
|
| 502 |
+
512,
|
| 503 |
+
512,
|
| 504 |
+
512,
|
| 505 |
+
512,
|
| 506 |
+
512,
|
| 507 |
+
512,
|
| 508 |
+
512,
|
| 509 |
+
512,
|
| 510 |
+
512,
|
| 511 |
+
512,
|
| 512 |
+
512,
|
| 513 |
+
512,
|
| 514 |
+
512,
|
| 515 |
+
512,
|
| 516 |
+
512,
|
| 517 |
+
512,
|
| 518 |
+
512,
|
| 519 |
+
512,
|
| 520 |
+
512,
|
| 521 |
+
512,
|
| 522 |
+
512,
|
| 523 |
+
512,
|
| 524 |
+
512,
|
| 525 |
+
512,
|
| 526 |
+
512,
|
| 527 |
+
512,
|
| 528 |
+
512,
|
| 529 |
+
512,
|
| 530 |
+
512,
|
| 531 |
+
512,
|
| 532 |
+
512,
|
| 533 |
+
512,
|
| 534 |
+
512,
|
| 535 |
+
512,
|
| 536 |
+
512,
|
| 537 |
+
512,
|
| 538 |
+
512,
|
| 539 |
+
512,
|
| 540 |
+
512,
|
| 541 |
+
512,
|
| 542 |
+
512
|
| 543 |
+
],
|
| 544 |
+
[
|
| 545 |
+
512,
|
| 546 |
+
512,
|
| 547 |
+
512,
|
| 548 |
+
512,
|
| 549 |
+
512,
|
| 550 |
+
512,
|
| 551 |
+
512,
|
| 552 |
+
512,
|
| 553 |
+
512,
|
| 554 |
+
512,
|
| 555 |
+
512,
|
| 556 |
+
512,
|
| 557 |
+
512,
|
| 558 |
+
512,
|
| 559 |
+
512,
|
| 560 |
+
512,
|
| 561 |
+
512,
|
| 562 |
+
512,
|
| 563 |
+
512,
|
| 564 |
+
512,
|
| 565 |
+
512,
|
| 566 |
+
512,
|
| 567 |
+
512,
|
| 568 |
+
512,
|
| 569 |
+
512,
|
| 570 |
+
512,
|
| 571 |
+
512,
|
| 572 |
+
512,
|
| 573 |
+
512,
|
| 574 |
+
512,
|
| 575 |
+
512,
|
| 576 |
+
512,
|
| 577 |
+
512,
|
| 578 |
+
512,
|
| 579 |
+
512,
|
| 580 |
+
512,
|
| 581 |
+
512,
|
| 582 |
+
512,
|
| 583 |
+
512,
|
| 584 |
+
512,
|
| 585 |
+
512,
|
| 586 |
+
512,
|
| 587 |
+
512,
|
| 588 |
+
512,
|
| 589 |
+
512,
|
| 590 |
+
512,
|
| 591 |
+
512,
|
| 592 |
+
512,
|
| 593 |
+
512,
|
| 594 |
+
512,
|
| 595 |
+
512,
|
| 596 |
+
512,
|
| 597 |
+
512,
|
| 598 |
+
512,
|
| 599 |
+
512,
|
| 600 |
+
512,
|
| 601 |
+
512,
|
| 602 |
+
512,
|
| 603 |
+
512,
|
| 604 |
+
512,
|
| 605 |
+
512,
|
| 606 |
+
512,
|
| 607 |
+
512,
|
| 608 |
+
512
|
| 609 |
+
],
|
| 610 |
+
[
|
| 611 |
+
512,
|
| 612 |
+
512,
|
| 613 |
+
512,
|
| 614 |
+
512,
|
| 615 |
+
512,
|
| 616 |
+
512,
|
| 617 |
+
512,
|
| 618 |
+
512,
|
| 619 |
+
512,
|
| 620 |
+
512,
|
| 621 |
+
512,
|
| 622 |
+
512,
|
| 623 |
+
512,
|
| 624 |
+
512,
|
| 625 |
+
512,
|
| 626 |
+
512,
|
| 627 |
+
512,
|
| 628 |
+
512,
|
| 629 |
+
512,
|
| 630 |
+
512,
|
| 631 |
+
512,
|
| 632 |
+
512,
|
| 633 |
+
512,
|
| 634 |
+
512,
|
| 635 |
+
512,
|
| 636 |
+
512,
|
| 637 |
+
512,
|
| 638 |
+
512,
|
| 639 |
+
512,
|
| 640 |
+
512,
|
| 641 |
+
512,
|
| 642 |
+
512,
|
| 643 |
+
512,
|
| 644 |
+
512,
|
| 645 |
+
512,
|
| 646 |
+
512,
|
| 647 |
+
512,
|
| 648 |
+
512,
|
| 649 |
+
512,
|
| 650 |
+
512,
|
| 651 |
+
512,
|
| 652 |
+
512,
|
| 653 |
+
512,
|
| 654 |
+
512,
|
| 655 |
+
512,
|
| 656 |
+
512,
|
| 657 |
+
512,
|
| 658 |
+
512,
|
| 659 |
+
512,
|
| 660 |
+
512,
|
| 661 |
+
512,
|
| 662 |
+
512,
|
| 663 |
+
512,
|
| 664 |
+
512,
|
| 665 |
+
512,
|
| 666 |
+
512,
|
| 667 |
+
512,
|
| 668 |
+
512,
|
| 669 |
+
512,
|
| 670 |
+
512,
|
| 671 |
+
512,
|
| 672 |
+
512,
|
| 673 |
+
512,
|
| 674 |
+
512
|
| 675 |
+
],
|
| 676 |
+
[
|
| 677 |
+
512,
|
| 678 |
+
512,
|
| 679 |
+
512,
|
| 680 |
+
512,
|
| 681 |
+
512,
|
| 682 |
+
512,
|
| 683 |
+
512,
|
| 684 |
+
512,
|
| 685 |
+
512,
|
| 686 |
+
512,
|
| 687 |
+
512,
|
| 688 |
+
512,
|
| 689 |
+
512,
|
| 690 |
+
512,
|
| 691 |
+
512,
|
| 692 |
+
512,
|
| 693 |
+
512,
|
| 694 |
+
512,
|
| 695 |
+
512,
|
| 696 |
+
512,
|
| 697 |
+
512,
|
| 698 |
+
512,
|
| 699 |
+
512,
|
| 700 |
+
512,
|
| 701 |
+
512,
|
| 702 |
+
512,
|
| 703 |
+
512,
|
| 704 |
+
512,
|
| 705 |
+
512,
|
| 706 |
+
512,
|
| 707 |
+
512,
|
| 708 |
+
512,
|
| 709 |
+
512,
|
| 710 |
+
512,
|
| 711 |
+
512,
|
| 712 |
+
512,
|
| 713 |
+
512,
|
| 714 |
+
512,
|
| 715 |
+
512,
|
| 716 |
+
512,
|
| 717 |
+
512,
|
| 718 |
+
512,
|
| 719 |
+
512,
|
| 720 |
+
512,
|
| 721 |
+
512,
|
| 722 |
+
512,
|
| 723 |
+
512,
|
| 724 |
+
512,
|
| 725 |
+
512,
|
| 726 |
+
512,
|
| 727 |
+
512,
|
| 728 |
+
512,
|
| 729 |
+
512,
|
| 730 |
+
512,
|
| 731 |
+
512,
|
| 732 |
+
512,
|
| 733 |
+
512,
|
| 734 |
+
512,
|
| 735 |
+
512,
|
| 736 |
+
512,
|
| 737 |
+
512,
|
| 738 |
+
512,
|
| 739 |
+
512,
|
| 740 |
+
512
|
| 741 |
+
],
|
| 742 |
+
[
|
| 743 |
+
512,
|
| 744 |
+
512,
|
| 745 |
+
512,
|
| 746 |
+
512,
|
| 747 |
+
512,
|
| 748 |
+
512,
|
| 749 |
+
512,
|
| 750 |
+
512,
|
| 751 |
+
512,
|
| 752 |
+
512,
|
| 753 |
+
512,
|
| 754 |
+
512,
|
| 755 |
+
512,
|
| 756 |
+
512,
|
| 757 |
+
512,
|
| 758 |
+
512,
|
| 759 |
+
512,
|
| 760 |
+
512,
|
| 761 |
+
512,
|
| 762 |
+
512,
|
| 763 |
+
512,
|
| 764 |
+
512,
|
| 765 |
+
512,
|
| 766 |
+
512,
|
| 767 |
+
512,
|
| 768 |
+
512,
|
| 769 |
+
512,
|
| 770 |
+
512,
|
| 771 |
+
512,
|
| 772 |
+
512,
|
| 773 |
+
512,
|
| 774 |
+
512,
|
| 775 |
+
512,
|
| 776 |
+
512,
|
| 777 |
+
512,
|
| 778 |
+
512,
|
| 779 |
+
512,
|
| 780 |
+
512,
|
| 781 |
+
512,
|
| 782 |
+
512,
|
| 783 |
+
512,
|
| 784 |
+
512,
|
| 785 |
+
512,
|
| 786 |
+
512,
|
| 787 |
+
512,
|
| 788 |
+
512,
|
| 789 |
+
512,
|
| 790 |
+
512,
|
| 791 |
+
512,
|
| 792 |
+
512,
|
| 793 |
+
512,
|
| 794 |
+
512,
|
| 795 |
+
512,
|
| 796 |
+
512,
|
| 797 |
+
512,
|
| 798 |
+
512,
|
| 799 |
+
512,
|
| 800 |
+
512,
|
| 801 |
+
512,
|
| 802 |
+
512,
|
| 803 |
+
512,
|
| 804 |
+
512,
|
| 805 |
+
512,
|
| 806 |
+
512
|
| 807 |
+
],
|
| 808 |
+
[
|
| 809 |
+
512,
|
| 810 |
+
512,
|
| 811 |
+
512,
|
| 812 |
+
512,
|
| 813 |
+
512,
|
| 814 |
+
512,
|
| 815 |
+
512,
|
| 816 |
+
512,
|
| 817 |
+
512,
|
| 818 |
+
512,
|
| 819 |
+
512,
|
| 820 |
+
512,
|
| 821 |
+
512,
|
| 822 |
+
512,
|
| 823 |
+
512,
|
| 824 |
+
512,
|
| 825 |
+
512,
|
| 826 |
+
512,
|
| 827 |
+
512,
|
| 828 |
+
512,
|
| 829 |
+
512,
|
| 830 |
+
512,
|
| 831 |
+
512,
|
| 832 |
+
512,
|
| 833 |
+
512,
|
| 834 |
+
512,
|
| 835 |
+
512,
|
| 836 |
+
512,
|
| 837 |
+
512,
|
| 838 |
+
512,
|
| 839 |
+
512,
|
| 840 |
+
512,
|
| 841 |
+
512,
|
| 842 |
+
512,
|
| 843 |
+
512,
|
| 844 |
+
512,
|
| 845 |
+
512,
|
| 846 |
+
512,
|
| 847 |
+
512,
|
| 848 |
+
512,
|
| 849 |
+
512,
|
| 850 |
+
512,
|
| 851 |
+
512,
|
| 852 |
+
512,
|
| 853 |
+
512,
|
| 854 |
+
512,
|
| 855 |
+
512,
|
| 856 |
+
512,
|
| 857 |
+
512,
|
| 858 |
+
512,
|
| 859 |
+
512,
|
| 860 |
+
512,
|
| 861 |
+
512,
|
| 862 |
+
512,
|
| 863 |
+
512,
|
| 864 |
+
512,
|
| 865 |
+
512,
|
| 866 |
+
512,
|
| 867 |
+
512,
|
| 868 |
+
512,
|
| 869 |
+
512,
|
| 870 |
+
512,
|
| 871 |
+
512,
|
| 872 |
+
512
|
| 873 |
+
],
|
| 874 |
+
[
|
| 875 |
+
512,
|
| 876 |
+
512,
|
| 877 |
+
512,
|
| 878 |
+
512,
|
| 879 |
+
512,
|
| 880 |
+
512,
|
| 881 |
+
512,
|
| 882 |
+
512,
|
| 883 |
+
512,
|
| 884 |
+
512,
|
| 885 |
+
512,
|
| 886 |
+
512,
|
| 887 |
+
512,
|
| 888 |
+
512,
|
| 889 |
+
512,
|
| 890 |
+
512,
|
| 891 |
+
512,
|
| 892 |
+
512,
|
| 893 |
+
512,
|
| 894 |
+
512,
|
| 895 |
+
512,
|
| 896 |
+
512,
|
| 897 |
+
512,
|
| 898 |
+
512,
|
| 899 |
+
512,
|
| 900 |
+
512,
|
| 901 |
+
512,
|
| 902 |
+
512,
|
| 903 |
+
512,
|
| 904 |
+
512,
|
| 905 |
+
512,
|
| 906 |
+
512,
|
| 907 |
+
512,
|
| 908 |
+
512,
|
| 909 |
+
512,
|
| 910 |
+
512,
|
| 911 |
+
512,
|
| 912 |
+
512,
|
| 913 |
+
512,
|
| 914 |
+
512,
|
| 915 |
+
512,
|
| 916 |
+
512,
|
| 917 |
+
512,
|
| 918 |
+
512,
|
| 919 |
+
512,
|
| 920 |
+
512,
|
| 921 |
+
512,
|
| 922 |
+
512,
|
| 923 |
+
512,
|
| 924 |
+
512,
|
| 925 |
+
512,
|
| 926 |
+
512,
|
| 927 |
+
512,
|
| 928 |
+
512,
|
| 929 |
+
512,
|
| 930 |
+
512,
|
| 931 |
+
512,
|
| 932 |
+
512,
|
| 933 |
+
512,
|
| 934 |
+
512,
|
| 935 |
+
512,
|
| 936 |
+
512,
|
| 937 |
+
512,
|
| 938 |
+
512
|
| 939 |
+
],
|
| 940 |
+
[
|
| 941 |
+
512,
|
| 942 |
+
512,
|
| 943 |
+
512,
|
| 944 |
+
512,
|
| 945 |
+
512,
|
| 946 |
+
512,
|
| 947 |
+
512,
|
| 948 |
+
512,
|
| 949 |
+
512,
|
| 950 |
+
512,
|
| 951 |
+
512,
|
| 952 |
+
512,
|
| 953 |
+
512,
|
| 954 |
+
512,
|
| 955 |
+
512,
|
| 956 |
+
512,
|
| 957 |
+
512,
|
| 958 |
+
512,
|
| 959 |
+
512,
|
| 960 |
+
512,
|
| 961 |
+
512,
|
| 962 |
+
512,
|
| 963 |
+
512,
|
| 964 |
+
512,
|
| 965 |
+
512,
|
| 966 |
+
512,
|
| 967 |
+
512,
|
| 968 |
+
512,
|
| 969 |
+
512,
|
| 970 |
+
512,
|
| 971 |
+
512,
|
| 972 |
+
512,
|
| 973 |
+
512,
|
| 974 |
+
512,
|
| 975 |
+
512,
|
| 976 |
+
512,
|
| 977 |
+
512,
|
| 978 |
+
512,
|
| 979 |
+
512,
|
| 980 |
+
512,
|
| 981 |
+
512,
|
| 982 |
+
512,
|
| 983 |
+
512,
|
| 984 |
+
512,
|
| 985 |
+
512,
|
| 986 |
+
512,
|
| 987 |
+
512,
|
| 988 |
+
512,
|
| 989 |
+
512,
|
| 990 |
+
512,
|
| 991 |
+
512,
|
| 992 |
+
512,
|
| 993 |
+
512,
|
| 994 |
+
512,
|
| 995 |
+
512,
|
| 996 |
+
512,
|
| 997 |
+
512,
|
| 998 |
+
512,
|
| 999 |
+
512,
|
| 1000 |
+
512,
|
| 1001 |
+
512,
|
| 1002 |
+
512,
|
| 1003 |
+
512,
|
| 1004 |
+
512
|
| 1005 |
+
],
|
| 1006 |
+
[
|
| 1007 |
+
512,
|
| 1008 |
+
512,
|
| 1009 |
+
512,
|
| 1010 |
+
512,
|
| 1011 |
+
512,
|
| 1012 |
+
512,
|
| 1013 |
+
512,
|
| 1014 |
+
512,
|
| 1015 |
+
512,
|
| 1016 |
+
512,
|
| 1017 |
+
512,
|
| 1018 |
+
512,
|
| 1019 |
+
512,
|
| 1020 |
+
512,
|
| 1021 |
+
512,
|
| 1022 |
+
512,
|
| 1023 |
+
512,
|
| 1024 |
+
512,
|
| 1025 |
+
512,
|
| 1026 |
+
512,
|
| 1027 |
+
512,
|
| 1028 |
+
512,
|
| 1029 |
+
512,
|
| 1030 |
+
512,
|
| 1031 |
+
512,
|
| 1032 |
+
512,
|
| 1033 |
+
512,
|
| 1034 |
+
512,
|
| 1035 |
+
512,
|
| 1036 |
+
512,
|
| 1037 |
+
512,
|
| 1038 |
+
512,
|
| 1039 |
+
512,
|
| 1040 |
+
512,
|
| 1041 |
+
512,
|
| 1042 |
+
512,
|
| 1043 |
+
512,
|
| 1044 |
+
512,
|
| 1045 |
+
512,
|
| 1046 |
+
512,
|
| 1047 |
+
512,
|
| 1048 |
+
512,
|
| 1049 |
+
512,
|
| 1050 |
+
512,
|
| 1051 |
+
512,
|
| 1052 |
+
512,
|
| 1053 |
+
512,
|
| 1054 |
+
512,
|
| 1055 |
+
512,
|
| 1056 |
+
512,
|
| 1057 |
+
512,
|
| 1058 |
+
512,
|
| 1059 |
+
512,
|
| 1060 |
+
512,
|
| 1061 |
+
512,
|
| 1062 |
+
512,
|
| 1063 |
+
512,
|
| 1064 |
+
512,
|
| 1065 |
+
512,
|
| 1066 |
+
512,
|
| 1067 |
+
512,
|
| 1068 |
+
512,
|
| 1069 |
+
512,
|
| 1070 |
+
512
|
| 1071 |
+
],
|
| 1072 |
+
[
|
| 1073 |
+
512,
|
| 1074 |
+
512,
|
| 1075 |
+
512,
|
| 1076 |
+
512,
|
| 1077 |
+
512,
|
| 1078 |
+
512,
|
| 1079 |
+
512,
|
| 1080 |
+
512,
|
| 1081 |
+
512,
|
| 1082 |
+
512,
|
| 1083 |
+
512,
|
| 1084 |
+
512,
|
| 1085 |
+
512,
|
| 1086 |
+
512,
|
| 1087 |
+
512,
|
| 1088 |
+
512,
|
| 1089 |
+
512,
|
| 1090 |
+
512,
|
| 1091 |
+
512,
|
| 1092 |
+
512,
|
| 1093 |
+
512,
|
| 1094 |
+
512,
|
| 1095 |
+
512,
|
| 1096 |
+
512,
|
| 1097 |
+
512,
|
| 1098 |
+
512,
|
| 1099 |
+
512,
|
| 1100 |
+
512,
|
| 1101 |
+
512,
|
| 1102 |
+
512,
|
| 1103 |
+
512,
|
| 1104 |
+
512,
|
| 1105 |
+
512,
|
| 1106 |
+
512,
|
| 1107 |
+
512,
|
| 1108 |
+
512,
|
| 1109 |
+
512,
|
| 1110 |
+
512,
|
| 1111 |
+
512,
|
| 1112 |
+
512,
|
| 1113 |
+
512,
|
| 1114 |
+
512,
|
| 1115 |
+
512,
|
| 1116 |
+
512,
|
| 1117 |
+
512,
|
| 1118 |
+
512,
|
| 1119 |
+
512,
|
| 1120 |
+
512,
|
| 1121 |
+
512,
|
| 1122 |
+
512,
|
| 1123 |
+
512,
|
| 1124 |
+
512,
|
| 1125 |
+
512,
|
| 1126 |
+
512,
|
| 1127 |
+
512,
|
| 1128 |
+
512,
|
| 1129 |
+
512,
|
| 1130 |
+
512,
|
| 1131 |
+
512,
|
| 1132 |
+
512,
|
| 1133 |
+
512,
|
| 1134 |
+
512,
|
| 1135 |
+
512,
|
| 1136 |
+
512
|
| 1137 |
+
],
|
| 1138 |
+
[
|
| 1139 |
+
512,
|
| 1140 |
+
512,
|
| 1141 |
+
512,
|
| 1142 |
+
512,
|
| 1143 |
+
512,
|
| 1144 |
+
512,
|
| 1145 |
+
512,
|
| 1146 |
+
512,
|
| 1147 |
+
512,
|
| 1148 |
+
512,
|
| 1149 |
+
512,
|
| 1150 |
+
512,
|
| 1151 |
+
512,
|
| 1152 |
+
512,
|
| 1153 |
+
512,
|
| 1154 |
+
512,
|
| 1155 |
+
512,
|
| 1156 |
+
512,
|
| 1157 |
+
512,
|
| 1158 |
+
512,
|
| 1159 |
+
512,
|
| 1160 |
+
512,
|
| 1161 |
+
512,
|
| 1162 |
+
512,
|
| 1163 |
+
512,
|
| 1164 |
+
512,
|
| 1165 |
+
512,
|
| 1166 |
+
512,
|
| 1167 |
+
512,
|
| 1168 |
+
512,
|
| 1169 |
+
512,
|
| 1170 |
+
512,
|
| 1171 |
+
512,
|
| 1172 |
+
512,
|
| 1173 |
+
512,
|
| 1174 |
+
512,
|
| 1175 |
+
512,
|
| 1176 |
+
512,
|
| 1177 |
+
512,
|
| 1178 |
+
512,
|
| 1179 |
+
512,
|
| 1180 |
+
512,
|
| 1181 |
+
512,
|
| 1182 |
+
512,
|
| 1183 |
+
512,
|
| 1184 |
+
512,
|
| 1185 |
+
512,
|
| 1186 |
+
512,
|
| 1187 |
+
512,
|
| 1188 |
+
512,
|
| 1189 |
+
512,
|
| 1190 |
+
512,
|
| 1191 |
+
512,
|
| 1192 |
+
512,
|
| 1193 |
+
512,
|
| 1194 |
+
512,
|
| 1195 |
+
512,
|
| 1196 |
+
512,
|
| 1197 |
+
512,
|
| 1198 |
+
512,
|
| 1199 |
+
512,
|
| 1200 |
+
512,
|
| 1201 |
+
512,
|
| 1202 |
+
512
|
| 1203 |
+
],
|
| 1204 |
+
[
|
| 1205 |
+
512,
|
| 1206 |
+
512,
|
| 1207 |
+
512,
|
| 1208 |
+
512,
|
| 1209 |
+
512,
|
| 1210 |
+
512,
|
| 1211 |
+
512,
|
| 1212 |
+
512,
|
| 1213 |
+
512,
|
| 1214 |
+
512,
|
| 1215 |
+
512,
|
| 1216 |
+
512,
|
| 1217 |
+
512,
|
| 1218 |
+
512,
|
| 1219 |
+
512,
|
| 1220 |
+
512,
|
| 1221 |
+
512,
|
| 1222 |
+
512,
|
| 1223 |
+
512,
|
| 1224 |
+
512,
|
| 1225 |
+
512,
|
| 1226 |
+
512,
|
| 1227 |
+
512,
|
| 1228 |
+
512,
|
| 1229 |
+
512,
|
| 1230 |
+
512,
|
| 1231 |
+
512,
|
| 1232 |
+
512,
|
| 1233 |
+
512,
|
| 1234 |
+
512,
|
| 1235 |
+
512,
|
| 1236 |
+
512,
|
| 1237 |
+
512,
|
| 1238 |
+
512,
|
| 1239 |
+
512,
|
| 1240 |
+
512,
|
| 1241 |
+
512,
|
| 1242 |
+
512,
|
| 1243 |
+
512,
|
| 1244 |
+
512,
|
| 1245 |
+
512,
|
| 1246 |
+
512,
|
| 1247 |
+
512,
|
| 1248 |
+
512,
|
| 1249 |
+
512,
|
| 1250 |
+
512,
|
| 1251 |
+
512,
|
| 1252 |
+
512,
|
| 1253 |
+
512,
|
| 1254 |
+
512,
|
| 1255 |
+
512,
|
| 1256 |
+
512,
|
| 1257 |
+
512,
|
| 1258 |
+
512,
|
| 1259 |
+
512,
|
| 1260 |
+
512,
|
| 1261 |
+
512,
|
| 1262 |
+
512,
|
| 1263 |
+
512,
|
| 1264 |
+
512,
|
| 1265 |
+
512,
|
| 1266 |
+
512,
|
| 1267 |
+
512,
|
| 1268 |
+
512
|
| 1269 |
+
],
|
| 1270 |
+
[
|
| 1271 |
+
512,
|
| 1272 |
+
512,
|
| 1273 |
+
512,
|
| 1274 |
+
512,
|
| 1275 |
+
512,
|
| 1276 |
+
512,
|
| 1277 |
+
512,
|
| 1278 |
+
512,
|
| 1279 |
+
512,
|
| 1280 |
+
512,
|
| 1281 |
+
512,
|
| 1282 |
+
512,
|
| 1283 |
+
512,
|
| 1284 |
+
512,
|
| 1285 |
+
512,
|
| 1286 |
+
512,
|
| 1287 |
+
512,
|
| 1288 |
+
512,
|
| 1289 |
+
512,
|
| 1290 |
+
512,
|
| 1291 |
+
512,
|
| 1292 |
+
512,
|
| 1293 |
+
512,
|
| 1294 |
+
512,
|
| 1295 |
+
512,
|
| 1296 |
+
512,
|
| 1297 |
+
512,
|
| 1298 |
+
512,
|
| 1299 |
+
512,
|
| 1300 |
+
512,
|
| 1301 |
+
512,
|
| 1302 |
+
512,
|
| 1303 |
+
512,
|
| 1304 |
+
512,
|
| 1305 |
+
512,
|
| 1306 |
+
512,
|
| 1307 |
+
512,
|
| 1308 |
+
512,
|
| 1309 |
+
512,
|
| 1310 |
+
512,
|
| 1311 |
+
512,
|
| 1312 |
+
512,
|
| 1313 |
+
512,
|
| 1314 |
+
512,
|
| 1315 |
+
512,
|
| 1316 |
+
512,
|
| 1317 |
+
512,
|
| 1318 |
+
512,
|
| 1319 |
+
512,
|
| 1320 |
+
512,
|
| 1321 |
+
512,
|
| 1322 |
+
512,
|
| 1323 |
+
512,
|
| 1324 |
+
512,
|
| 1325 |
+
512,
|
| 1326 |
+
512,
|
| 1327 |
+
512,
|
| 1328 |
+
512,
|
| 1329 |
+
512,
|
| 1330 |
+
512,
|
| 1331 |
+
512,
|
| 1332 |
+
512,
|
| 1333 |
+
512,
|
| 1334 |
+
512
|
| 1335 |
+
],
|
| 1336 |
+
[
|
| 1337 |
+
512,
|
| 1338 |
+
512,
|
| 1339 |
+
512,
|
| 1340 |
+
512,
|
| 1341 |
+
512,
|
| 1342 |
+
512,
|
| 1343 |
+
512,
|
| 1344 |
+
512,
|
| 1345 |
+
512,
|
| 1346 |
+
512,
|
| 1347 |
+
512,
|
| 1348 |
+
512,
|
| 1349 |
+
512,
|
| 1350 |
+
512,
|
| 1351 |
+
512,
|
| 1352 |
+
512,
|
| 1353 |
+
512,
|
| 1354 |
+
512,
|
| 1355 |
+
512,
|
| 1356 |
+
512,
|
| 1357 |
+
512,
|
| 1358 |
+
512,
|
| 1359 |
+
512,
|
| 1360 |
+
512,
|
| 1361 |
+
512,
|
| 1362 |
+
512,
|
| 1363 |
+
512,
|
| 1364 |
+
512,
|
| 1365 |
+
512,
|
| 1366 |
+
512,
|
| 1367 |
+
512,
|
| 1368 |
+
512,
|
| 1369 |
+
512,
|
| 1370 |
+
512,
|
| 1371 |
+
512,
|
| 1372 |
+
512,
|
| 1373 |
+
512,
|
| 1374 |
+
512,
|
| 1375 |
+
512,
|
| 1376 |
+
512,
|
| 1377 |
+
512,
|
| 1378 |
+
512,
|
| 1379 |
+
512,
|
| 1380 |
+
512,
|
| 1381 |
+
512,
|
| 1382 |
+
512,
|
| 1383 |
+
512,
|
| 1384 |
+
512,
|
| 1385 |
+
512,
|
| 1386 |
+
512,
|
| 1387 |
+
512,
|
| 1388 |
+
512,
|
| 1389 |
+
512,
|
| 1390 |
+
512,
|
| 1391 |
+
512,
|
| 1392 |
+
512,
|
| 1393 |
+
512,
|
| 1394 |
+
512,
|
| 1395 |
+
512,
|
| 1396 |
+
512,
|
| 1397 |
+
512,
|
| 1398 |
+
512,
|
| 1399 |
+
512,
|
| 1400 |
+
512
|
| 1401 |
+
],
|
| 1402 |
+
[
|
| 1403 |
+
512,
|
| 1404 |
+
512,
|
| 1405 |
+
512,
|
| 1406 |
+
512,
|
| 1407 |
+
512,
|
| 1408 |
+
512,
|
| 1409 |
+
512,
|
| 1410 |
+
512,
|
| 1411 |
+
512,
|
| 1412 |
+
512,
|
| 1413 |
+
512,
|
| 1414 |
+
512,
|
| 1415 |
+
512,
|
| 1416 |
+
512,
|
| 1417 |
+
512,
|
| 1418 |
+
512,
|
| 1419 |
+
512,
|
| 1420 |
+
512,
|
| 1421 |
+
512,
|
| 1422 |
+
512,
|
| 1423 |
+
512,
|
| 1424 |
+
512,
|
| 1425 |
+
512,
|
| 1426 |
+
512,
|
| 1427 |
+
512,
|
| 1428 |
+
512,
|
| 1429 |
+
512,
|
| 1430 |
+
512,
|
| 1431 |
+
512,
|
| 1432 |
+
512,
|
| 1433 |
+
512,
|
| 1434 |
+
512,
|
| 1435 |
+
512,
|
| 1436 |
+
512,
|
| 1437 |
+
512,
|
| 1438 |
+
512,
|
| 1439 |
+
512,
|
| 1440 |
+
512,
|
| 1441 |
+
512,
|
| 1442 |
+
512,
|
| 1443 |
+
512,
|
| 1444 |
+
512,
|
| 1445 |
+
512,
|
| 1446 |
+
512,
|
| 1447 |
+
512,
|
| 1448 |
+
512,
|
| 1449 |
+
512,
|
| 1450 |
+
512,
|
| 1451 |
+
512,
|
| 1452 |
+
512,
|
| 1453 |
+
512,
|
| 1454 |
+
512,
|
| 1455 |
+
512,
|
| 1456 |
+
512,
|
| 1457 |
+
512,
|
| 1458 |
+
512,
|
| 1459 |
+
512,
|
| 1460 |
+
512,
|
| 1461 |
+
512,
|
| 1462 |
+
512,
|
| 1463 |
+
512,
|
| 1464 |
+
512,
|
| 1465 |
+
512,
|
| 1466 |
+
512
|
| 1467 |
+
],
|
| 1468 |
+
[
|
| 1469 |
+
512,
|
| 1470 |
+
512,
|
| 1471 |
+
512,
|
| 1472 |
+
512,
|
| 1473 |
+
512,
|
| 1474 |
+
512,
|
| 1475 |
+
512,
|
| 1476 |
+
512,
|
| 1477 |
+
512,
|
| 1478 |
+
512,
|
| 1479 |
+
512,
|
| 1480 |
+
512,
|
| 1481 |
+
512,
|
| 1482 |
+
512,
|
| 1483 |
+
512,
|
| 1484 |
+
512,
|
| 1485 |
+
512,
|
| 1486 |
+
512,
|
| 1487 |
+
512,
|
| 1488 |
+
512,
|
| 1489 |
+
512,
|
| 1490 |
+
512,
|
| 1491 |
+
512,
|
| 1492 |
+
512,
|
| 1493 |
+
512,
|
| 1494 |
+
512,
|
| 1495 |
+
512,
|
| 1496 |
+
512,
|
| 1497 |
+
512,
|
| 1498 |
+
512,
|
| 1499 |
+
512,
|
| 1500 |
+
512,
|
| 1501 |
+
512,
|
| 1502 |
+
512,
|
| 1503 |
+
512,
|
| 1504 |
+
512,
|
| 1505 |
+
512,
|
| 1506 |
+
512,
|
| 1507 |
+
512,
|
| 1508 |
+
512,
|
| 1509 |
+
512,
|
| 1510 |
+
512,
|
| 1511 |
+
512,
|
| 1512 |
+
512,
|
| 1513 |
+
512,
|
| 1514 |
+
512,
|
| 1515 |
+
512,
|
| 1516 |
+
512,
|
| 1517 |
+
512,
|
| 1518 |
+
512,
|
| 1519 |
+
512,
|
| 1520 |
+
512,
|
| 1521 |
+
512,
|
| 1522 |
+
512,
|
| 1523 |
+
512,
|
| 1524 |
+
512,
|
| 1525 |
+
512,
|
| 1526 |
+
512,
|
| 1527 |
+
512,
|
| 1528 |
+
512,
|
| 1529 |
+
512,
|
| 1530 |
+
512,
|
| 1531 |
+
512,
|
| 1532 |
+
512
|
| 1533 |
+
],
|
| 1534 |
+
[
|
| 1535 |
+
512,
|
| 1536 |
+
512,
|
| 1537 |
+
512,
|
| 1538 |
+
512,
|
| 1539 |
+
512,
|
| 1540 |
+
512,
|
| 1541 |
+
512,
|
| 1542 |
+
512,
|
| 1543 |
+
512,
|
| 1544 |
+
512,
|
| 1545 |
+
512,
|
| 1546 |
+
512,
|
| 1547 |
+
512,
|
| 1548 |
+
512,
|
| 1549 |
+
512,
|
| 1550 |
+
512,
|
| 1551 |
+
512,
|
| 1552 |
+
512,
|
| 1553 |
+
512,
|
| 1554 |
+
512,
|
| 1555 |
+
512,
|
| 1556 |
+
512,
|
| 1557 |
+
512,
|
| 1558 |
+
512,
|
| 1559 |
+
512,
|
| 1560 |
+
512,
|
| 1561 |
+
512,
|
| 1562 |
+
512,
|
| 1563 |
+
512,
|
| 1564 |
+
512,
|
| 1565 |
+
512,
|
| 1566 |
+
512,
|
| 1567 |
+
512,
|
| 1568 |
+
512,
|
| 1569 |
+
512,
|
| 1570 |
+
512,
|
| 1571 |
+
512,
|
| 1572 |
+
512,
|
| 1573 |
+
512,
|
| 1574 |
+
512,
|
| 1575 |
+
512,
|
| 1576 |
+
512,
|
| 1577 |
+
512,
|
| 1578 |
+
512,
|
| 1579 |
+
512,
|
| 1580 |
+
512,
|
| 1581 |
+
512,
|
| 1582 |
+
512,
|
| 1583 |
+
512,
|
| 1584 |
+
512,
|
| 1585 |
+
512,
|
| 1586 |
+
512,
|
| 1587 |
+
512,
|
| 1588 |
+
512,
|
| 1589 |
+
512,
|
| 1590 |
+
512,
|
| 1591 |
+
512,
|
| 1592 |
+
512,
|
| 1593 |
+
512,
|
| 1594 |
+
512,
|
| 1595 |
+
512,
|
| 1596 |
+
512,
|
| 1597 |
+
512,
|
| 1598 |
+
512
|
| 1599 |
+
],
|
| 1600 |
+
[
|
| 1601 |
+
512,
|
| 1602 |
+
512,
|
| 1603 |
+
512,
|
| 1604 |
+
512,
|
| 1605 |
+
512,
|
| 1606 |
+
512,
|
| 1607 |
+
512,
|
| 1608 |
+
512,
|
| 1609 |
+
512,
|
| 1610 |
+
512,
|
| 1611 |
+
512,
|
| 1612 |
+
512,
|
| 1613 |
+
512,
|
| 1614 |
+
512,
|
| 1615 |
+
512,
|
| 1616 |
+
512,
|
| 1617 |
+
512,
|
| 1618 |
+
512,
|
| 1619 |
+
512,
|
| 1620 |
+
512,
|
| 1621 |
+
512,
|
| 1622 |
+
512,
|
| 1623 |
+
512,
|
| 1624 |
+
512,
|
| 1625 |
+
512,
|
| 1626 |
+
512,
|
| 1627 |
+
512,
|
| 1628 |
+
512,
|
| 1629 |
+
512,
|
| 1630 |
+
512,
|
| 1631 |
+
512,
|
| 1632 |
+
512,
|
| 1633 |
+
512,
|
| 1634 |
+
512,
|
| 1635 |
+
512,
|
| 1636 |
+
512,
|
| 1637 |
+
512,
|
| 1638 |
+
512,
|
| 1639 |
+
512,
|
| 1640 |
+
512,
|
| 1641 |
+
512,
|
| 1642 |
+
512,
|
| 1643 |
+
512,
|
| 1644 |
+
512,
|
| 1645 |
+
512,
|
| 1646 |
+
512,
|
| 1647 |
+
512,
|
| 1648 |
+
512,
|
| 1649 |
+
512,
|
| 1650 |
+
512,
|
| 1651 |
+
512,
|
| 1652 |
+
512,
|
| 1653 |
+
512,
|
| 1654 |
+
512,
|
| 1655 |
+
512,
|
| 1656 |
+
512,
|
| 1657 |
+
512,
|
| 1658 |
+
512,
|
| 1659 |
+
512,
|
| 1660 |
+
512,
|
| 1661 |
+
512,
|
| 1662 |
+
512,
|
| 1663 |
+
512,
|
| 1664 |
+
512
|
| 1665 |
+
],
|
| 1666 |
+
[
|
| 1667 |
+
512,
|
| 1668 |
+
512,
|
| 1669 |
+
512,
|
| 1670 |
+
512,
|
| 1671 |
+
512,
|
| 1672 |
+
512,
|
| 1673 |
+
512,
|
| 1674 |
+
512,
|
| 1675 |
+
512,
|
| 1676 |
+
512,
|
| 1677 |
+
512,
|
| 1678 |
+
512,
|
| 1679 |
+
512,
|
| 1680 |
+
512,
|
| 1681 |
+
512,
|
| 1682 |
+
512,
|
| 1683 |
+
512,
|
| 1684 |
+
512,
|
| 1685 |
+
512,
|
| 1686 |
+
512,
|
| 1687 |
+
512,
|
| 1688 |
+
512,
|
| 1689 |
+
512,
|
| 1690 |
+
512,
|
| 1691 |
+
512,
|
| 1692 |
+
512,
|
| 1693 |
+
512,
|
| 1694 |
+
512,
|
| 1695 |
+
512,
|
| 1696 |
+
512,
|
| 1697 |
+
512,
|
| 1698 |
+
512,
|
| 1699 |
+
512,
|
| 1700 |
+
512,
|
| 1701 |
+
512,
|
| 1702 |
+
512,
|
| 1703 |
+
512,
|
| 1704 |
+
512,
|
| 1705 |
+
512,
|
| 1706 |
+
512,
|
| 1707 |
+
512,
|
| 1708 |
+
512,
|
| 1709 |
+
512,
|
| 1710 |
+
512,
|
| 1711 |
+
512,
|
| 1712 |
+
512,
|
| 1713 |
+
512,
|
| 1714 |
+
512,
|
| 1715 |
+
512,
|
| 1716 |
+
512,
|
| 1717 |
+
512,
|
| 1718 |
+
512,
|
| 1719 |
+
512,
|
| 1720 |
+
512,
|
| 1721 |
+
512,
|
| 1722 |
+
512,
|
| 1723 |
+
512,
|
| 1724 |
+
512,
|
| 1725 |
+
512,
|
| 1726 |
+
512,
|
| 1727 |
+
512,
|
| 1728 |
+
512,
|
| 1729 |
+
512,
|
| 1730 |
+
512
|
| 1731 |
+
],
|
| 1732 |
+
[
|
| 1733 |
+
512,
|
| 1734 |
+
512,
|
| 1735 |
+
512,
|
| 1736 |
+
512,
|
| 1737 |
+
512,
|
| 1738 |
+
512,
|
| 1739 |
+
512,
|
| 1740 |
+
512,
|
| 1741 |
+
512,
|
| 1742 |
+
512,
|
| 1743 |
+
512,
|
| 1744 |
+
512,
|
| 1745 |
+
512,
|
| 1746 |
+
512,
|
| 1747 |
+
512,
|
| 1748 |
+
512,
|
| 1749 |
+
512,
|
| 1750 |
+
512,
|
| 1751 |
+
512,
|
| 1752 |
+
512,
|
| 1753 |
+
512,
|
| 1754 |
+
512,
|
| 1755 |
+
512,
|
| 1756 |
+
512,
|
| 1757 |
+
512,
|
| 1758 |
+
512,
|
| 1759 |
+
512,
|
| 1760 |
+
512,
|
| 1761 |
+
512,
|
| 1762 |
+
512,
|
| 1763 |
+
512,
|
| 1764 |
+
512,
|
| 1765 |
+
512,
|
| 1766 |
+
512,
|
| 1767 |
+
512,
|
| 1768 |
+
512,
|
| 1769 |
+
512,
|
| 1770 |
+
512,
|
| 1771 |
+
512,
|
| 1772 |
+
512,
|
| 1773 |
+
512,
|
| 1774 |
+
512,
|
| 1775 |
+
512,
|
| 1776 |
+
512,
|
| 1777 |
+
512,
|
| 1778 |
+
512,
|
| 1779 |
+
512,
|
| 1780 |
+
512,
|
| 1781 |
+
512,
|
| 1782 |
+
512,
|
| 1783 |
+
512,
|
| 1784 |
+
512,
|
| 1785 |
+
512,
|
| 1786 |
+
512,
|
| 1787 |
+
512,
|
| 1788 |
+
512,
|
| 1789 |
+
512,
|
| 1790 |
+
512,
|
| 1791 |
+
512,
|
| 1792 |
+
512,
|
| 1793 |
+
512,
|
| 1794 |
+
512,
|
| 1795 |
+
512,
|
| 1796 |
+
512
|
| 1797 |
+
],
|
| 1798 |
+
[
|
| 1799 |
+
512,
|
| 1800 |
+
512,
|
| 1801 |
+
512,
|
| 1802 |
+
512,
|
| 1803 |
+
512,
|
| 1804 |
+
512,
|
| 1805 |
+
512,
|
| 1806 |
+
512,
|
| 1807 |
+
512,
|
| 1808 |
+
512,
|
| 1809 |
+
512,
|
| 1810 |
+
512,
|
| 1811 |
+
512,
|
| 1812 |
+
512,
|
| 1813 |
+
512,
|
| 1814 |
+
512,
|
| 1815 |
+
512,
|
| 1816 |
+
512,
|
| 1817 |
+
512,
|
| 1818 |
+
512,
|
| 1819 |
+
512,
|
| 1820 |
+
512,
|
| 1821 |
+
512,
|
| 1822 |
+
512,
|
| 1823 |
+
512,
|
| 1824 |
+
512,
|
| 1825 |
+
512,
|
| 1826 |
+
512,
|
| 1827 |
+
512,
|
| 1828 |
+
512,
|
| 1829 |
+
512,
|
| 1830 |
+
512,
|
| 1831 |
+
512,
|
| 1832 |
+
512,
|
| 1833 |
+
512,
|
| 1834 |
+
512,
|
| 1835 |
+
512,
|
| 1836 |
+
512,
|
| 1837 |
+
512,
|
| 1838 |
+
512,
|
| 1839 |
+
512,
|
| 1840 |
+
512,
|
| 1841 |
+
512,
|
| 1842 |
+
512,
|
| 1843 |
+
512,
|
| 1844 |
+
512,
|
| 1845 |
+
512,
|
| 1846 |
+
512,
|
| 1847 |
+
512,
|
| 1848 |
+
512,
|
| 1849 |
+
512,
|
| 1850 |
+
512,
|
| 1851 |
+
512,
|
| 1852 |
+
512,
|
| 1853 |
+
512,
|
| 1854 |
+
512,
|
| 1855 |
+
512,
|
| 1856 |
+
512,
|
| 1857 |
+
512,
|
| 1858 |
+
512,
|
| 1859 |
+
512,
|
| 1860 |
+
512,
|
| 1861 |
+
512,
|
| 1862 |
+
512
|
| 1863 |
+
],
|
| 1864 |
+
[
|
| 1865 |
+
512,
|
| 1866 |
+
512,
|
| 1867 |
+
512,
|
| 1868 |
+
512,
|
| 1869 |
+
512,
|
| 1870 |
+
512,
|
| 1871 |
+
512,
|
| 1872 |
+
512,
|
| 1873 |
+
512,
|
| 1874 |
+
512,
|
| 1875 |
+
512,
|
| 1876 |
+
512,
|
| 1877 |
+
512,
|
| 1878 |
+
512,
|
| 1879 |
+
512,
|
| 1880 |
+
512,
|
| 1881 |
+
512,
|
| 1882 |
+
512,
|
| 1883 |
+
512,
|
| 1884 |
+
512,
|
| 1885 |
+
512,
|
| 1886 |
+
512,
|
| 1887 |
+
512,
|
| 1888 |
+
512,
|
| 1889 |
+
512,
|
| 1890 |
+
512,
|
| 1891 |
+
512,
|
| 1892 |
+
512,
|
| 1893 |
+
512,
|
| 1894 |
+
512,
|
| 1895 |
+
512,
|
| 1896 |
+
512,
|
| 1897 |
+
512,
|
| 1898 |
+
512,
|
| 1899 |
+
512,
|
| 1900 |
+
512,
|
| 1901 |
+
512,
|
| 1902 |
+
512,
|
| 1903 |
+
512,
|
| 1904 |
+
512,
|
| 1905 |
+
512,
|
| 1906 |
+
512,
|
| 1907 |
+
512,
|
| 1908 |
+
512,
|
| 1909 |
+
512,
|
| 1910 |
+
512,
|
| 1911 |
+
512,
|
| 1912 |
+
512,
|
| 1913 |
+
512,
|
| 1914 |
+
512,
|
| 1915 |
+
512,
|
| 1916 |
+
512,
|
| 1917 |
+
512,
|
| 1918 |
+
512,
|
| 1919 |
+
512,
|
| 1920 |
+
512,
|
| 1921 |
+
512,
|
| 1922 |
+
512,
|
| 1923 |
+
512,
|
| 1924 |
+
512,
|
| 1925 |
+
512,
|
| 1926 |
+
512,
|
| 1927 |
+
512,
|
| 1928 |
+
512
|
| 1929 |
+
],
|
| 1930 |
+
[
|
| 1931 |
+
512,
|
| 1932 |
+
512,
|
| 1933 |
+
512,
|
| 1934 |
+
512,
|
| 1935 |
+
512,
|
| 1936 |
+
512,
|
| 1937 |
+
512,
|
| 1938 |
+
512,
|
| 1939 |
+
512,
|
| 1940 |
+
512,
|
| 1941 |
+
512,
|
| 1942 |
+
512,
|
| 1943 |
+
512,
|
| 1944 |
+
512,
|
| 1945 |
+
512,
|
| 1946 |
+
512,
|
| 1947 |
+
512,
|
| 1948 |
+
512,
|
| 1949 |
+
512,
|
| 1950 |
+
512,
|
| 1951 |
+
512,
|
| 1952 |
+
512,
|
| 1953 |
+
512,
|
| 1954 |
+
512,
|
| 1955 |
+
512,
|
| 1956 |
+
512,
|
| 1957 |
+
512,
|
| 1958 |
+
512,
|
| 1959 |
+
512,
|
| 1960 |
+
512,
|
| 1961 |
+
512,
|
| 1962 |
+
512,
|
| 1963 |
+
512,
|
| 1964 |
+
512,
|
| 1965 |
+
512,
|
| 1966 |
+
512,
|
| 1967 |
+
512,
|
| 1968 |
+
512,
|
| 1969 |
+
512,
|
| 1970 |
+
512,
|
| 1971 |
+
512,
|
| 1972 |
+
512,
|
| 1973 |
+
512,
|
| 1974 |
+
512,
|
| 1975 |
+
512,
|
| 1976 |
+
512,
|
| 1977 |
+
512,
|
| 1978 |
+
512,
|
| 1979 |
+
512,
|
| 1980 |
+
512,
|
| 1981 |
+
512,
|
| 1982 |
+
512,
|
| 1983 |
+
512,
|
| 1984 |
+
512,
|
| 1985 |
+
512,
|
| 1986 |
+
512,
|
| 1987 |
+
512,
|
| 1988 |
+
512,
|
| 1989 |
+
512,
|
| 1990 |
+
512,
|
| 1991 |
+
512,
|
| 1992 |
+
512,
|
| 1993 |
+
512,
|
| 1994 |
+
512
|
| 1995 |
+
],
|
| 1996 |
+
[
|
| 1997 |
+
512,
|
| 1998 |
+
512,
|
| 1999 |
+
512,
|
| 2000 |
+
512,
|
| 2001 |
+
512,
|
| 2002 |
+
512,
|
| 2003 |
+
512,
|
| 2004 |
+
512,
|
| 2005 |
+
512,
|
| 2006 |
+
512,
|
| 2007 |
+
512,
|
| 2008 |
+
512,
|
| 2009 |
+
512,
|
| 2010 |
+
512,
|
| 2011 |
+
512,
|
| 2012 |
+
512,
|
| 2013 |
+
512,
|
| 2014 |
+
512,
|
| 2015 |
+
512,
|
| 2016 |
+
512,
|
| 2017 |
+
512,
|
| 2018 |
+
512,
|
| 2019 |
+
512,
|
| 2020 |
+
512,
|
| 2021 |
+
512,
|
| 2022 |
+
512,
|
| 2023 |
+
512,
|
| 2024 |
+
512,
|
| 2025 |
+
512,
|
| 2026 |
+
512,
|
| 2027 |
+
512,
|
| 2028 |
+
512,
|
| 2029 |
+
512,
|
| 2030 |
+
512,
|
| 2031 |
+
512,
|
| 2032 |
+
512,
|
| 2033 |
+
512,
|
| 2034 |
+
512,
|
| 2035 |
+
512,
|
| 2036 |
+
512,
|
| 2037 |
+
512,
|
| 2038 |
+
512,
|
| 2039 |
+
512,
|
| 2040 |
+
512,
|
| 2041 |
+
512,
|
| 2042 |
+
512,
|
| 2043 |
+
512,
|
| 2044 |
+
512,
|
| 2045 |
+
512,
|
| 2046 |
+
512,
|
| 2047 |
+
512,
|
| 2048 |
+
512,
|
| 2049 |
+
512,
|
| 2050 |
+
512,
|
| 2051 |
+
512,
|
| 2052 |
+
512,
|
| 2053 |
+
512,
|
| 2054 |
+
512,
|
| 2055 |
+
512,
|
| 2056 |
+
512,
|
| 2057 |
+
512,
|
| 2058 |
+
512,
|
| 2059 |
+
512,
|
| 2060 |
+
512
|
| 2061 |
+
],
|
| 2062 |
+
[
|
| 2063 |
+
512,
|
| 2064 |
+
512,
|
| 2065 |
+
512,
|
| 2066 |
+
512,
|
| 2067 |
+
512,
|
| 2068 |
+
512,
|
| 2069 |
+
512,
|
| 2070 |
+
512,
|
| 2071 |
+
512,
|
| 2072 |
+
512,
|
| 2073 |
+
512,
|
| 2074 |
+
512,
|
| 2075 |
+
512,
|
| 2076 |
+
512,
|
| 2077 |
+
512,
|
| 2078 |
+
512,
|
| 2079 |
+
512,
|
| 2080 |
+
512,
|
| 2081 |
+
512,
|
| 2082 |
+
512,
|
| 2083 |
+
512,
|
| 2084 |
+
512,
|
| 2085 |
+
512,
|
| 2086 |
+
512,
|
| 2087 |
+
512,
|
| 2088 |
+
512,
|
| 2089 |
+
512,
|
| 2090 |
+
512,
|
| 2091 |
+
512,
|
| 2092 |
+
512,
|
| 2093 |
+
512,
|
| 2094 |
+
512,
|
| 2095 |
+
512,
|
| 2096 |
+
512,
|
| 2097 |
+
512,
|
| 2098 |
+
512,
|
| 2099 |
+
512,
|
| 2100 |
+
512,
|
| 2101 |
+
512,
|
| 2102 |
+
512,
|
| 2103 |
+
512,
|
| 2104 |
+
512,
|
| 2105 |
+
512,
|
| 2106 |
+
512,
|
| 2107 |
+
512,
|
| 2108 |
+
512,
|
| 2109 |
+
512,
|
| 2110 |
+
512,
|
| 2111 |
+
512,
|
| 2112 |
+
512,
|
| 2113 |
+
512,
|
| 2114 |
+
512,
|
| 2115 |
+
512,
|
| 2116 |
+
512,
|
| 2117 |
+
512,
|
| 2118 |
+
512,
|
| 2119 |
+
512,
|
| 2120 |
+
512,
|
| 2121 |
+
512,
|
| 2122 |
+
512,
|
| 2123 |
+
512,
|
| 2124 |
+
512,
|
| 2125 |
+
512,
|
| 2126 |
+
512
|
| 2127 |
+
],
|
| 2128 |
+
[
|
| 2129 |
+
512,
|
| 2130 |
+
512,
|
| 2131 |
+
512,
|
| 2132 |
+
512,
|
| 2133 |
+
512,
|
| 2134 |
+
512,
|
| 2135 |
+
512,
|
| 2136 |
+
512,
|
| 2137 |
+
512,
|
| 2138 |
+
512,
|
| 2139 |
+
512,
|
| 2140 |
+
512,
|
| 2141 |
+
512,
|
| 2142 |
+
512,
|
| 2143 |
+
512,
|
| 2144 |
+
512,
|
| 2145 |
+
512,
|
| 2146 |
+
512,
|
| 2147 |
+
512,
|
| 2148 |
+
512,
|
| 2149 |
+
512,
|
| 2150 |
+
512,
|
| 2151 |
+
512,
|
| 2152 |
+
512,
|
| 2153 |
+
512,
|
| 2154 |
+
512,
|
| 2155 |
+
512,
|
| 2156 |
+
512,
|
| 2157 |
+
512,
|
| 2158 |
+
512,
|
| 2159 |
+
512,
|
| 2160 |
+
512,
|
| 2161 |
+
512,
|
| 2162 |
+
512,
|
| 2163 |
+
512,
|
| 2164 |
+
512,
|
| 2165 |
+
512,
|
| 2166 |
+
512,
|
| 2167 |
+
512,
|
| 2168 |
+
512,
|
| 2169 |
+
512,
|
| 2170 |
+
512,
|
| 2171 |
+
512,
|
| 2172 |
+
512,
|
| 2173 |
+
512,
|
| 2174 |
+
512,
|
| 2175 |
+
512,
|
| 2176 |
+
512,
|
| 2177 |
+
512,
|
| 2178 |
+
512,
|
| 2179 |
+
512,
|
| 2180 |
+
512,
|
| 2181 |
+
512,
|
| 2182 |
+
512,
|
| 2183 |
+
512,
|
| 2184 |
+
512,
|
| 2185 |
+
512,
|
| 2186 |
+
512,
|
| 2187 |
+
512,
|
| 2188 |
+
512,
|
| 2189 |
+
512,
|
| 2190 |
+
512,
|
| 2191 |
+
512,
|
| 2192 |
+
512
|
| 2193 |
+
],
|
| 2194 |
+
[
|
| 2195 |
+
512,
|
| 2196 |
+
512,
|
| 2197 |
+
512,
|
| 2198 |
+
512,
|
| 2199 |
+
512,
|
| 2200 |
+
512,
|
| 2201 |
+
512,
|
| 2202 |
+
512,
|
| 2203 |
+
512,
|
| 2204 |
+
512,
|
| 2205 |
+
512,
|
| 2206 |
+
512,
|
| 2207 |
+
512,
|
| 2208 |
+
512,
|
| 2209 |
+
512,
|
| 2210 |
+
512,
|
| 2211 |
+
512,
|
| 2212 |
+
512,
|
| 2213 |
+
512,
|
| 2214 |
+
512,
|
| 2215 |
+
512,
|
| 2216 |
+
512,
|
| 2217 |
+
512,
|
| 2218 |
+
512,
|
| 2219 |
+
512,
|
| 2220 |
+
512,
|
| 2221 |
+
512,
|
| 2222 |
+
512,
|
| 2223 |
+
512,
|
| 2224 |
+
512,
|
| 2225 |
+
512,
|
| 2226 |
+
512,
|
| 2227 |
+
512,
|
| 2228 |
+
512,
|
| 2229 |
+
512,
|
| 2230 |
+
512,
|
| 2231 |
+
512,
|
| 2232 |
+
512,
|
| 2233 |
+
512,
|
| 2234 |
+
512,
|
| 2235 |
+
512,
|
| 2236 |
+
512,
|
| 2237 |
+
512,
|
| 2238 |
+
512,
|
| 2239 |
+
512,
|
| 2240 |
+
512,
|
| 2241 |
+
512,
|
| 2242 |
+
512,
|
| 2243 |
+
512,
|
| 2244 |
+
512,
|
| 2245 |
+
512,
|
| 2246 |
+
512,
|
| 2247 |
+
512,
|
| 2248 |
+
512,
|
| 2249 |
+
512,
|
| 2250 |
+
512,
|
| 2251 |
+
512,
|
| 2252 |
+
512,
|
| 2253 |
+
512,
|
| 2254 |
+
512,
|
| 2255 |
+
512,
|
| 2256 |
+
512,
|
| 2257 |
+
512,
|
| 2258 |
+
512
|
| 2259 |
+
],
|
| 2260 |
+
[
|
| 2261 |
+
512,
|
| 2262 |
+
512,
|
| 2263 |
+
512,
|
| 2264 |
+
512,
|
| 2265 |
+
512,
|
| 2266 |
+
512,
|
| 2267 |
+
512,
|
| 2268 |
+
512,
|
| 2269 |
+
512,
|
| 2270 |
+
512,
|
| 2271 |
+
512,
|
| 2272 |
+
512,
|
| 2273 |
+
512,
|
| 2274 |
+
512,
|
| 2275 |
+
512,
|
| 2276 |
+
512,
|
| 2277 |
+
512,
|
| 2278 |
+
512,
|
| 2279 |
+
512,
|
| 2280 |
+
512,
|
| 2281 |
+
512,
|
| 2282 |
+
512,
|
| 2283 |
+
512,
|
| 2284 |
+
512,
|
| 2285 |
+
512,
|
| 2286 |
+
512,
|
| 2287 |
+
512,
|
| 2288 |
+
512,
|
| 2289 |
+
512,
|
| 2290 |
+
512,
|
| 2291 |
+
512,
|
| 2292 |
+
512,
|
| 2293 |
+
512,
|
| 2294 |
+
512,
|
| 2295 |
+
512,
|
| 2296 |
+
512,
|
| 2297 |
+
512,
|
| 2298 |
+
512,
|
| 2299 |
+
512,
|
| 2300 |
+
512,
|
| 2301 |
+
512,
|
| 2302 |
+
512,
|
| 2303 |
+
512,
|
| 2304 |
+
512,
|
| 2305 |
+
512,
|
| 2306 |
+
512,
|
| 2307 |
+
512,
|
| 2308 |
+
512,
|
| 2309 |
+
512,
|
| 2310 |
+
512,
|
| 2311 |
+
512,
|
| 2312 |
+
512,
|
| 2313 |
+
512,
|
| 2314 |
+
512,
|
| 2315 |
+
512,
|
| 2316 |
+
512,
|
| 2317 |
+
512,
|
| 2318 |
+
512,
|
| 2319 |
+
512,
|
| 2320 |
+
512,
|
| 2321 |
+
512,
|
| 2322 |
+
512,
|
| 2323 |
+
512,
|
| 2324 |
+
512
|
| 2325 |
+
],
|
| 2326 |
+
[
|
| 2327 |
+
512,
|
| 2328 |
+
512,
|
| 2329 |
+
512,
|
| 2330 |
+
512,
|
| 2331 |
+
512,
|
| 2332 |
+
512,
|
| 2333 |
+
512,
|
| 2334 |
+
512,
|
| 2335 |
+
512,
|
| 2336 |
+
512,
|
| 2337 |
+
512,
|
| 2338 |
+
512,
|
| 2339 |
+
512,
|
| 2340 |
+
512,
|
| 2341 |
+
512,
|
| 2342 |
+
512,
|
| 2343 |
+
512,
|
| 2344 |
+
512,
|
| 2345 |
+
512,
|
| 2346 |
+
512,
|
| 2347 |
+
512,
|
| 2348 |
+
512,
|
| 2349 |
+
512,
|
| 2350 |
+
512,
|
| 2351 |
+
512,
|
| 2352 |
+
512,
|
| 2353 |
+
512,
|
| 2354 |
+
512,
|
| 2355 |
+
512,
|
| 2356 |
+
512,
|
| 2357 |
+
512,
|
| 2358 |
+
512,
|
| 2359 |
+
512,
|
| 2360 |
+
512,
|
| 2361 |
+
512,
|
| 2362 |
+
512,
|
| 2363 |
+
512,
|
| 2364 |
+
512,
|
| 2365 |
+
512,
|
| 2366 |
+
512,
|
| 2367 |
+
512,
|
| 2368 |
+
512,
|
| 2369 |
+
512,
|
| 2370 |
+
512,
|
| 2371 |
+
512,
|
| 2372 |
+
512,
|
| 2373 |
+
512,
|
| 2374 |
+
512,
|
| 2375 |
+
512,
|
| 2376 |
+
512,
|
| 2377 |
+
512,
|
| 2378 |
+
512,
|
| 2379 |
+
512,
|
| 2380 |
+
512,
|
| 2381 |
+
512,
|
| 2382 |
+
512,
|
| 2383 |
+
512,
|
| 2384 |
+
512,
|
| 2385 |
+
512,
|
| 2386 |
+
512,
|
| 2387 |
+
512,
|
| 2388 |
+
512,
|
| 2389 |
+
512,
|
| 2390 |
+
512
|
| 2391 |
+
],
|
| 2392 |
+
[
|
| 2393 |
+
512,
|
| 2394 |
+
512,
|
| 2395 |
+
512,
|
| 2396 |
+
512,
|
| 2397 |
+
512,
|
| 2398 |
+
512,
|
| 2399 |
+
512,
|
| 2400 |
+
512,
|
| 2401 |
+
512,
|
| 2402 |
+
512,
|
| 2403 |
+
512,
|
| 2404 |
+
512,
|
| 2405 |
+
512,
|
| 2406 |
+
512,
|
| 2407 |
+
512,
|
| 2408 |
+
512,
|
| 2409 |
+
512,
|
| 2410 |
+
512,
|
| 2411 |
+
512,
|
| 2412 |
+
512,
|
| 2413 |
+
512,
|
| 2414 |
+
512,
|
| 2415 |
+
512,
|
| 2416 |
+
512,
|
| 2417 |
+
512,
|
| 2418 |
+
512,
|
| 2419 |
+
512,
|
| 2420 |
+
512,
|
| 2421 |
+
512,
|
| 2422 |
+
512,
|
| 2423 |
+
512,
|
| 2424 |
+
512,
|
| 2425 |
+
512,
|
| 2426 |
+
512,
|
| 2427 |
+
512,
|
| 2428 |
+
512,
|
| 2429 |
+
512,
|
| 2430 |
+
512,
|
| 2431 |
+
512,
|
| 2432 |
+
512,
|
| 2433 |
+
512,
|
| 2434 |
+
512,
|
| 2435 |
+
512,
|
| 2436 |
+
512,
|
| 2437 |
+
512,
|
| 2438 |
+
512,
|
| 2439 |
+
512,
|
| 2440 |
+
512,
|
| 2441 |
+
512,
|
| 2442 |
+
512,
|
| 2443 |
+
512,
|
| 2444 |
+
512,
|
| 2445 |
+
512,
|
| 2446 |
+
512,
|
| 2447 |
+
512,
|
| 2448 |
+
512,
|
| 2449 |
+
512,
|
| 2450 |
+
512,
|
| 2451 |
+
512,
|
| 2452 |
+
512,
|
| 2453 |
+
512,
|
| 2454 |
+
512,
|
| 2455 |
+
512,
|
| 2456 |
+
512
|
| 2457 |
+
],
|
| 2458 |
+
[
|
| 2459 |
+
512,
|
| 2460 |
+
512,
|
| 2461 |
+
512,
|
| 2462 |
+
512,
|
| 2463 |
+
512,
|
| 2464 |
+
512,
|
| 2465 |
+
512,
|
| 2466 |
+
512,
|
| 2467 |
+
512,
|
| 2468 |
+
512,
|
| 2469 |
+
512,
|
| 2470 |
+
512,
|
| 2471 |
+
512,
|
| 2472 |
+
512,
|
| 2473 |
+
512,
|
| 2474 |
+
512,
|
| 2475 |
+
512,
|
| 2476 |
+
512,
|
| 2477 |
+
512,
|
| 2478 |
+
512,
|
| 2479 |
+
512,
|
| 2480 |
+
512,
|
| 2481 |
+
512,
|
| 2482 |
+
512,
|
| 2483 |
+
512,
|
| 2484 |
+
512,
|
| 2485 |
+
512,
|
| 2486 |
+
512,
|
| 2487 |
+
512,
|
| 2488 |
+
512,
|
| 2489 |
+
512,
|
| 2490 |
+
512,
|
| 2491 |
+
512,
|
| 2492 |
+
512,
|
| 2493 |
+
512,
|
| 2494 |
+
512,
|
| 2495 |
+
512,
|
| 2496 |
+
512,
|
| 2497 |
+
512,
|
| 2498 |
+
512,
|
| 2499 |
+
512,
|
| 2500 |
+
512,
|
| 2501 |
+
512,
|
| 2502 |
+
512,
|
| 2503 |
+
512,
|
| 2504 |
+
512,
|
| 2505 |
+
512,
|
| 2506 |
+
512,
|
| 2507 |
+
512,
|
| 2508 |
+
512,
|
| 2509 |
+
512,
|
| 2510 |
+
512,
|
| 2511 |
+
512,
|
| 2512 |
+
512,
|
| 2513 |
+
512,
|
| 2514 |
+
512,
|
| 2515 |
+
512,
|
| 2516 |
+
512,
|
| 2517 |
+
512,
|
| 2518 |
+
512,
|
| 2519 |
+
512,
|
| 2520 |
+
512,
|
| 2521 |
+
512,
|
| 2522 |
+
512
|
| 2523 |
+
],
|
| 2524 |
+
[
|
| 2525 |
+
512,
|
| 2526 |
+
512,
|
| 2527 |
+
512,
|
| 2528 |
+
512,
|
| 2529 |
+
512,
|
| 2530 |
+
512,
|
| 2531 |
+
512,
|
| 2532 |
+
512,
|
| 2533 |
+
512,
|
| 2534 |
+
512,
|
| 2535 |
+
512,
|
| 2536 |
+
512,
|
| 2537 |
+
512,
|
| 2538 |
+
512,
|
| 2539 |
+
512,
|
| 2540 |
+
512,
|
| 2541 |
+
512,
|
| 2542 |
+
512,
|
| 2543 |
+
512,
|
| 2544 |
+
512,
|
| 2545 |
+
512,
|
| 2546 |
+
512,
|
| 2547 |
+
512,
|
| 2548 |
+
512,
|
| 2549 |
+
512,
|
| 2550 |
+
512,
|
| 2551 |
+
512,
|
| 2552 |
+
512,
|
| 2553 |
+
512,
|
| 2554 |
+
512,
|
| 2555 |
+
512,
|
| 2556 |
+
512,
|
| 2557 |
+
512,
|
| 2558 |
+
512,
|
| 2559 |
+
512,
|
| 2560 |
+
512,
|
| 2561 |
+
512,
|
| 2562 |
+
512,
|
| 2563 |
+
512,
|
| 2564 |
+
512,
|
| 2565 |
+
512,
|
| 2566 |
+
512,
|
| 2567 |
+
512,
|
| 2568 |
+
512,
|
| 2569 |
+
512,
|
| 2570 |
+
512,
|
| 2571 |
+
512,
|
| 2572 |
+
512,
|
| 2573 |
+
512,
|
| 2574 |
+
512,
|
| 2575 |
+
512,
|
| 2576 |
+
512,
|
| 2577 |
+
512,
|
| 2578 |
+
512,
|
| 2579 |
+
512,
|
| 2580 |
+
512,
|
| 2581 |
+
512,
|
| 2582 |
+
512,
|
| 2583 |
+
512,
|
| 2584 |
+
512,
|
| 2585 |
+
512,
|
| 2586 |
+
512,
|
| 2587 |
+
512,
|
| 2588 |
+
512
|
| 2589 |
+
],
|
| 2590 |
+
[
|
| 2591 |
+
512,
|
| 2592 |
+
512,
|
| 2593 |
+
512,
|
| 2594 |
+
512,
|
| 2595 |
+
512,
|
| 2596 |
+
512,
|
| 2597 |
+
512,
|
| 2598 |
+
512,
|
| 2599 |
+
512,
|
| 2600 |
+
512,
|
| 2601 |
+
512,
|
| 2602 |
+
512,
|
| 2603 |
+
512,
|
| 2604 |
+
512,
|
| 2605 |
+
512,
|
| 2606 |
+
512,
|
| 2607 |
+
512,
|
| 2608 |
+
512,
|
| 2609 |
+
512,
|
| 2610 |
+
512,
|
| 2611 |
+
512,
|
| 2612 |
+
512,
|
| 2613 |
+
512,
|
| 2614 |
+
512,
|
| 2615 |
+
512,
|
| 2616 |
+
512,
|
| 2617 |
+
512,
|
| 2618 |
+
512,
|
| 2619 |
+
512,
|
| 2620 |
+
512,
|
| 2621 |
+
512,
|
| 2622 |
+
512,
|
| 2623 |
+
512,
|
| 2624 |
+
512,
|
| 2625 |
+
512,
|
| 2626 |
+
512,
|
| 2627 |
+
512,
|
| 2628 |
+
512,
|
| 2629 |
+
512,
|
| 2630 |
+
512,
|
| 2631 |
+
512,
|
| 2632 |
+
512,
|
| 2633 |
+
512,
|
| 2634 |
+
512,
|
| 2635 |
+
512,
|
| 2636 |
+
512,
|
| 2637 |
+
512,
|
| 2638 |
+
512,
|
| 2639 |
+
512,
|
| 2640 |
+
512,
|
| 2641 |
+
512,
|
| 2642 |
+
512,
|
| 2643 |
+
512,
|
| 2644 |
+
512,
|
| 2645 |
+
512,
|
| 2646 |
+
512,
|
| 2647 |
+
512,
|
| 2648 |
+
512,
|
| 2649 |
+
512,
|
| 2650 |
+
512,
|
| 2651 |
+
512,
|
| 2652 |
+
512,
|
| 2653 |
+
512,
|
| 2654 |
+
512
|
| 2655 |
+
]
|
| 2656 |
+
],
|
| 2657 |
+
"full_attention_interval": 4,
|
| 2658 |
+
"glean_metadata": {
|
| 2659 |
+
"keep_fraction": 0.25,
|
| 2660 |
+
"method": "REAP whole-expert prune (reap), uniform per-layer keep",
|
| 2661 |
+
"score": {
|
| 2662 |
+
"alpha": 1,
|
| 2663 |
+
"b": 1.0,
|
| 2664 |
+
"beta": 1
|
| 2665 |
+
},
|
| 2666 |
+
"source_model": "Qwen/Qwen3.6-35B-A3B",
|
| 2667 |
+
"stats_path": "outputs/qwen35_stats1024.pt"
|
| 2668 |
+
},
|
| 2669 |
+
"head_dim": 256,
|
| 2670 |
+
"hidden_act": "silu",
|
| 2671 |
+
"hidden_size": 2048,
|
| 2672 |
+
"initializer_range": 0.02,
|
| 2673 |
+
"layer_types": [
|
| 2674 |
+
"linear_attention",
|
| 2675 |
+
"linear_attention",
|
| 2676 |
+
"linear_attention",
|
| 2677 |
+
"full_attention",
|
| 2678 |
+
"linear_attention",
|
| 2679 |
+
"linear_attention",
|
| 2680 |
+
"linear_attention",
|
| 2681 |
+
"full_attention",
|
| 2682 |
+
"linear_attention",
|
| 2683 |
+
"linear_attention",
|
| 2684 |
+
"linear_attention",
|
| 2685 |
+
"full_attention",
|
| 2686 |
+
"linear_attention",
|
| 2687 |
+
"linear_attention",
|
| 2688 |
+
"linear_attention",
|
| 2689 |
+
"full_attention",
|
| 2690 |
+
"linear_attention",
|
| 2691 |
+
"linear_attention",
|
| 2692 |
+
"linear_attention",
|
| 2693 |
+
"full_attention",
|
| 2694 |
+
"linear_attention",
|
| 2695 |
+
"linear_attention",
|
| 2696 |
+
"linear_attention",
|
| 2697 |
+
"full_attention",
|
| 2698 |
+
"linear_attention",
|
| 2699 |
+
"linear_attention",
|
| 2700 |
+
"linear_attention",
|
| 2701 |
+
"full_attention",
|
| 2702 |
+
"linear_attention",
|
| 2703 |
+
"linear_attention",
|
| 2704 |
+
"linear_attention",
|
| 2705 |
+
"full_attention",
|
| 2706 |
+
"linear_attention",
|
| 2707 |
+
"linear_attention",
|
| 2708 |
+
"linear_attention",
|
| 2709 |
+
"full_attention",
|
| 2710 |
+
"linear_attention",
|
| 2711 |
+
"linear_attention",
|
| 2712 |
+
"linear_attention",
|
| 2713 |
+
"full_attention"
|
| 2714 |
+
],
|
| 2715 |
+
"linear_conv_kernel_dim": 4,
|
| 2716 |
+
"linear_key_head_dim": 128,
|
| 2717 |
+
"linear_num_key_heads": 16,
|
| 2718 |
+
"linear_num_value_heads": 32,
|
| 2719 |
+
"linear_value_head_dim": 128,
|
| 2720 |
+
"mamba_ssm_dtype": "float32",
|
| 2721 |
+
"max_position_embeddings": 262144,
|
| 2722 |
+
"model_type": "pruned_qwen3_5_moe",
|
| 2723 |
+
"moe_intermediate_size": 512,
|
| 2724 |
+
"mtp_num_hidden_layers": 1,
|
| 2725 |
+
"mtp_use_dedicated_embeddings": false,
|
| 2726 |
+
"num_attention_heads": 16,
|
| 2727 |
+
"num_experts": 256,
|
| 2728 |
+
"num_experts_per_tok": 8,
|
| 2729 |
+
"num_hidden_layers": 40,
|
| 2730 |
+
"num_key_value_heads": 2,
|
| 2731 |
+
"output_router_logits": false,
|
| 2732 |
+
"pad_token_id": null,
|
| 2733 |
+
"partial_rotary_factor": 0.25,
|
| 2734 |
+
"rms_norm_eps": 1e-06,
|
| 2735 |
+
"rope_parameters": {
|
| 2736 |
+
"mrope_interleaved": true,
|
| 2737 |
+
"mrope_section": [
|
| 2738 |
+
11,
|
| 2739 |
+
11,
|
| 2740 |
+
10
|
| 2741 |
+
],
|
| 2742 |
+
"partial_rotary_factor": 0.25,
|
| 2743 |
+
"rope_theta": 10000000,
|
| 2744 |
+
"rope_type": "default"
|
| 2745 |
+
},
|
| 2746 |
+
"router_aux_loss_coef": 0.001,
|
| 2747 |
+
"shared_expert_intermediate_size": 512,
|
| 2748 |
+
"tie_word_embeddings": false,
|
| 2749 |
+
"transformers_version": "5.13.1",
|
| 2750 |
+
"use_cache": true,
|
| 2751 |
+
"vocab_size": 248320
|
| 2752 |
+
}
|
qwen35_reap_keep25/configuration_pruned_qwen3_5_moe.py
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Configuration for GLEAN-pruned Qwen3.5-MoE: variable-width, variable-count experts.
|
| 2 |
+
|
| 3 |
+
Requires the ``qwen3_5_moe`` architecture (transformers >= 5.x); checkpoints
|
| 4 |
+
carrying this module import the upstream classes rather than vendoring the
|
| 5 |
+
~1.5k-line hybrid (GatedDeltaNet + attention) stack.
|
| 6 |
+
"""
|
| 7 |
+
|
| 8 |
+
from transformers.models.qwen3_5_moe.configuration_qwen3_5_moe import (
|
| 9 |
+
Qwen3_5MoeTextConfig,
|
| 10 |
+
)
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
class PrunedQwen3_5MoeTextConfig(Qwen3_5MoeTextConfig):
|
| 14 |
+
"""Qwen3_5MoeTextConfig plus a per-(layer, expert) width table.
|
| 15 |
+
|
| 16 |
+
``expert_widths[l]`` lists the SwiGLU intermediate width of each surviving
|
| 17 |
+
routed expert in decoder layer ``l``, in original expert order. Lists are
|
| 18 |
+
ragged: layers may keep different numbers of experts (deleted experts
|
| 19 |
+
simply don't appear — the router in layer ``l`` has
|
| 20 |
+
``len(expert_widths[l])`` rows), and each width may differ. ``None`` means
|
| 21 |
+
an unpruned model (uniform ``num_experts`` x ``moe_intermediate_size``).
|
| 22 |
+
|
| 23 |
+
The inherited ``num_experts`` / ``moe_intermediate_size`` keep their
|
| 24 |
+
ORIGINAL (pre-pruning) values for provenance; the width table is
|
| 25 |
+
authoritative for the built architecture. The shared expert and its
|
| 26 |
+
sigmoid gate are untouched by pruning and keep their stock config fields.
|
| 27 |
+
"""
|
| 28 |
+
|
| 29 |
+
model_type = "pruned_qwen3_5_moe"
|
| 30 |
+
|
| 31 |
+
expert_widths: list[list[int]] | None = None
|
qwen35_reap_keep25/generation_config.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 248044,
|
| 4 |
+
"eos_token_id": 248044,
|
| 5 |
+
"output_attentions": false,
|
| 6 |
+
"output_hidden_states": false,
|
| 7 |
+
"transformers_version": "5.13.1",
|
| 8 |
+
"use_cache": true
|
| 9 |
+
}
|
qwen35_reap_keep25/modeling_pruned_qwen3_5_moe.py
ADDED
|
@@ -0,0 +1,122 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""GLEAN-pruned Qwen3.5-MoE: HF-loadable model with ragged (variable-width) experts.
|
| 2 |
+
|
| 3 |
+
Same pattern as ``modeling_pruned_olmoe``: ``super().__init__`` builds the
|
| 4 |
+
uniform architecture from the config (free on the meta device during
|
| 5 |
+
``from_pretrained``), then every MoE block's router and fused experts are
|
| 6 |
+
rebuilt to their pruned shape — surviving experts only, each at its own width,
|
| 7 |
+
router rows sliced to match. The token mixers (GatedDeltaNet / attention), the
|
| 8 |
+
shared expert, and its sigmoid gate are stock and untouched.
|
| 9 |
+
|
| 10 |
+
Unlike OLMoE's per-expert ``nn.Linear`` modules, Qwen3.5-MoE fuses experts
|
| 11 |
+
into 3-D parameters, which cannot hold ragged widths — so the pruned experts
|
| 12 |
+
module stores per-expert 2-D parameters in ``nn.ParameterList``s
|
| 13 |
+
(``gate_up_projs.{j}`` ``[2*w_j, H]``, ``down_projs.{j}`` ``[H, w_j]``) and
|
| 14 |
+
runs the same routed per-expert loop as upstream ``Qwen3_5MoeExperts.forward``
|
| 15 |
+
(verified against transformers 5.13.1; re-verify after upgrades).
|
| 16 |
+
|
| 17 |
+
Caveats: ``output_router_logits=True`` (the load-balancing aux loss) assumes a
|
| 18 |
+
uniform ``config.num_experts`` and is unsupported on ragged models; the eager
|
| 19 |
+
per-expert loop bypasses the fused ``_experts_implementation`` kernels.
|
| 20 |
+
"""
|
| 21 |
+
|
| 22 |
+
import torch
|
| 23 |
+
import torch.nn.functional as F
|
| 24 |
+
from torch import nn
|
| 25 |
+
from transformers.activations import ACT2FN
|
| 26 |
+
from transformers.models.qwen3_5_moe.modeling_qwen3_5_moe import (
|
| 27 |
+
Qwen3_5MoeForCausalLM,
|
| 28 |
+
)
|
| 29 |
+
|
| 30 |
+
from .configuration_pruned_qwen3_5_moe import PrunedQwen3_5MoeTextConfig
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
class PrunedQwen3_5MoeExperts(nn.Module):
|
| 34 |
+
"""Ragged replacement for the fused ``Qwen3_5MoeExperts``.
|
| 35 |
+
|
| 36 |
+
Forward replicates the upstream routed per-expert loop exactly, indexing
|
| 37 |
+
per-expert parameters instead of slices of a stacked 3-D tensor.
|
| 38 |
+
"""
|
| 39 |
+
|
| 40 |
+
def __init__(self, config: PrunedQwen3_5MoeTextConfig, widths: list[int]):
|
| 41 |
+
super().__init__()
|
| 42 |
+
self.num_experts = len(widths)
|
| 43 |
+
self.hidden_dim = config.hidden_size
|
| 44 |
+
self.gate_up_projs = nn.ParameterList(
|
| 45 |
+
nn.Parameter(torch.empty(2 * w, config.hidden_size)) for w in widths
|
| 46 |
+
)
|
| 47 |
+
self.down_projs = nn.ParameterList(
|
| 48 |
+
nn.Parameter(torch.empty(config.hidden_size, w)) for w in widths
|
| 49 |
+
)
|
| 50 |
+
self.act_fn = ACT2FN[config.hidden_act]
|
| 51 |
+
|
| 52 |
+
def forward(
|
| 53 |
+
self,
|
| 54 |
+
hidden_states: torch.Tensor,
|
| 55 |
+
top_k_index: torch.Tensor,
|
| 56 |
+
top_k_weights: torch.Tensor,
|
| 57 |
+
) -> torch.Tensor:
|
| 58 |
+
final_hidden_states = torch.zeros_like(hidden_states)
|
| 59 |
+
with torch.no_grad():
|
| 60 |
+
expert_mask = F.one_hot(top_k_index, num_classes=self.num_experts)
|
| 61 |
+
expert_mask = expert_mask.permute(2, 1, 0)
|
| 62 |
+
expert_hit = torch.greater(expert_mask.sum(dim=(-1, -2)), 0).nonzero()
|
| 63 |
+
|
| 64 |
+
for expert_idx in expert_hit:
|
| 65 |
+
expert_idx = int(expert_idx[0])
|
| 66 |
+
top_k_pos, token_idx = torch.where(expert_mask[expert_idx])
|
| 67 |
+
current_state = hidden_states[token_idx]
|
| 68 |
+
gate, up = F.linear(current_state, self.gate_up_projs[expert_idx]).chunk(2, dim=-1)
|
| 69 |
+
current_hidden_states = self.act_fn(gate) * up
|
| 70 |
+
current_hidden_states = F.linear(current_hidden_states, self.down_projs[expert_idx])
|
| 71 |
+
current_hidden_states = current_hidden_states * top_k_weights[token_idx, top_k_pos, None]
|
| 72 |
+
final_hidden_states.index_add_(
|
| 73 |
+
0, token_idx, current_hidden_states.to(final_hidden_states.dtype)
|
| 74 |
+
)
|
| 75 |
+
|
| 76 |
+
return final_hidden_states
|
| 77 |
+
|
| 78 |
+
|
| 79 |
+
class PrunedQwen3_5MoeForCausalLM(Qwen3_5MoeForCausalLM):
|
| 80 |
+
"""Qwen3.5-MoE with per-layer surviving-expert lists at per-expert widths."""
|
| 81 |
+
|
| 82 |
+
config_class = PrunedQwen3_5MoeTextConfig
|
| 83 |
+
|
| 84 |
+
def __init__(self, config: PrunedQwen3_5MoeTextConfig):
|
| 85 |
+
super().__init__(config)
|
| 86 |
+
widths_table = getattr(config, "expert_widths", None)
|
| 87 |
+
if widths_table is None:
|
| 88 |
+
return # unpruned: plain Qwen3.5-MoE
|
| 89 |
+
if len(widths_table) != len(self.model.layers):
|
| 90 |
+
raise ValueError(
|
| 91 |
+
f"expert_widths has {len(widths_table)} rows but the model has "
|
| 92 |
+
f"{len(self.model.layers)} decoder layers"
|
| 93 |
+
)
|
| 94 |
+
for layer, widths in zip(self.model.layers, widths_table):
|
| 95 |
+
if any(w <= 0 for w in widths):
|
| 96 |
+
raise ValueError("expert_widths must list surviving experts only (>0)")
|
| 97 |
+
block = layer.mlp
|
| 98 |
+
if len(widths) < block.gate.top_k:
|
| 99 |
+
raise ValueError(
|
| 100 |
+
f"a layer keeps {len(widths)} experts < top_k={block.gate.top_k}"
|
| 101 |
+
)
|
| 102 |
+
# keep the stock router class (OutputRecorder isinstance, forward
|
| 103 |
+
# unchanged) but shrink it to the surviving experts' rows
|
| 104 |
+
block.gate.num_experts = len(widths)
|
| 105 |
+
block.gate.weight = nn.Parameter(
|
| 106 |
+
torch.empty(
|
| 107 |
+
len(widths),
|
| 108 |
+
config.hidden_size,
|
| 109 |
+
dtype=block.gate.weight.dtype,
|
| 110 |
+
device=block.gate.weight.device,
|
| 111 |
+
)
|
| 112 |
+
)
|
| 113 |
+
block.experts = PrunedQwen3_5MoeExperts(config, list(widths))
|
| 114 |
+
|
| 115 |
+
@torch.no_grad()
|
| 116 |
+
def _init_weights(self, module):
|
| 117 |
+
super()._init_weights(module)
|
| 118 |
+
# the base isinstance(Qwen3_5MoeExperts) branch never sees our ragged
|
| 119 |
+
# module; raw nn.Parameters get no default init otherwise
|
| 120 |
+
if isinstance(module, PrunedQwen3_5MoeExperts):
|
| 121 |
+
for p in list(module.gate_up_projs) + list(module.down_projs):
|
| 122 |
+
nn.init.normal_(p, mean=0.0, std=self.config.initializer_range)
|
qwen35_reap_keep25/reap_verify.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"keep": 0.25,
|
| 3 |
+
"criterion": "reap",
|
| 4 |
+
"ppl": 22.945579528808594,
|
| 5 |
+
"n_params_b": 10.485691008,
|
| 6 |
+
"eval_seq": 32,
|
| 7 |
+
"seq_len": 2048,
|
| 8 |
+
"dataset": "c4"
|
| 9 |
+
}
|
qwen35_reap_keep25/tokenizer_config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|im_end|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"local_files_only": false,
|
| 14 |
+
"model_max_length": 262144,
|
| 15 |
+
"model_specific_special_tokens": {
|
| 16 |
+
"audio_bos_token": "<|audio_start|>",
|
| 17 |
+
"audio_eos_token": "<|audio_end|>",
|
| 18 |
+
"audio_token": "<|audio_pad|>",
|
| 19 |
+
"image_token": "<|image_pad|>",
|
| 20 |
+
"video_token": "<|video_pad|>",
|
| 21 |
+
"vision_bos_token": "<|vision_start|>",
|
| 22 |
+
"vision_eos_token": "<|vision_end|>"
|
| 23 |
+
},
|
| 24 |
+
"pad_token": "<|endoftext|>",
|
| 25 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 26 |
+
"split_special_tokens": false,
|
| 27 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 28 |
+
"unk_token": null,
|
| 29 |
+
"video_token": "<|video_pad|>",
|
| 30 |
+
"vision_bos_token": "<|vision_start|>",
|
| 31 |
+
"vision_eos_token": "<|vision_end|>"
|
| 32 |
+
}
|
qwen35_reap_keep50/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if (preserve_thinking is defined and preserve_thinking is true) or (loop.index0 > ns.last_query_index) %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
qwen35_reap_keep50/config.json
ADDED
|
@@ -0,0 +1,5312 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"PrunedQwen3_5MoeForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"attn_output_gate": true,
|
| 8 |
+
"auto_map": {
|
| 9 |
+
"AutoConfig": "configuration_pruned_qwen3_5_moe.PrunedQwen3_5MoeTextConfig",
|
| 10 |
+
"AutoModelForCausalLM": "modeling_pruned_qwen3_5_moe.PrunedQwen3_5MoeForCausalLM"
|
| 11 |
+
},
|
| 12 |
+
"bos_token_id": 248044,
|
| 13 |
+
"dtype": "bfloat16",
|
| 14 |
+
"eos_token_id": 248044,
|
| 15 |
+
"expert_widths": [
|
| 16 |
+
[
|
| 17 |
+
512,
|
| 18 |
+
512,
|
| 19 |
+
512,
|
| 20 |
+
512,
|
| 21 |
+
512,
|
| 22 |
+
512,
|
| 23 |
+
512,
|
| 24 |
+
512,
|
| 25 |
+
512,
|
| 26 |
+
512,
|
| 27 |
+
512,
|
| 28 |
+
512,
|
| 29 |
+
512,
|
| 30 |
+
512,
|
| 31 |
+
512,
|
| 32 |
+
512,
|
| 33 |
+
512,
|
| 34 |
+
512,
|
| 35 |
+
512,
|
| 36 |
+
512,
|
| 37 |
+
512,
|
| 38 |
+
512,
|
| 39 |
+
512,
|
| 40 |
+
512,
|
| 41 |
+
512,
|
| 42 |
+
512,
|
| 43 |
+
512,
|
| 44 |
+
512,
|
| 45 |
+
512,
|
| 46 |
+
512,
|
| 47 |
+
512,
|
| 48 |
+
512,
|
| 49 |
+
512,
|
| 50 |
+
512,
|
| 51 |
+
512,
|
| 52 |
+
512,
|
| 53 |
+
512,
|
| 54 |
+
512,
|
| 55 |
+
512,
|
| 56 |
+
512,
|
| 57 |
+
512,
|
| 58 |
+
512,
|
| 59 |
+
512,
|
| 60 |
+
512,
|
| 61 |
+
512,
|
| 62 |
+
512,
|
| 63 |
+
512,
|
| 64 |
+
512,
|
| 65 |
+
512,
|
| 66 |
+
512,
|
| 67 |
+
512,
|
| 68 |
+
512,
|
| 69 |
+
512,
|
| 70 |
+
512,
|
| 71 |
+
512,
|
| 72 |
+
512,
|
| 73 |
+
512,
|
| 74 |
+
512,
|
| 75 |
+
512,
|
| 76 |
+
512,
|
| 77 |
+
512,
|
| 78 |
+
512,
|
| 79 |
+
512,
|
| 80 |
+
512,
|
| 81 |
+
512,
|
| 82 |
+
512,
|
| 83 |
+
512,
|
| 84 |
+
512,
|
| 85 |
+
512,
|
| 86 |
+
512,
|
| 87 |
+
512,
|
| 88 |
+
512,
|
| 89 |
+
512,
|
| 90 |
+
512,
|
| 91 |
+
512,
|
| 92 |
+
512,
|
| 93 |
+
512,
|
| 94 |
+
512,
|
| 95 |
+
512,
|
| 96 |
+
512,
|
| 97 |
+
512,
|
| 98 |
+
512,
|
| 99 |
+
512,
|
| 100 |
+
512,
|
| 101 |
+
512,
|
| 102 |
+
512,
|
| 103 |
+
512,
|
| 104 |
+
512,
|
| 105 |
+
512,
|
| 106 |
+
512,
|
| 107 |
+
512,
|
| 108 |
+
512,
|
| 109 |
+
512,
|
| 110 |
+
512,
|
| 111 |
+
512,
|
| 112 |
+
512,
|
| 113 |
+
512,
|
| 114 |
+
512,
|
| 115 |
+
512,
|
| 116 |
+
512,
|
| 117 |
+
512,
|
| 118 |
+
512,
|
| 119 |
+
512,
|
| 120 |
+
512,
|
| 121 |
+
512,
|
| 122 |
+
512,
|
| 123 |
+
512,
|
| 124 |
+
512,
|
| 125 |
+
512,
|
| 126 |
+
512,
|
| 127 |
+
512,
|
| 128 |
+
512,
|
| 129 |
+
512,
|
| 130 |
+
512,
|
| 131 |
+
512,
|
| 132 |
+
512,
|
| 133 |
+
512,
|
| 134 |
+
512,
|
| 135 |
+
512,
|
| 136 |
+
512,
|
| 137 |
+
512,
|
| 138 |
+
512,
|
| 139 |
+
512,
|
| 140 |
+
512,
|
| 141 |
+
512,
|
| 142 |
+
512,
|
| 143 |
+
512,
|
| 144 |
+
512
|
| 145 |
+
],
|
| 146 |
+
[
|
| 147 |
+
512,
|
| 148 |
+
512,
|
| 149 |
+
512,
|
| 150 |
+
512,
|
| 151 |
+
512,
|
| 152 |
+
512,
|
| 153 |
+
512,
|
| 154 |
+
512,
|
| 155 |
+
512,
|
| 156 |
+
512,
|
| 157 |
+
512,
|
| 158 |
+
512,
|
| 159 |
+
512,
|
| 160 |
+
512,
|
| 161 |
+
512,
|
| 162 |
+
512,
|
| 163 |
+
512,
|
| 164 |
+
512,
|
| 165 |
+
512,
|
| 166 |
+
512,
|
| 167 |
+
512,
|
| 168 |
+
512,
|
| 169 |
+
512,
|
| 170 |
+
512,
|
| 171 |
+
512,
|
| 172 |
+
512,
|
| 173 |
+
512,
|
| 174 |
+
512,
|
| 175 |
+
512,
|
| 176 |
+
512,
|
| 177 |
+
512,
|
| 178 |
+
512,
|
| 179 |
+
512,
|
| 180 |
+
512,
|
| 181 |
+
512,
|
| 182 |
+
512,
|
| 183 |
+
512,
|
| 184 |
+
512,
|
| 185 |
+
512,
|
| 186 |
+
512,
|
| 187 |
+
512,
|
| 188 |
+
512,
|
| 189 |
+
512,
|
| 190 |
+
512,
|
| 191 |
+
512,
|
| 192 |
+
512,
|
| 193 |
+
512,
|
| 194 |
+
512,
|
| 195 |
+
512,
|
| 196 |
+
512,
|
| 197 |
+
512,
|
| 198 |
+
512,
|
| 199 |
+
512,
|
| 200 |
+
512,
|
| 201 |
+
512,
|
| 202 |
+
512,
|
| 203 |
+
512,
|
| 204 |
+
512,
|
| 205 |
+
512,
|
| 206 |
+
512,
|
| 207 |
+
512,
|
| 208 |
+
512,
|
| 209 |
+
512,
|
| 210 |
+
512,
|
| 211 |
+
512,
|
| 212 |
+
512,
|
| 213 |
+
512,
|
| 214 |
+
512,
|
| 215 |
+
512,
|
| 216 |
+
512,
|
| 217 |
+
512,
|
| 218 |
+
512,
|
| 219 |
+
512,
|
| 220 |
+
512,
|
| 221 |
+
512,
|
| 222 |
+
512,
|
| 223 |
+
512,
|
| 224 |
+
512,
|
| 225 |
+
512,
|
| 226 |
+
512,
|
| 227 |
+
512,
|
| 228 |
+
512,
|
| 229 |
+
512,
|
| 230 |
+
512,
|
| 231 |
+
512,
|
| 232 |
+
512,
|
| 233 |
+
512,
|
| 234 |
+
512,
|
| 235 |
+
512,
|
| 236 |
+
512,
|
| 237 |
+
512,
|
| 238 |
+
512,
|
| 239 |
+
512,
|
| 240 |
+
512,
|
| 241 |
+
512,
|
| 242 |
+
512,
|
| 243 |
+
512,
|
| 244 |
+
512,
|
| 245 |
+
512,
|
| 246 |
+
512,
|
| 247 |
+
512,
|
| 248 |
+
512,
|
| 249 |
+
512,
|
| 250 |
+
512,
|
| 251 |
+
512,
|
| 252 |
+
512,
|
| 253 |
+
512,
|
| 254 |
+
512,
|
| 255 |
+
512,
|
| 256 |
+
512,
|
| 257 |
+
512,
|
| 258 |
+
512,
|
| 259 |
+
512,
|
| 260 |
+
512,
|
| 261 |
+
512,
|
| 262 |
+
512,
|
| 263 |
+
512,
|
| 264 |
+
512,
|
| 265 |
+
512,
|
| 266 |
+
512,
|
| 267 |
+
512,
|
| 268 |
+
512,
|
| 269 |
+
512,
|
| 270 |
+
512,
|
| 271 |
+
512,
|
| 272 |
+
512,
|
| 273 |
+
512,
|
| 274 |
+
512
|
| 275 |
+
],
|
| 276 |
+
[
|
| 277 |
+
512,
|
| 278 |
+
512,
|
| 279 |
+
512,
|
| 280 |
+
512,
|
| 281 |
+
512,
|
| 282 |
+
512,
|
| 283 |
+
512,
|
| 284 |
+
512,
|
| 285 |
+
512,
|
| 286 |
+
512,
|
| 287 |
+
512,
|
| 288 |
+
512,
|
| 289 |
+
512,
|
| 290 |
+
512,
|
| 291 |
+
512,
|
| 292 |
+
512,
|
| 293 |
+
512,
|
| 294 |
+
512,
|
| 295 |
+
512,
|
| 296 |
+
512,
|
| 297 |
+
512,
|
| 298 |
+
512,
|
| 299 |
+
512,
|
| 300 |
+
512,
|
| 301 |
+
512,
|
| 302 |
+
512,
|
| 303 |
+
512,
|
| 304 |
+
512,
|
| 305 |
+
512,
|
| 306 |
+
512,
|
| 307 |
+
512,
|
| 308 |
+
512,
|
| 309 |
+
512,
|
| 310 |
+
512,
|
| 311 |
+
512,
|
| 312 |
+
512,
|
| 313 |
+
512,
|
| 314 |
+
512,
|
| 315 |
+
512,
|
| 316 |
+
512,
|
| 317 |
+
512,
|
| 318 |
+
512,
|
| 319 |
+
512,
|
| 320 |
+
512,
|
| 321 |
+
512,
|
| 322 |
+
512,
|
| 323 |
+
512,
|
| 324 |
+
512,
|
| 325 |
+
512,
|
| 326 |
+
512,
|
| 327 |
+
512,
|
| 328 |
+
512,
|
| 329 |
+
512,
|
| 330 |
+
512,
|
| 331 |
+
512,
|
| 332 |
+
512,
|
| 333 |
+
512,
|
| 334 |
+
512,
|
| 335 |
+
512,
|
| 336 |
+
512,
|
| 337 |
+
512,
|
| 338 |
+
512,
|
| 339 |
+
512,
|
| 340 |
+
512,
|
| 341 |
+
512,
|
| 342 |
+
512,
|
| 343 |
+
512,
|
| 344 |
+
512,
|
| 345 |
+
512,
|
| 346 |
+
512,
|
| 347 |
+
512,
|
| 348 |
+
512,
|
| 349 |
+
512,
|
| 350 |
+
512,
|
| 351 |
+
512,
|
| 352 |
+
512,
|
| 353 |
+
512,
|
| 354 |
+
512,
|
| 355 |
+
512,
|
| 356 |
+
512,
|
| 357 |
+
512,
|
| 358 |
+
512,
|
| 359 |
+
512,
|
| 360 |
+
512,
|
| 361 |
+
512,
|
| 362 |
+
512,
|
| 363 |
+
512,
|
| 364 |
+
512,
|
| 365 |
+
512,
|
| 366 |
+
512,
|
| 367 |
+
512,
|
| 368 |
+
512,
|
| 369 |
+
512,
|
| 370 |
+
512,
|
| 371 |
+
512,
|
| 372 |
+
512,
|
| 373 |
+
512,
|
| 374 |
+
512,
|
| 375 |
+
512,
|
| 376 |
+
512,
|
| 377 |
+
512,
|
| 378 |
+
512,
|
| 379 |
+
512,
|
| 380 |
+
512,
|
| 381 |
+
512,
|
| 382 |
+
512,
|
| 383 |
+
512,
|
| 384 |
+
512,
|
| 385 |
+
512,
|
| 386 |
+
512,
|
| 387 |
+
512,
|
| 388 |
+
512,
|
| 389 |
+
512,
|
| 390 |
+
512,
|
| 391 |
+
512,
|
| 392 |
+
512,
|
| 393 |
+
512,
|
| 394 |
+
512,
|
| 395 |
+
512,
|
| 396 |
+
512,
|
| 397 |
+
512,
|
| 398 |
+
512,
|
| 399 |
+
512,
|
| 400 |
+
512,
|
| 401 |
+
512,
|
| 402 |
+
512,
|
| 403 |
+
512,
|
| 404 |
+
512
|
| 405 |
+
],
|
| 406 |
+
[
|
| 407 |
+
512,
|
| 408 |
+
512,
|
| 409 |
+
512,
|
| 410 |
+
512,
|
| 411 |
+
512,
|
| 412 |
+
512,
|
| 413 |
+
512,
|
| 414 |
+
512,
|
| 415 |
+
512,
|
| 416 |
+
512,
|
| 417 |
+
512,
|
| 418 |
+
512,
|
| 419 |
+
512,
|
| 420 |
+
512,
|
| 421 |
+
512,
|
| 422 |
+
512,
|
| 423 |
+
512,
|
| 424 |
+
512,
|
| 425 |
+
512,
|
| 426 |
+
512,
|
| 427 |
+
512,
|
| 428 |
+
512,
|
| 429 |
+
512,
|
| 430 |
+
512,
|
| 431 |
+
512,
|
| 432 |
+
512,
|
| 433 |
+
512,
|
| 434 |
+
512,
|
| 435 |
+
512,
|
| 436 |
+
512,
|
| 437 |
+
512,
|
| 438 |
+
512,
|
| 439 |
+
512,
|
| 440 |
+
512,
|
| 441 |
+
512,
|
| 442 |
+
512,
|
| 443 |
+
512,
|
| 444 |
+
512,
|
| 445 |
+
512,
|
| 446 |
+
512,
|
| 447 |
+
512,
|
| 448 |
+
512,
|
| 449 |
+
512,
|
| 450 |
+
512,
|
| 451 |
+
512,
|
| 452 |
+
512,
|
| 453 |
+
512,
|
| 454 |
+
512,
|
| 455 |
+
512,
|
| 456 |
+
512,
|
| 457 |
+
512,
|
| 458 |
+
512,
|
| 459 |
+
512,
|
| 460 |
+
512,
|
| 461 |
+
512,
|
| 462 |
+
512,
|
| 463 |
+
512,
|
| 464 |
+
512,
|
| 465 |
+
512,
|
| 466 |
+
512,
|
| 467 |
+
512,
|
| 468 |
+
512,
|
| 469 |
+
512,
|
| 470 |
+
512,
|
| 471 |
+
512,
|
| 472 |
+
512,
|
| 473 |
+
512,
|
| 474 |
+
512,
|
| 475 |
+
512,
|
| 476 |
+
512,
|
| 477 |
+
512,
|
| 478 |
+
512,
|
| 479 |
+
512,
|
| 480 |
+
512,
|
| 481 |
+
512,
|
| 482 |
+
512,
|
| 483 |
+
512,
|
| 484 |
+
512,
|
| 485 |
+
512,
|
| 486 |
+
512,
|
| 487 |
+
512,
|
| 488 |
+
512,
|
| 489 |
+
512,
|
| 490 |
+
512,
|
| 491 |
+
512,
|
| 492 |
+
512,
|
| 493 |
+
512,
|
| 494 |
+
512,
|
| 495 |
+
512,
|
| 496 |
+
512,
|
| 497 |
+
512,
|
| 498 |
+
512,
|
| 499 |
+
512,
|
| 500 |
+
512,
|
| 501 |
+
512,
|
| 502 |
+
512,
|
| 503 |
+
512,
|
| 504 |
+
512,
|
| 505 |
+
512,
|
| 506 |
+
512,
|
| 507 |
+
512,
|
| 508 |
+
512,
|
| 509 |
+
512,
|
| 510 |
+
512,
|
| 511 |
+
512,
|
| 512 |
+
512,
|
| 513 |
+
512,
|
| 514 |
+
512,
|
| 515 |
+
512,
|
| 516 |
+
512,
|
| 517 |
+
512,
|
| 518 |
+
512,
|
| 519 |
+
512,
|
| 520 |
+
512,
|
| 521 |
+
512,
|
| 522 |
+
512,
|
| 523 |
+
512,
|
| 524 |
+
512,
|
| 525 |
+
512,
|
| 526 |
+
512,
|
| 527 |
+
512,
|
| 528 |
+
512,
|
| 529 |
+
512,
|
| 530 |
+
512,
|
| 531 |
+
512,
|
| 532 |
+
512,
|
| 533 |
+
512,
|
| 534 |
+
512
|
| 535 |
+
],
|
| 536 |
+
[
|
| 537 |
+
512,
|
| 538 |
+
512,
|
| 539 |
+
512,
|
| 540 |
+
512,
|
| 541 |
+
512,
|
| 542 |
+
512,
|
| 543 |
+
512,
|
| 544 |
+
512,
|
| 545 |
+
512,
|
| 546 |
+
512,
|
| 547 |
+
512,
|
| 548 |
+
512,
|
| 549 |
+
512,
|
| 550 |
+
512,
|
| 551 |
+
512,
|
| 552 |
+
512,
|
| 553 |
+
512,
|
| 554 |
+
512,
|
| 555 |
+
512,
|
| 556 |
+
512,
|
| 557 |
+
512,
|
| 558 |
+
512,
|
| 559 |
+
512,
|
| 560 |
+
512,
|
| 561 |
+
512,
|
| 562 |
+
512,
|
| 563 |
+
512,
|
| 564 |
+
512,
|
| 565 |
+
512,
|
| 566 |
+
512,
|
| 567 |
+
512,
|
| 568 |
+
512,
|
| 569 |
+
512,
|
| 570 |
+
512,
|
| 571 |
+
512,
|
| 572 |
+
512,
|
| 573 |
+
512,
|
| 574 |
+
512,
|
| 575 |
+
512,
|
| 576 |
+
512,
|
| 577 |
+
512,
|
| 578 |
+
512,
|
| 579 |
+
512,
|
| 580 |
+
512,
|
| 581 |
+
512,
|
| 582 |
+
512,
|
| 583 |
+
512,
|
| 584 |
+
512,
|
| 585 |
+
512,
|
| 586 |
+
512,
|
| 587 |
+
512,
|
| 588 |
+
512,
|
| 589 |
+
512,
|
| 590 |
+
512,
|
| 591 |
+
512,
|
| 592 |
+
512,
|
| 593 |
+
512,
|
| 594 |
+
512,
|
| 595 |
+
512,
|
| 596 |
+
512,
|
| 597 |
+
512,
|
| 598 |
+
512,
|
| 599 |
+
512,
|
| 600 |
+
512,
|
| 601 |
+
512,
|
| 602 |
+
512,
|
| 603 |
+
512,
|
| 604 |
+
512,
|
| 605 |
+
512,
|
| 606 |
+
512,
|
| 607 |
+
512,
|
| 608 |
+
512,
|
| 609 |
+
512,
|
| 610 |
+
512,
|
| 611 |
+
512,
|
| 612 |
+
512,
|
| 613 |
+
512,
|
| 614 |
+
512,
|
| 615 |
+
512,
|
| 616 |
+
512,
|
| 617 |
+
512,
|
| 618 |
+
512,
|
| 619 |
+
512,
|
| 620 |
+
512,
|
| 621 |
+
512,
|
| 622 |
+
512,
|
| 623 |
+
512,
|
| 624 |
+
512,
|
| 625 |
+
512,
|
| 626 |
+
512,
|
| 627 |
+
512,
|
| 628 |
+
512,
|
| 629 |
+
512,
|
| 630 |
+
512,
|
| 631 |
+
512,
|
| 632 |
+
512,
|
| 633 |
+
512,
|
| 634 |
+
512,
|
| 635 |
+
512,
|
| 636 |
+
512,
|
| 637 |
+
512,
|
| 638 |
+
512,
|
| 639 |
+
512,
|
| 640 |
+
512,
|
| 641 |
+
512,
|
| 642 |
+
512,
|
| 643 |
+
512,
|
| 644 |
+
512,
|
| 645 |
+
512,
|
| 646 |
+
512,
|
| 647 |
+
512,
|
| 648 |
+
512,
|
| 649 |
+
512,
|
| 650 |
+
512,
|
| 651 |
+
512,
|
| 652 |
+
512,
|
| 653 |
+
512,
|
| 654 |
+
512,
|
| 655 |
+
512,
|
| 656 |
+
512,
|
| 657 |
+
512,
|
| 658 |
+
512,
|
| 659 |
+
512,
|
| 660 |
+
512,
|
| 661 |
+
512,
|
| 662 |
+
512,
|
| 663 |
+
512,
|
| 664 |
+
512
|
| 665 |
+
],
|
| 666 |
+
[
|
| 667 |
+
512,
|
| 668 |
+
512,
|
| 669 |
+
512,
|
| 670 |
+
512,
|
| 671 |
+
512,
|
| 672 |
+
512,
|
| 673 |
+
512,
|
| 674 |
+
512,
|
| 675 |
+
512,
|
| 676 |
+
512,
|
| 677 |
+
512,
|
| 678 |
+
512,
|
| 679 |
+
512,
|
| 680 |
+
512,
|
| 681 |
+
512,
|
| 682 |
+
512,
|
| 683 |
+
512,
|
| 684 |
+
512,
|
| 685 |
+
512,
|
| 686 |
+
512,
|
| 687 |
+
512,
|
| 688 |
+
512,
|
| 689 |
+
512,
|
| 690 |
+
512,
|
| 691 |
+
512,
|
| 692 |
+
512,
|
| 693 |
+
512,
|
| 694 |
+
512,
|
| 695 |
+
512,
|
| 696 |
+
512,
|
| 697 |
+
512,
|
| 698 |
+
512,
|
| 699 |
+
512,
|
| 700 |
+
512,
|
| 701 |
+
512,
|
| 702 |
+
512,
|
| 703 |
+
512,
|
| 704 |
+
512,
|
| 705 |
+
512,
|
| 706 |
+
512,
|
| 707 |
+
512,
|
| 708 |
+
512,
|
| 709 |
+
512,
|
| 710 |
+
512,
|
| 711 |
+
512,
|
| 712 |
+
512,
|
| 713 |
+
512,
|
| 714 |
+
512,
|
| 715 |
+
512,
|
| 716 |
+
512,
|
| 717 |
+
512,
|
| 718 |
+
512,
|
| 719 |
+
512,
|
| 720 |
+
512,
|
| 721 |
+
512,
|
| 722 |
+
512,
|
| 723 |
+
512,
|
| 724 |
+
512,
|
| 725 |
+
512,
|
| 726 |
+
512,
|
| 727 |
+
512,
|
| 728 |
+
512,
|
| 729 |
+
512,
|
| 730 |
+
512,
|
| 731 |
+
512,
|
| 732 |
+
512,
|
| 733 |
+
512,
|
| 734 |
+
512,
|
| 735 |
+
512,
|
| 736 |
+
512,
|
| 737 |
+
512,
|
| 738 |
+
512,
|
| 739 |
+
512,
|
| 740 |
+
512,
|
| 741 |
+
512,
|
| 742 |
+
512,
|
| 743 |
+
512,
|
| 744 |
+
512,
|
| 745 |
+
512,
|
| 746 |
+
512,
|
| 747 |
+
512,
|
| 748 |
+
512,
|
| 749 |
+
512,
|
| 750 |
+
512,
|
| 751 |
+
512,
|
| 752 |
+
512,
|
| 753 |
+
512,
|
| 754 |
+
512,
|
| 755 |
+
512,
|
| 756 |
+
512,
|
| 757 |
+
512,
|
| 758 |
+
512,
|
| 759 |
+
512,
|
| 760 |
+
512,
|
| 761 |
+
512,
|
| 762 |
+
512,
|
| 763 |
+
512,
|
| 764 |
+
512,
|
| 765 |
+
512,
|
| 766 |
+
512,
|
| 767 |
+
512,
|
| 768 |
+
512,
|
| 769 |
+
512,
|
| 770 |
+
512,
|
| 771 |
+
512,
|
| 772 |
+
512,
|
| 773 |
+
512,
|
| 774 |
+
512,
|
| 775 |
+
512,
|
| 776 |
+
512,
|
| 777 |
+
512,
|
| 778 |
+
512,
|
| 779 |
+
512,
|
| 780 |
+
512,
|
| 781 |
+
512,
|
| 782 |
+
512,
|
| 783 |
+
512,
|
| 784 |
+
512,
|
| 785 |
+
512,
|
| 786 |
+
512,
|
| 787 |
+
512,
|
| 788 |
+
512,
|
| 789 |
+
512,
|
| 790 |
+
512,
|
| 791 |
+
512,
|
| 792 |
+
512,
|
| 793 |
+
512,
|
| 794 |
+
512
|
| 795 |
+
],
|
| 796 |
+
[
|
| 797 |
+
512,
|
| 798 |
+
512,
|
| 799 |
+
512,
|
| 800 |
+
512,
|
| 801 |
+
512,
|
| 802 |
+
512,
|
| 803 |
+
512,
|
| 804 |
+
512,
|
| 805 |
+
512,
|
| 806 |
+
512,
|
| 807 |
+
512,
|
| 808 |
+
512,
|
| 809 |
+
512,
|
| 810 |
+
512,
|
| 811 |
+
512,
|
| 812 |
+
512,
|
| 813 |
+
512,
|
| 814 |
+
512,
|
| 815 |
+
512,
|
| 816 |
+
512,
|
| 817 |
+
512,
|
| 818 |
+
512,
|
| 819 |
+
512,
|
| 820 |
+
512,
|
| 821 |
+
512,
|
| 822 |
+
512,
|
| 823 |
+
512,
|
| 824 |
+
512,
|
| 825 |
+
512,
|
| 826 |
+
512,
|
| 827 |
+
512,
|
| 828 |
+
512,
|
| 829 |
+
512,
|
| 830 |
+
512,
|
| 831 |
+
512,
|
| 832 |
+
512,
|
| 833 |
+
512,
|
| 834 |
+
512,
|
| 835 |
+
512,
|
| 836 |
+
512,
|
| 837 |
+
512,
|
| 838 |
+
512,
|
| 839 |
+
512,
|
| 840 |
+
512,
|
| 841 |
+
512,
|
| 842 |
+
512,
|
| 843 |
+
512,
|
| 844 |
+
512,
|
| 845 |
+
512,
|
| 846 |
+
512,
|
| 847 |
+
512,
|
| 848 |
+
512,
|
| 849 |
+
512,
|
| 850 |
+
512,
|
| 851 |
+
512,
|
| 852 |
+
512,
|
| 853 |
+
512,
|
| 854 |
+
512,
|
| 855 |
+
512,
|
| 856 |
+
512,
|
| 857 |
+
512,
|
| 858 |
+
512,
|
| 859 |
+
512,
|
| 860 |
+
512,
|
| 861 |
+
512,
|
| 862 |
+
512,
|
| 863 |
+
512,
|
| 864 |
+
512,
|
| 865 |
+
512,
|
| 866 |
+
512,
|
| 867 |
+
512,
|
| 868 |
+
512,
|
| 869 |
+
512,
|
| 870 |
+
512,
|
| 871 |
+
512,
|
| 872 |
+
512,
|
| 873 |
+
512,
|
| 874 |
+
512,
|
| 875 |
+
512,
|
| 876 |
+
512,
|
| 877 |
+
512,
|
| 878 |
+
512,
|
| 879 |
+
512,
|
| 880 |
+
512,
|
| 881 |
+
512,
|
| 882 |
+
512,
|
| 883 |
+
512,
|
| 884 |
+
512,
|
| 885 |
+
512,
|
| 886 |
+
512,
|
| 887 |
+
512,
|
| 888 |
+
512,
|
| 889 |
+
512,
|
| 890 |
+
512,
|
| 891 |
+
512,
|
| 892 |
+
512,
|
| 893 |
+
512,
|
| 894 |
+
512,
|
| 895 |
+
512,
|
| 896 |
+
512,
|
| 897 |
+
512,
|
| 898 |
+
512,
|
| 899 |
+
512,
|
| 900 |
+
512,
|
| 901 |
+
512,
|
| 902 |
+
512,
|
| 903 |
+
512,
|
| 904 |
+
512,
|
| 905 |
+
512,
|
| 906 |
+
512,
|
| 907 |
+
512,
|
| 908 |
+
512,
|
| 909 |
+
512,
|
| 910 |
+
512,
|
| 911 |
+
512,
|
| 912 |
+
512,
|
| 913 |
+
512,
|
| 914 |
+
512,
|
| 915 |
+
512,
|
| 916 |
+
512,
|
| 917 |
+
512,
|
| 918 |
+
512,
|
| 919 |
+
512,
|
| 920 |
+
512,
|
| 921 |
+
512,
|
| 922 |
+
512,
|
| 923 |
+
512,
|
| 924 |
+
512
|
| 925 |
+
],
|
| 926 |
+
[
|
| 927 |
+
512,
|
| 928 |
+
512,
|
| 929 |
+
512,
|
| 930 |
+
512,
|
| 931 |
+
512,
|
| 932 |
+
512,
|
| 933 |
+
512,
|
| 934 |
+
512,
|
| 935 |
+
512,
|
| 936 |
+
512,
|
| 937 |
+
512,
|
| 938 |
+
512,
|
| 939 |
+
512,
|
| 940 |
+
512,
|
| 941 |
+
512,
|
| 942 |
+
512,
|
| 943 |
+
512,
|
| 944 |
+
512,
|
| 945 |
+
512,
|
| 946 |
+
512,
|
| 947 |
+
512,
|
| 948 |
+
512,
|
| 949 |
+
512,
|
| 950 |
+
512,
|
| 951 |
+
512,
|
| 952 |
+
512,
|
| 953 |
+
512,
|
| 954 |
+
512,
|
| 955 |
+
512,
|
| 956 |
+
512,
|
| 957 |
+
512,
|
| 958 |
+
512,
|
| 959 |
+
512,
|
| 960 |
+
512,
|
| 961 |
+
512,
|
| 962 |
+
512,
|
| 963 |
+
512,
|
| 964 |
+
512,
|
| 965 |
+
512,
|
| 966 |
+
512,
|
| 967 |
+
512,
|
| 968 |
+
512,
|
| 969 |
+
512,
|
| 970 |
+
512,
|
| 971 |
+
512,
|
| 972 |
+
512,
|
| 973 |
+
512,
|
| 974 |
+
512,
|
| 975 |
+
512,
|
| 976 |
+
512,
|
| 977 |
+
512,
|
| 978 |
+
512,
|
| 979 |
+
512,
|
| 980 |
+
512,
|
| 981 |
+
512,
|
| 982 |
+
512,
|
| 983 |
+
512,
|
| 984 |
+
512,
|
| 985 |
+
512,
|
| 986 |
+
512,
|
| 987 |
+
512,
|
| 988 |
+
512,
|
| 989 |
+
512,
|
| 990 |
+
512,
|
| 991 |
+
512,
|
| 992 |
+
512,
|
| 993 |
+
512,
|
| 994 |
+
512,
|
| 995 |
+
512,
|
| 996 |
+
512,
|
| 997 |
+
512,
|
| 998 |
+
512,
|
| 999 |
+
512,
|
| 1000 |
+
512,
|
| 1001 |
+
512,
|
| 1002 |
+
512,
|
| 1003 |
+
512,
|
| 1004 |
+
512,
|
| 1005 |
+
512,
|
| 1006 |
+
512,
|
| 1007 |
+
512,
|
| 1008 |
+
512,
|
| 1009 |
+
512,
|
| 1010 |
+
512,
|
| 1011 |
+
512,
|
| 1012 |
+
512,
|
| 1013 |
+
512,
|
| 1014 |
+
512,
|
| 1015 |
+
512,
|
| 1016 |
+
512,
|
| 1017 |
+
512,
|
| 1018 |
+
512,
|
| 1019 |
+
512,
|
| 1020 |
+
512,
|
| 1021 |
+
512,
|
| 1022 |
+
512,
|
| 1023 |
+
512,
|
| 1024 |
+
512,
|
| 1025 |
+
512,
|
| 1026 |
+
512,
|
| 1027 |
+
512,
|
| 1028 |
+
512,
|
| 1029 |
+
512,
|
| 1030 |
+
512,
|
| 1031 |
+
512,
|
| 1032 |
+
512,
|
| 1033 |
+
512,
|
| 1034 |
+
512,
|
| 1035 |
+
512,
|
| 1036 |
+
512,
|
| 1037 |
+
512,
|
| 1038 |
+
512,
|
| 1039 |
+
512,
|
| 1040 |
+
512,
|
| 1041 |
+
512,
|
| 1042 |
+
512,
|
| 1043 |
+
512,
|
| 1044 |
+
512,
|
| 1045 |
+
512,
|
| 1046 |
+
512,
|
| 1047 |
+
512,
|
| 1048 |
+
512,
|
| 1049 |
+
512,
|
| 1050 |
+
512,
|
| 1051 |
+
512,
|
| 1052 |
+
512,
|
| 1053 |
+
512,
|
| 1054 |
+
512
|
| 1055 |
+
],
|
| 1056 |
+
[
|
| 1057 |
+
512,
|
| 1058 |
+
512,
|
| 1059 |
+
512,
|
| 1060 |
+
512,
|
| 1061 |
+
512,
|
| 1062 |
+
512,
|
| 1063 |
+
512,
|
| 1064 |
+
512,
|
| 1065 |
+
512,
|
| 1066 |
+
512,
|
| 1067 |
+
512,
|
| 1068 |
+
512,
|
| 1069 |
+
512,
|
| 1070 |
+
512,
|
| 1071 |
+
512,
|
| 1072 |
+
512,
|
| 1073 |
+
512,
|
| 1074 |
+
512,
|
| 1075 |
+
512,
|
| 1076 |
+
512,
|
| 1077 |
+
512,
|
| 1078 |
+
512,
|
| 1079 |
+
512,
|
| 1080 |
+
512,
|
| 1081 |
+
512,
|
| 1082 |
+
512,
|
| 1083 |
+
512,
|
| 1084 |
+
512,
|
| 1085 |
+
512,
|
| 1086 |
+
512,
|
| 1087 |
+
512,
|
| 1088 |
+
512,
|
| 1089 |
+
512,
|
| 1090 |
+
512,
|
| 1091 |
+
512,
|
| 1092 |
+
512,
|
| 1093 |
+
512,
|
| 1094 |
+
512,
|
| 1095 |
+
512,
|
| 1096 |
+
512,
|
| 1097 |
+
512,
|
| 1098 |
+
512,
|
| 1099 |
+
512,
|
| 1100 |
+
512,
|
| 1101 |
+
512,
|
| 1102 |
+
512,
|
| 1103 |
+
512,
|
| 1104 |
+
512,
|
| 1105 |
+
512,
|
| 1106 |
+
512,
|
| 1107 |
+
512,
|
| 1108 |
+
512,
|
| 1109 |
+
512,
|
| 1110 |
+
512,
|
| 1111 |
+
512,
|
| 1112 |
+
512,
|
| 1113 |
+
512,
|
| 1114 |
+
512,
|
| 1115 |
+
512,
|
| 1116 |
+
512,
|
| 1117 |
+
512,
|
| 1118 |
+
512,
|
| 1119 |
+
512,
|
| 1120 |
+
512,
|
| 1121 |
+
512,
|
| 1122 |
+
512,
|
| 1123 |
+
512,
|
| 1124 |
+
512,
|
| 1125 |
+
512,
|
| 1126 |
+
512,
|
| 1127 |
+
512,
|
| 1128 |
+
512,
|
| 1129 |
+
512,
|
| 1130 |
+
512,
|
| 1131 |
+
512,
|
| 1132 |
+
512,
|
| 1133 |
+
512,
|
| 1134 |
+
512,
|
| 1135 |
+
512,
|
| 1136 |
+
512,
|
| 1137 |
+
512,
|
| 1138 |
+
512,
|
| 1139 |
+
512,
|
| 1140 |
+
512,
|
| 1141 |
+
512,
|
| 1142 |
+
512,
|
| 1143 |
+
512,
|
| 1144 |
+
512,
|
| 1145 |
+
512,
|
| 1146 |
+
512,
|
| 1147 |
+
512,
|
| 1148 |
+
512,
|
| 1149 |
+
512,
|
| 1150 |
+
512,
|
| 1151 |
+
512,
|
| 1152 |
+
512,
|
| 1153 |
+
512,
|
| 1154 |
+
512,
|
| 1155 |
+
512,
|
| 1156 |
+
512,
|
| 1157 |
+
512,
|
| 1158 |
+
512,
|
| 1159 |
+
512,
|
| 1160 |
+
512,
|
| 1161 |
+
512,
|
| 1162 |
+
512,
|
| 1163 |
+
512,
|
| 1164 |
+
512,
|
| 1165 |
+
512,
|
| 1166 |
+
512,
|
| 1167 |
+
512,
|
| 1168 |
+
512,
|
| 1169 |
+
512,
|
| 1170 |
+
512,
|
| 1171 |
+
512,
|
| 1172 |
+
512,
|
| 1173 |
+
512,
|
| 1174 |
+
512,
|
| 1175 |
+
512,
|
| 1176 |
+
512,
|
| 1177 |
+
512,
|
| 1178 |
+
512,
|
| 1179 |
+
512,
|
| 1180 |
+
512,
|
| 1181 |
+
512,
|
| 1182 |
+
512,
|
| 1183 |
+
512,
|
| 1184 |
+
512
|
| 1185 |
+
],
|
| 1186 |
+
[
|
| 1187 |
+
512,
|
| 1188 |
+
512,
|
| 1189 |
+
512,
|
| 1190 |
+
512,
|
| 1191 |
+
512,
|
| 1192 |
+
512,
|
| 1193 |
+
512,
|
| 1194 |
+
512,
|
| 1195 |
+
512,
|
| 1196 |
+
512,
|
| 1197 |
+
512,
|
| 1198 |
+
512,
|
| 1199 |
+
512,
|
| 1200 |
+
512,
|
| 1201 |
+
512,
|
| 1202 |
+
512,
|
| 1203 |
+
512,
|
| 1204 |
+
512,
|
| 1205 |
+
512,
|
| 1206 |
+
512,
|
| 1207 |
+
512,
|
| 1208 |
+
512,
|
| 1209 |
+
512,
|
| 1210 |
+
512,
|
| 1211 |
+
512,
|
| 1212 |
+
512,
|
| 1213 |
+
512,
|
| 1214 |
+
512,
|
| 1215 |
+
512,
|
| 1216 |
+
512,
|
| 1217 |
+
512,
|
| 1218 |
+
512,
|
| 1219 |
+
512,
|
| 1220 |
+
512,
|
| 1221 |
+
512,
|
| 1222 |
+
512,
|
| 1223 |
+
512,
|
| 1224 |
+
512,
|
| 1225 |
+
512,
|
| 1226 |
+
512,
|
| 1227 |
+
512,
|
| 1228 |
+
512,
|
| 1229 |
+
512,
|
| 1230 |
+
512,
|
| 1231 |
+
512,
|
| 1232 |
+
512,
|
| 1233 |
+
512,
|
| 1234 |
+
512,
|
| 1235 |
+
512,
|
| 1236 |
+
512,
|
| 1237 |
+
512,
|
| 1238 |
+
512,
|
| 1239 |
+
512,
|
| 1240 |
+
512,
|
| 1241 |
+
512,
|
| 1242 |
+
512,
|
| 1243 |
+
512,
|
| 1244 |
+
512,
|
| 1245 |
+
512,
|
| 1246 |
+
512,
|
| 1247 |
+
512,
|
| 1248 |
+
512,
|
| 1249 |
+
512,
|
| 1250 |
+
512,
|
| 1251 |
+
512,
|
| 1252 |
+
512,
|
| 1253 |
+
512,
|
| 1254 |
+
512,
|
| 1255 |
+
512,
|
| 1256 |
+
512,
|
| 1257 |
+
512,
|
| 1258 |
+
512,
|
| 1259 |
+
512,
|
| 1260 |
+
512,
|
| 1261 |
+
512,
|
| 1262 |
+
512,
|
| 1263 |
+
512,
|
| 1264 |
+
512,
|
| 1265 |
+
512,
|
| 1266 |
+
512,
|
| 1267 |
+
512,
|
| 1268 |
+
512,
|
| 1269 |
+
512,
|
| 1270 |
+
512,
|
| 1271 |
+
512,
|
| 1272 |
+
512,
|
| 1273 |
+
512,
|
| 1274 |
+
512,
|
| 1275 |
+
512,
|
| 1276 |
+
512,
|
| 1277 |
+
512,
|
| 1278 |
+
512,
|
| 1279 |
+
512,
|
| 1280 |
+
512,
|
| 1281 |
+
512,
|
| 1282 |
+
512,
|
| 1283 |
+
512,
|
| 1284 |
+
512,
|
| 1285 |
+
512,
|
| 1286 |
+
512,
|
| 1287 |
+
512,
|
| 1288 |
+
512,
|
| 1289 |
+
512,
|
| 1290 |
+
512,
|
| 1291 |
+
512,
|
| 1292 |
+
512,
|
| 1293 |
+
512,
|
| 1294 |
+
512,
|
| 1295 |
+
512,
|
| 1296 |
+
512,
|
| 1297 |
+
512,
|
| 1298 |
+
512,
|
| 1299 |
+
512,
|
| 1300 |
+
512,
|
| 1301 |
+
512,
|
| 1302 |
+
512,
|
| 1303 |
+
512,
|
| 1304 |
+
512,
|
| 1305 |
+
512,
|
| 1306 |
+
512,
|
| 1307 |
+
512,
|
| 1308 |
+
512,
|
| 1309 |
+
512,
|
| 1310 |
+
512,
|
| 1311 |
+
512,
|
| 1312 |
+
512,
|
| 1313 |
+
512,
|
| 1314 |
+
512
|
| 1315 |
+
],
|
| 1316 |
+
[
|
| 1317 |
+
512,
|
| 1318 |
+
512,
|
| 1319 |
+
512,
|
| 1320 |
+
512,
|
| 1321 |
+
512,
|
| 1322 |
+
512,
|
| 1323 |
+
512,
|
| 1324 |
+
512,
|
| 1325 |
+
512,
|
| 1326 |
+
512,
|
| 1327 |
+
512,
|
| 1328 |
+
512,
|
| 1329 |
+
512,
|
| 1330 |
+
512,
|
| 1331 |
+
512,
|
| 1332 |
+
512,
|
| 1333 |
+
512,
|
| 1334 |
+
512,
|
| 1335 |
+
512,
|
| 1336 |
+
512,
|
| 1337 |
+
512,
|
| 1338 |
+
512,
|
| 1339 |
+
512,
|
| 1340 |
+
512,
|
| 1341 |
+
512,
|
| 1342 |
+
512,
|
| 1343 |
+
512,
|
| 1344 |
+
512,
|
| 1345 |
+
512,
|
| 1346 |
+
512,
|
| 1347 |
+
512,
|
| 1348 |
+
512,
|
| 1349 |
+
512,
|
| 1350 |
+
512,
|
| 1351 |
+
512,
|
| 1352 |
+
512,
|
| 1353 |
+
512,
|
| 1354 |
+
512,
|
| 1355 |
+
512,
|
| 1356 |
+
512,
|
| 1357 |
+
512,
|
| 1358 |
+
512,
|
| 1359 |
+
512,
|
| 1360 |
+
512,
|
| 1361 |
+
512,
|
| 1362 |
+
512,
|
| 1363 |
+
512,
|
| 1364 |
+
512,
|
| 1365 |
+
512,
|
| 1366 |
+
512,
|
| 1367 |
+
512,
|
| 1368 |
+
512,
|
| 1369 |
+
512,
|
| 1370 |
+
512,
|
| 1371 |
+
512,
|
| 1372 |
+
512,
|
| 1373 |
+
512,
|
| 1374 |
+
512,
|
| 1375 |
+
512,
|
| 1376 |
+
512,
|
| 1377 |
+
512,
|
| 1378 |
+
512,
|
| 1379 |
+
512,
|
| 1380 |
+
512,
|
| 1381 |
+
512,
|
| 1382 |
+
512,
|
| 1383 |
+
512,
|
| 1384 |
+
512,
|
| 1385 |
+
512,
|
| 1386 |
+
512,
|
| 1387 |
+
512,
|
| 1388 |
+
512,
|
| 1389 |
+
512,
|
| 1390 |
+
512,
|
| 1391 |
+
512,
|
| 1392 |
+
512,
|
| 1393 |
+
512,
|
| 1394 |
+
512,
|
| 1395 |
+
512,
|
| 1396 |
+
512,
|
| 1397 |
+
512,
|
| 1398 |
+
512,
|
| 1399 |
+
512,
|
| 1400 |
+
512,
|
| 1401 |
+
512,
|
| 1402 |
+
512,
|
| 1403 |
+
512,
|
| 1404 |
+
512,
|
| 1405 |
+
512,
|
| 1406 |
+
512,
|
| 1407 |
+
512,
|
| 1408 |
+
512,
|
| 1409 |
+
512,
|
| 1410 |
+
512,
|
| 1411 |
+
512,
|
| 1412 |
+
512,
|
| 1413 |
+
512,
|
| 1414 |
+
512,
|
| 1415 |
+
512,
|
| 1416 |
+
512,
|
| 1417 |
+
512,
|
| 1418 |
+
512,
|
| 1419 |
+
512,
|
| 1420 |
+
512,
|
| 1421 |
+
512,
|
| 1422 |
+
512,
|
| 1423 |
+
512,
|
| 1424 |
+
512,
|
| 1425 |
+
512,
|
| 1426 |
+
512,
|
| 1427 |
+
512,
|
| 1428 |
+
512,
|
| 1429 |
+
512,
|
| 1430 |
+
512,
|
| 1431 |
+
512,
|
| 1432 |
+
512,
|
| 1433 |
+
512,
|
| 1434 |
+
512,
|
| 1435 |
+
512,
|
| 1436 |
+
512,
|
| 1437 |
+
512,
|
| 1438 |
+
512,
|
| 1439 |
+
512,
|
| 1440 |
+
512,
|
| 1441 |
+
512,
|
| 1442 |
+
512,
|
| 1443 |
+
512,
|
| 1444 |
+
512
|
| 1445 |
+
],
|
| 1446 |
+
[
|
| 1447 |
+
512,
|
| 1448 |
+
512,
|
| 1449 |
+
512,
|
| 1450 |
+
512,
|
| 1451 |
+
512,
|
| 1452 |
+
512,
|
| 1453 |
+
512,
|
| 1454 |
+
512,
|
| 1455 |
+
512,
|
| 1456 |
+
512,
|
| 1457 |
+
512,
|
| 1458 |
+
512,
|
| 1459 |
+
512,
|
| 1460 |
+
512,
|
| 1461 |
+
512,
|
| 1462 |
+
512,
|
| 1463 |
+
512,
|
| 1464 |
+
512,
|
| 1465 |
+
512,
|
| 1466 |
+
512,
|
| 1467 |
+
512,
|
| 1468 |
+
512,
|
| 1469 |
+
512,
|
| 1470 |
+
512,
|
| 1471 |
+
512,
|
| 1472 |
+
512,
|
| 1473 |
+
512,
|
| 1474 |
+
512,
|
| 1475 |
+
512,
|
| 1476 |
+
512,
|
| 1477 |
+
512,
|
| 1478 |
+
512,
|
| 1479 |
+
512,
|
| 1480 |
+
512,
|
| 1481 |
+
512,
|
| 1482 |
+
512,
|
| 1483 |
+
512,
|
| 1484 |
+
512,
|
| 1485 |
+
512,
|
| 1486 |
+
512,
|
| 1487 |
+
512,
|
| 1488 |
+
512,
|
| 1489 |
+
512,
|
| 1490 |
+
512,
|
| 1491 |
+
512,
|
| 1492 |
+
512,
|
| 1493 |
+
512,
|
| 1494 |
+
512,
|
| 1495 |
+
512,
|
| 1496 |
+
512,
|
| 1497 |
+
512,
|
| 1498 |
+
512,
|
| 1499 |
+
512,
|
| 1500 |
+
512,
|
| 1501 |
+
512,
|
| 1502 |
+
512,
|
| 1503 |
+
512,
|
| 1504 |
+
512,
|
| 1505 |
+
512,
|
| 1506 |
+
512,
|
| 1507 |
+
512,
|
| 1508 |
+
512,
|
| 1509 |
+
512,
|
| 1510 |
+
512,
|
| 1511 |
+
512,
|
| 1512 |
+
512,
|
| 1513 |
+
512,
|
| 1514 |
+
512,
|
| 1515 |
+
512,
|
| 1516 |
+
512,
|
| 1517 |
+
512,
|
| 1518 |
+
512,
|
| 1519 |
+
512,
|
| 1520 |
+
512,
|
| 1521 |
+
512,
|
| 1522 |
+
512,
|
| 1523 |
+
512,
|
| 1524 |
+
512,
|
| 1525 |
+
512,
|
| 1526 |
+
512,
|
| 1527 |
+
512,
|
| 1528 |
+
512,
|
| 1529 |
+
512,
|
| 1530 |
+
512,
|
| 1531 |
+
512,
|
| 1532 |
+
512,
|
| 1533 |
+
512,
|
| 1534 |
+
512,
|
| 1535 |
+
512,
|
| 1536 |
+
512,
|
| 1537 |
+
512,
|
| 1538 |
+
512,
|
| 1539 |
+
512,
|
| 1540 |
+
512,
|
| 1541 |
+
512,
|
| 1542 |
+
512,
|
| 1543 |
+
512,
|
| 1544 |
+
512,
|
| 1545 |
+
512,
|
| 1546 |
+
512,
|
| 1547 |
+
512,
|
| 1548 |
+
512,
|
| 1549 |
+
512,
|
| 1550 |
+
512,
|
| 1551 |
+
512,
|
| 1552 |
+
512,
|
| 1553 |
+
512,
|
| 1554 |
+
512,
|
| 1555 |
+
512,
|
| 1556 |
+
512,
|
| 1557 |
+
512,
|
| 1558 |
+
512,
|
| 1559 |
+
512,
|
| 1560 |
+
512,
|
| 1561 |
+
512,
|
| 1562 |
+
512,
|
| 1563 |
+
512,
|
| 1564 |
+
512,
|
| 1565 |
+
512,
|
| 1566 |
+
512,
|
| 1567 |
+
512,
|
| 1568 |
+
512,
|
| 1569 |
+
512,
|
| 1570 |
+
512,
|
| 1571 |
+
512,
|
| 1572 |
+
512,
|
| 1573 |
+
512,
|
| 1574 |
+
512
|
| 1575 |
+
],
|
| 1576 |
+
[
|
| 1577 |
+
512,
|
| 1578 |
+
512,
|
| 1579 |
+
512,
|
| 1580 |
+
512,
|
| 1581 |
+
512,
|
| 1582 |
+
512,
|
| 1583 |
+
512,
|
| 1584 |
+
512,
|
| 1585 |
+
512,
|
| 1586 |
+
512,
|
| 1587 |
+
512,
|
| 1588 |
+
512,
|
| 1589 |
+
512,
|
| 1590 |
+
512,
|
| 1591 |
+
512,
|
| 1592 |
+
512,
|
| 1593 |
+
512,
|
| 1594 |
+
512,
|
| 1595 |
+
512,
|
| 1596 |
+
512,
|
| 1597 |
+
512,
|
| 1598 |
+
512,
|
| 1599 |
+
512,
|
| 1600 |
+
512,
|
| 1601 |
+
512,
|
| 1602 |
+
512,
|
| 1603 |
+
512,
|
| 1604 |
+
512,
|
| 1605 |
+
512,
|
| 1606 |
+
512,
|
| 1607 |
+
512,
|
| 1608 |
+
512,
|
| 1609 |
+
512,
|
| 1610 |
+
512,
|
| 1611 |
+
512,
|
| 1612 |
+
512,
|
| 1613 |
+
512,
|
| 1614 |
+
512,
|
| 1615 |
+
512,
|
| 1616 |
+
512,
|
| 1617 |
+
512,
|
| 1618 |
+
512,
|
| 1619 |
+
512,
|
| 1620 |
+
512,
|
| 1621 |
+
512,
|
| 1622 |
+
512,
|
| 1623 |
+
512,
|
| 1624 |
+
512,
|
| 1625 |
+
512,
|
| 1626 |
+
512,
|
| 1627 |
+
512,
|
| 1628 |
+
512,
|
| 1629 |
+
512,
|
| 1630 |
+
512,
|
| 1631 |
+
512,
|
| 1632 |
+
512,
|
| 1633 |
+
512,
|
| 1634 |
+
512,
|
| 1635 |
+
512,
|
| 1636 |
+
512,
|
| 1637 |
+
512,
|
| 1638 |
+
512,
|
| 1639 |
+
512,
|
| 1640 |
+
512,
|
| 1641 |
+
512,
|
| 1642 |
+
512,
|
| 1643 |
+
512,
|
| 1644 |
+
512,
|
| 1645 |
+
512,
|
| 1646 |
+
512,
|
| 1647 |
+
512,
|
| 1648 |
+
512,
|
| 1649 |
+
512,
|
| 1650 |
+
512,
|
| 1651 |
+
512,
|
| 1652 |
+
512,
|
| 1653 |
+
512,
|
| 1654 |
+
512,
|
| 1655 |
+
512,
|
| 1656 |
+
512,
|
| 1657 |
+
512,
|
| 1658 |
+
512,
|
| 1659 |
+
512,
|
| 1660 |
+
512,
|
| 1661 |
+
512,
|
| 1662 |
+
512,
|
| 1663 |
+
512,
|
| 1664 |
+
512,
|
| 1665 |
+
512,
|
| 1666 |
+
512,
|
| 1667 |
+
512,
|
| 1668 |
+
512,
|
| 1669 |
+
512,
|
| 1670 |
+
512,
|
| 1671 |
+
512,
|
| 1672 |
+
512,
|
| 1673 |
+
512,
|
| 1674 |
+
512,
|
| 1675 |
+
512,
|
| 1676 |
+
512,
|
| 1677 |
+
512,
|
| 1678 |
+
512,
|
| 1679 |
+
512,
|
| 1680 |
+
512,
|
| 1681 |
+
512,
|
| 1682 |
+
512,
|
| 1683 |
+
512,
|
| 1684 |
+
512,
|
| 1685 |
+
512,
|
| 1686 |
+
512,
|
| 1687 |
+
512,
|
| 1688 |
+
512,
|
| 1689 |
+
512,
|
| 1690 |
+
512,
|
| 1691 |
+
512,
|
| 1692 |
+
512,
|
| 1693 |
+
512,
|
| 1694 |
+
512,
|
| 1695 |
+
512,
|
| 1696 |
+
512,
|
| 1697 |
+
512,
|
| 1698 |
+
512,
|
| 1699 |
+
512,
|
| 1700 |
+
512,
|
| 1701 |
+
512,
|
| 1702 |
+
512,
|
| 1703 |
+
512,
|
| 1704 |
+
512
|
| 1705 |
+
],
|
| 1706 |
+
[
|
| 1707 |
+
512,
|
| 1708 |
+
512,
|
| 1709 |
+
512,
|
| 1710 |
+
512,
|
| 1711 |
+
512,
|
| 1712 |
+
512,
|
| 1713 |
+
512,
|
| 1714 |
+
512,
|
| 1715 |
+
512,
|
| 1716 |
+
512,
|
| 1717 |
+
512,
|
| 1718 |
+
512,
|
| 1719 |
+
512,
|
| 1720 |
+
512,
|
| 1721 |
+
512,
|
| 1722 |
+
512,
|
| 1723 |
+
512,
|
| 1724 |
+
512,
|
| 1725 |
+
512,
|
| 1726 |
+
512,
|
| 1727 |
+
512,
|
| 1728 |
+
512,
|
| 1729 |
+
512,
|
| 1730 |
+
512,
|
| 1731 |
+
512,
|
| 1732 |
+
512,
|
| 1733 |
+
512,
|
| 1734 |
+
512,
|
| 1735 |
+
512,
|
| 1736 |
+
512,
|
| 1737 |
+
512,
|
| 1738 |
+
512,
|
| 1739 |
+
512,
|
| 1740 |
+
512,
|
| 1741 |
+
512,
|
| 1742 |
+
512,
|
| 1743 |
+
512,
|
| 1744 |
+
512,
|
| 1745 |
+
512,
|
| 1746 |
+
512,
|
| 1747 |
+
512,
|
| 1748 |
+
512,
|
| 1749 |
+
512,
|
| 1750 |
+
512,
|
| 1751 |
+
512,
|
| 1752 |
+
512,
|
| 1753 |
+
512,
|
| 1754 |
+
512,
|
| 1755 |
+
512,
|
| 1756 |
+
512,
|
| 1757 |
+
512,
|
| 1758 |
+
512,
|
| 1759 |
+
512,
|
| 1760 |
+
512,
|
| 1761 |
+
512,
|
| 1762 |
+
512,
|
| 1763 |
+
512,
|
| 1764 |
+
512,
|
| 1765 |
+
512,
|
| 1766 |
+
512,
|
| 1767 |
+
512,
|
| 1768 |
+
512,
|
| 1769 |
+
512,
|
| 1770 |
+
512,
|
| 1771 |
+
512,
|
| 1772 |
+
512,
|
| 1773 |
+
512,
|
| 1774 |
+
512,
|
| 1775 |
+
512,
|
| 1776 |
+
512,
|
| 1777 |
+
512,
|
| 1778 |
+
512,
|
| 1779 |
+
512,
|
| 1780 |
+
512,
|
| 1781 |
+
512,
|
| 1782 |
+
512,
|
| 1783 |
+
512,
|
| 1784 |
+
512,
|
| 1785 |
+
512,
|
| 1786 |
+
512,
|
| 1787 |
+
512,
|
| 1788 |
+
512,
|
| 1789 |
+
512,
|
| 1790 |
+
512,
|
| 1791 |
+
512,
|
| 1792 |
+
512,
|
| 1793 |
+
512,
|
| 1794 |
+
512,
|
| 1795 |
+
512,
|
| 1796 |
+
512,
|
| 1797 |
+
512,
|
| 1798 |
+
512,
|
| 1799 |
+
512,
|
| 1800 |
+
512,
|
| 1801 |
+
512,
|
| 1802 |
+
512,
|
| 1803 |
+
512,
|
| 1804 |
+
512,
|
| 1805 |
+
512,
|
| 1806 |
+
512,
|
| 1807 |
+
512,
|
| 1808 |
+
512,
|
| 1809 |
+
512,
|
| 1810 |
+
512,
|
| 1811 |
+
512,
|
| 1812 |
+
512,
|
| 1813 |
+
512,
|
| 1814 |
+
512,
|
| 1815 |
+
512,
|
| 1816 |
+
512,
|
| 1817 |
+
512,
|
| 1818 |
+
512,
|
| 1819 |
+
512,
|
| 1820 |
+
512,
|
| 1821 |
+
512,
|
| 1822 |
+
512,
|
| 1823 |
+
512,
|
| 1824 |
+
512,
|
| 1825 |
+
512,
|
| 1826 |
+
512,
|
| 1827 |
+
512,
|
| 1828 |
+
512,
|
| 1829 |
+
512,
|
| 1830 |
+
512,
|
| 1831 |
+
512,
|
| 1832 |
+
512,
|
| 1833 |
+
512,
|
| 1834 |
+
512
|
| 1835 |
+
],
|
| 1836 |
+
[
|
| 1837 |
+
512,
|
| 1838 |
+
512,
|
| 1839 |
+
512,
|
| 1840 |
+
512,
|
| 1841 |
+
512,
|
| 1842 |
+
512,
|
| 1843 |
+
512,
|
| 1844 |
+
512,
|
| 1845 |
+
512,
|
| 1846 |
+
512,
|
| 1847 |
+
512,
|
| 1848 |
+
512,
|
| 1849 |
+
512,
|
| 1850 |
+
512,
|
| 1851 |
+
512,
|
| 1852 |
+
512,
|
| 1853 |
+
512,
|
| 1854 |
+
512,
|
| 1855 |
+
512,
|
| 1856 |
+
512,
|
| 1857 |
+
512,
|
| 1858 |
+
512,
|
| 1859 |
+
512,
|
| 1860 |
+
512,
|
| 1861 |
+
512,
|
| 1862 |
+
512,
|
| 1863 |
+
512,
|
| 1864 |
+
512,
|
| 1865 |
+
512,
|
| 1866 |
+
512,
|
| 1867 |
+
512,
|
| 1868 |
+
512,
|
| 1869 |
+
512,
|
| 1870 |
+
512,
|
| 1871 |
+
512,
|
| 1872 |
+
512,
|
| 1873 |
+
512,
|
| 1874 |
+
512,
|
| 1875 |
+
512,
|
| 1876 |
+
512,
|
| 1877 |
+
512,
|
| 1878 |
+
512,
|
| 1879 |
+
512,
|
| 1880 |
+
512,
|
| 1881 |
+
512,
|
| 1882 |
+
512,
|
| 1883 |
+
512,
|
| 1884 |
+
512,
|
| 1885 |
+
512,
|
| 1886 |
+
512,
|
| 1887 |
+
512,
|
| 1888 |
+
512,
|
| 1889 |
+
512,
|
| 1890 |
+
512,
|
| 1891 |
+
512,
|
| 1892 |
+
512,
|
| 1893 |
+
512,
|
| 1894 |
+
512,
|
| 1895 |
+
512,
|
| 1896 |
+
512,
|
| 1897 |
+
512,
|
| 1898 |
+
512,
|
| 1899 |
+
512,
|
| 1900 |
+
512,
|
| 1901 |
+
512,
|
| 1902 |
+
512,
|
| 1903 |
+
512,
|
| 1904 |
+
512,
|
| 1905 |
+
512,
|
| 1906 |
+
512,
|
| 1907 |
+
512,
|
| 1908 |
+
512,
|
| 1909 |
+
512,
|
| 1910 |
+
512,
|
| 1911 |
+
512,
|
| 1912 |
+
512,
|
| 1913 |
+
512,
|
| 1914 |
+
512,
|
| 1915 |
+
512,
|
| 1916 |
+
512,
|
| 1917 |
+
512,
|
| 1918 |
+
512,
|
| 1919 |
+
512,
|
| 1920 |
+
512,
|
| 1921 |
+
512,
|
| 1922 |
+
512,
|
| 1923 |
+
512,
|
| 1924 |
+
512,
|
| 1925 |
+
512,
|
| 1926 |
+
512,
|
| 1927 |
+
512,
|
| 1928 |
+
512,
|
| 1929 |
+
512,
|
| 1930 |
+
512,
|
| 1931 |
+
512,
|
| 1932 |
+
512,
|
| 1933 |
+
512,
|
| 1934 |
+
512,
|
| 1935 |
+
512,
|
| 1936 |
+
512,
|
| 1937 |
+
512,
|
| 1938 |
+
512,
|
| 1939 |
+
512,
|
| 1940 |
+
512,
|
| 1941 |
+
512,
|
| 1942 |
+
512,
|
| 1943 |
+
512,
|
| 1944 |
+
512,
|
| 1945 |
+
512,
|
| 1946 |
+
512,
|
| 1947 |
+
512,
|
| 1948 |
+
512,
|
| 1949 |
+
512,
|
| 1950 |
+
512,
|
| 1951 |
+
512,
|
| 1952 |
+
512,
|
| 1953 |
+
512,
|
| 1954 |
+
512,
|
| 1955 |
+
512,
|
| 1956 |
+
512,
|
| 1957 |
+
512,
|
| 1958 |
+
512,
|
| 1959 |
+
512,
|
| 1960 |
+
512,
|
| 1961 |
+
512,
|
| 1962 |
+
512,
|
| 1963 |
+
512,
|
| 1964 |
+
512
|
| 1965 |
+
],
|
| 1966 |
+
[
|
| 1967 |
+
512,
|
| 1968 |
+
512,
|
| 1969 |
+
512,
|
| 1970 |
+
512,
|
| 1971 |
+
512,
|
| 1972 |
+
512,
|
| 1973 |
+
512,
|
| 1974 |
+
512,
|
| 1975 |
+
512,
|
| 1976 |
+
512,
|
| 1977 |
+
512,
|
| 1978 |
+
512,
|
| 1979 |
+
512,
|
| 1980 |
+
512,
|
| 1981 |
+
512,
|
| 1982 |
+
512,
|
| 1983 |
+
512,
|
| 1984 |
+
512,
|
| 1985 |
+
512,
|
| 1986 |
+
512,
|
| 1987 |
+
512,
|
| 1988 |
+
512,
|
| 1989 |
+
512,
|
| 1990 |
+
512,
|
| 1991 |
+
512,
|
| 1992 |
+
512,
|
| 1993 |
+
512,
|
| 1994 |
+
512,
|
| 1995 |
+
512,
|
| 1996 |
+
512,
|
| 1997 |
+
512,
|
| 1998 |
+
512,
|
| 1999 |
+
512,
|
| 2000 |
+
512,
|
| 2001 |
+
512,
|
| 2002 |
+
512,
|
| 2003 |
+
512,
|
| 2004 |
+
512,
|
| 2005 |
+
512,
|
| 2006 |
+
512,
|
| 2007 |
+
512,
|
| 2008 |
+
512,
|
| 2009 |
+
512,
|
| 2010 |
+
512,
|
| 2011 |
+
512,
|
| 2012 |
+
512,
|
| 2013 |
+
512,
|
| 2014 |
+
512,
|
| 2015 |
+
512,
|
| 2016 |
+
512,
|
| 2017 |
+
512,
|
| 2018 |
+
512,
|
| 2019 |
+
512,
|
| 2020 |
+
512,
|
| 2021 |
+
512,
|
| 2022 |
+
512,
|
| 2023 |
+
512,
|
| 2024 |
+
512,
|
| 2025 |
+
512,
|
| 2026 |
+
512,
|
| 2027 |
+
512,
|
| 2028 |
+
512,
|
| 2029 |
+
512,
|
| 2030 |
+
512,
|
| 2031 |
+
512,
|
| 2032 |
+
512,
|
| 2033 |
+
512,
|
| 2034 |
+
512,
|
| 2035 |
+
512,
|
| 2036 |
+
512,
|
| 2037 |
+
512,
|
| 2038 |
+
512,
|
| 2039 |
+
512,
|
| 2040 |
+
512,
|
| 2041 |
+
512,
|
| 2042 |
+
512,
|
| 2043 |
+
512,
|
| 2044 |
+
512,
|
| 2045 |
+
512,
|
| 2046 |
+
512,
|
| 2047 |
+
512,
|
| 2048 |
+
512,
|
| 2049 |
+
512,
|
| 2050 |
+
512,
|
| 2051 |
+
512,
|
| 2052 |
+
512,
|
| 2053 |
+
512,
|
| 2054 |
+
512,
|
| 2055 |
+
512,
|
| 2056 |
+
512,
|
| 2057 |
+
512,
|
| 2058 |
+
512,
|
| 2059 |
+
512,
|
| 2060 |
+
512,
|
| 2061 |
+
512,
|
| 2062 |
+
512,
|
| 2063 |
+
512,
|
| 2064 |
+
512,
|
| 2065 |
+
512,
|
| 2066 |
+
512,
|
| 2067 |
+
512,
|
| 2068 |
+
512,
|
| 2069 |
+
512,
|
| 2070 |
+
512,
|
| 2071 |
+
512,
|
| 2072 |
+
512,
|
| 2073 |
+
512,
|
| 2074 |
+
512,
|
| 2075 |
+
512,
|
| 2076 |
+
512,
|
| 2077 |
+
512,
|
| 2078 |
+
512,
|
| 2079 |
+
512,
|
| 2080 |
+
512,
|
| 2081 |
+
512,
|
| 2082 |
+
512,
|
| 2083 |
+
512,
|
| 2084 |
+
512,
|
| 2085 |
+
512,
|
| 2086 |
+
512,
|
| 2087 |
+
512,
|
| 2088 |
+
512,
|
| 2089 |
+
512,
|
| 2090 |
+
512,
|
| 2091 |
+
512,
|
| 2092 |
+
512,
|
| 2093 |
+
512,
|
| 2094 |
+
512
|
| 2095 |
+
],
|
| 2096 |
+
[
|
| 2097 |
+
512,
|
| 2098 |
+
512,
|
| 2099 |
+
512,
|
| 2100 |
+
512,
|
| 2101 |
+
512,
|
| 2102 |
+
512,
|
| 2103 |
+
512,
|
| 2104 |
+
512,
|
| 2105 |
+
512,
|
| 2106 |
+
512,
|
| 2107 |
+
512,
|
| 2108 |
+
512,
|
| 2109 |
+
512,
|
| 2110 |
+
512,
|
| 2111 |
+
512,
|
| 2112 |
+
512,
|
| 2113 |
+
512,
|
| 2114 |
+
512,
|
| 2115 |
+
512,
|
| 2116 |
+
512,
|
| 2117 |
+
512,
|
| 2118 |
+
512,
|
| 2119 |
+
512,
|
| 2120 |
+
512,
|
| 2121 |
+
512,
|
| 2122 |
+
512,
|
| 2123 |
+
512,
|
| 2124 |
+
512,
|
| 2125 |
+
512,
|
| 2126 |
+
512,
|
| 2127 |
+
512,
|
| 2128 |
+
512,
|
| 2129 |
+
512,
|
| 2130 |
+
512,
|
| 2131 |
+
512,
|
| 2132 |
+
512,
|
| 2133 |
+
512,
|
| 2134 |
+
512,
|
| 2135 |
+
512,
|
| 2136 |
+
512,
|
| 2137 |
+
512,
|
| 2138 |
+
512,
|
| 2139 |
+
512,
|
| 2140 |
+
512,
|
| 2141 |
+
512,
|
| 2142 |
+
512,
|
| 2143 |
+
512,
|
| 2144 |
+
512,
|
| 2145 |
+
512,
|
| 2146 |
+
512,
|
| 2147 |
+
512,
|
| 2148 |
+
512,
|
| 2149 |
+
512,
|
| 2150 |
+
512,
|
| 2151 |
+
512,
|
| 2152 |
+
512,
|
| 2153 |
+
512,
|
| 2154 |
+
512,
|
| 2155 |
+
512,
|
| 2156 |
+
512,
|
| 2157 |
+
512,
|
| 2158 |
+
512,
|
| 2159 |
+
512,
|
| 2160 |
+
512,
|
| 2161 |
+
512,
|
| 2162 |
+
512,
|
| 2163 |
+
512,
|
| 2164 |
+
512,
|
| 2165 |
+
512,
|
| 2166 |
+
512,
|
| 2167 |
+
512,
|
| 2168 |
+
512,
|
| 2169 |
+
512,
|
| 2170 |
+
512,
|
| 2171 |
+
512,
|
| 2172 |
+
512,
|
| 2173 |
+
512,
|
| 2174 |
+
512,
|
| 2175 |
+
512,
|
| 2176 |
+
512,
|
| 2177 |
+
512,
|
| 2178 |
+
512,
|
| 2179 |
+
512,
|
| 2180 |
+
512,
|
| 2181 |
+
512,
|
| 2182 |
+
512,
|
| 2183 |
+
512,
|
| 2184 |
+
512,
|
| 2185 |
+
512,
|
| 2186 |
+
512,
|
| 2187 |
+
512,
|
| 2188 |
+
512,
|
| 2189 |
+
512,
|
| 2190 |
+
512,
|
| 2191 |
+
512,
|
| 2192 |
+
512,
|
| 2193 |
+
512,
|
| 2194 |
+
512,
|
| 2195 |
+
512,
|
| 2196 |
+
512,
|
| 2197 |
+
512,
|
| 2198 |
+
512,
|
| 2199 |
+
512,
|
| 2200 |
+
512,
|
| 2201 |
+
512,
|
| 2202 |
+
512,
|
| 2203 |
+
512,
|
| 2204 |
+
512,
|
| 2205 |
+
512,
|
| 2206 |
+
512,
|
| 2207 |
+
512,
|
| 2208 |
+
512,
|
| 2209 |
+
512,
|
| 2210 |
+
512,
|
| 2211 |
+
512,
|
| 2212 |
+
512,
|
| 2213 |
+
512,
|
| 2214 |
+
512,
|
| 2215 |
+
512,
|
| 2216 |
+
512,
|
| 2217 |
+
512,
|
| 2218 |
+
512,
|
| 2219 |
+
512,
|
| 2220 |
+
512,
|
| 2221 |
+
512,
|
| 2222 |
+
512,
|
| 2223 |
+
512,
|
| 2224 |
+
512
|
| 2225 |
+
],
|
| 2226 |
+
[
|
| 2227 |
+
512,
|
| 2228 |
+
512,
|
| 2229 |
+
512,
|
| 2230 |
+
512,
|
| 2231 |
+
512,
|
| 2232 |
+
512,
|
| 2233 |
+
512,
|
| 2234 |
+
512,
|
| 2235 |
+
512,
|
| 2236 |
+
512,
|
| 2237 |
+
512,
|
| 2238 |
+
512,
|
| 2239 |
+
512,
|
| 2240 |
+
512,
|
| 2241 |
+
512,
|
| 2242 |
+
512,
|
| 2243 |
+
512,
|
| 2244 |
+
512,
|
| 2245 |
+
512,
|
| 2246 |
+
512,
|
| 2247 |
+
512,
|
| 2248 |
+
512,
|
| 2249 |
+
512,
|
| 2250 |
+
512,
|
| 2251 |
+
512,
|
| 2252 |
+
512,
|
| 2253 |
+
512,
|
| 2254 |
+
512,
|
| 2255 |
+
512,
|
| 2256 |
+
512,
|
| 2257 |
+
512,
|
| 2258 |
+
512,
|
| 2259 |
+
512,
|
| 2260 |
+
512,
|
| 2261 |
+
512,
|
| 2262 |
+
512,
|
| 2263 |
+
512,
|
| 2264 |
+
512,
|
| 2265 |
+
512,
|
| 2266 |
+
512,
|
| 2267 |
+
512,
|
| 2268 |
+
512,
|
| 2269 |
+
512,
|
| 2270 |
+
512,
|
| 2271 |
+
512,
|
| 2272 |
+
512,
|
| 2273 |
+
512,
|
| 2274 |
+
512,
|
| 2275 |
+
512,
|
| 2276 |
+
512,
|
| 2277 |
+
512,
|
| 2278 |
+
512,
|
| 2279 |
+
512,
|
| 2280 |
+
512,
|
| 2281 |
+
512,
|
| 2282 |
+
512,
|
| 2283 |
+
512,
|
| 2284 |
+
512,
|
| 2285 |
+
512,
|
| 2286 |
+
512,
|
| 2287 |
+
512,
|
| 2288 |
+
512,
|
| 2289 |
+
512,
|
| 2290 |
+
512,
|
| 2291 |
+
512,
|
| 2292 |
+
512,
|
| 2293 |
+
512,
|
| 2294 |
+
512,
|
| 2295 |
+
512,
|
| 2296 |
+
512,
|
| 2297 |
+
512,
|
| 2298 |
+
512,
|
| 2299 |
+
512,
|
| 2300 |
+
512,
|
| 2301 |
+
512,
|
| 2302 |
+
512,
|
| 2303 |
+
512,
|
| 2304 |
+
512,
|
| 2305 |
+
512,
|
| 2306 |
+
512,
|
| 2307 |
+
512,
|
| 2308 |
+
512,
|
| 2309 |
+
512,
|
| 2310 |
+
512,
|
| 2311 |
+
512,
|
| 2312 |
+
512,
|
| 2313 |
+
512,
|
| 2314 |
+
512,
|
| 2315 |
+
512,
|
| 2316 |
+
512,
|
| 2317 |
+
512,
|
| 2318 |
+
512,
|
| 2319 |
+
512,
|
| 2320 |
+
512,
|
| 2321 |
+
512,
|
| 2322 |
+
512,
|
| 2323 |
+
512,
|
| 2324 |
+
512,
|
| 2325 |
+
512,
|
| 2326 |
+
512,
|
| 2327 |
+
512,
|
| 2328 |
+
512,
|
| 2329 |
+
512,
|
| 2330 |
+
512,
|
| 2331 |
+
512,
|
| 2332 |
+
512,
|
| 2333 |
+
512,
|
| 2334 |
+
512,
|
| 2335 |
+
512,
|
| 2336 |
+
512,
|
| 2337 |
+
512,
|
| 2338 |
+
512,
|
| 2339 |
+
512,
|
| 2340 |
+
512,
|
| 2341 |
+
512,
|
| 2342 |
+
512,
|
| 2343 |
+
512,
|
| 2344 |
+
512,
|
| 2345 |
+
512,
|
| 2346 |
+
512,
|
| 2347 |
+
512,
|
| 2348 |
+
512,
|
| 2349 |
+
512,
|
| 2350 |
+
512,
|
| 2351 |
+
512,
|
| 2352 |
+
512,
|
| 2353 |
+
512,
|
| 2354 |
+
512
|
| 2355 |
+
],
|
| 2356 |
+
[
|
| 2357 |
+
512,
|
| 2358 |
+
512,
|
| 2359 |
+
512,
|
| 2360 |
+
512,
|
| 2361 |
+
512,
|
| 2362 |
+
512,
|
| 2363 |
+
512,
|
| 2364 |
+
512,
|
| 2365 |
+
512,
|
| 2366 |
+
512,
|
| 2367 |
+
512,
|
| 2368 |
+
512,
|
| 2369 |
+
512,
|
| 2370 |
+
512,
|
| 2371 |
+
512,
|
| 2372 |
+
512,
|
| 2373 |
+
512,
|
| 2374 |
+
512,
|
| 2375 |
+
512,
|
| 2376 |
+
512,
|
| 2377 |
+
512,
|
| 2378 |
+
512,
|
| 2379 |
+
512,
|
| 2380 |
+
512,
|
| 2381 |
+
512,
|
| 2382 |
+
512,
|
| 2383 |
+
512,
|
| 2384 |
+
512,
|
| 2385 |
+
512,
|
| 2386 |
+
512,
|
| 2387 |
+
512,
|
| 2388 |
+
512,
|
| 2389 |
+
512,
|
| 2390 |
+
512,
|
| 2391 |
+
512,
|
| 2392 |
+
512,
|
| 2393 |
+
512,
|
| 2394 |
+
512,
|
| 2395 |
+
512,
|
| 2396 |
+
512,
|
| 2397 |
+
512,
|
| 2398 |
+
512,
|
| 2399 |
+
512,
|
| 2400 |
+
512,
|
| 2401 |
+
512,
|
| 2402 |
+
512,
|
| 2403 |
+
512,
|
| 2404 |
+
512,
|
| 2405 |
+
512,
|
| 2406 |
+
512,
|
| 2407 |
+
512,
|
| 2408 |
+
512,
|
| 2409 |
+
512,
|
| 2410 |
+
512,
|
| 2411 |
+
512,
|
| 2412 |
+
512,
|
| 2413 |
+
512,
|
| 2414 |
+
512,
|
| 2415 |
+
512,
|
| 2416 |
+
512,
|
| 2417 |
+
512,
|
| 2418 |
+
512,
|
| 2419 |
+
512,
|
| 2420 |
+
512,
|
| 2421 |
+
512,
|
| 2422 |
+
512,
|
| 2423 |
+
512,
|
| 2424 |
+
512,
|
| 2425 |
+
512,
|
| 2426 |
+
512,
|
| 2427 |
+
512,
|
| 2428 |
+
512,
|
| 2429 |
+
512,
|
| 2430 |
+
512,
|
| 2431 |
+
512,
|
| 2432 |
+
512,
|
| 2433 |
+
512,
|
| 2434 |
+
512,
|
| 2435 |
+
512,
|
| 2436 |
+
512,
|
| 2437 |
+
512,
|
| 2438 |
+
512,
|
| 2439 |
+
512,
|
| 2440 |
+
512,
|
| 2441 |
+
512,
|
| 2442 |
+
512,
|
| 2443 |
+
512,
|
| 2444 |
+
512,
|
| 2445 |
+
512,
|
| 2446 |
+
512,
|
| 2447 |
+
512,
|
| 2448 |
+
512,
|
| 2449 |
+
512,
|
| 2450 |
+
512,
|
| 2451 |
+
512,
|
| 2452 |
+
512,
|
| 2453 |
+
512,
|
| 2454 |
+
512,
|
| 2455 |
+
512,
|
| 2456 |
+
512,
|
| 2457 |
+
512,
|
| 2458 |
+
512,
|
| 2459 |
+
512,
|
| 2460 |
+
512,
|
| 2461 |
+
512,
|
| 2462 |
+
512,
|
| 2463 |
+
512,
|
| 2464 |
+
512,
|
| 2465 |
+
512,
|
| 2466 |
+
512,
|
| 2467 |
+
512,
|
| 2468 |
+
512,
|
| 2469 |
+
512,
|
| 2470 |
+
512,
|
| 2471 |
+
512,
|
| 2472 |
+
512,
|
| 2473 |
+
512,
|
| 2474 |
+
512,
|
| 2475 |
+
512,
|
| 2476 |
+
512,
|
| 2477 |
+
512,
|
| 2478 |
+
512,
|
| 2479 |
+
512,
|
| 2480 |
+
512,
|
| 2481 |
+
512,
|
| 2482 |
+
512,
|
| 2483 |
+
512,
|
| 2484 |
+
512
|
| 2485 |
+
],
|
| 2486 |
+
[
|
| 2487 |
+
512,
|
| 2488 |
+
512,
|
| 2489 |
+
512,
|
| 2490 |
+
512,
|
| 2491 |
+
512,
|
| 2492 |
+
512,
|
| 2493 |
+
512,
|
| 2494 |
+
512,
|
| 2495 |
+
512,
|
| 2496 |
+
512,
|
| 2497 |
+
512,
|
| 2498 |
+
512,
|
| 2499 |
+
512,
|
| 2500 |
+
512,
|
| 2501 |
+
512,
|
| 2502 |
+
512,
|
| 2503 |
+
512,
|
| 2504 |
+
512,
|
| 2505 |
+
512,
|
| 2506 |
+
512,
|
| 2507 |
+
512,
|
| 2508 |
+
512,
|
| 2509 |
+
512,
|
| 2510 |
+
512,
|
| 2511 |
+
512,
|
| 2512 |
+
512,
|
| 2513 |
+
512,
|
| 2514 |
+
512,
|
| 2515 |
+
512,
|
| 2516 |
+
512,
|
| 2517 |
+
512,
|
| 2518 |
+
512,
|
| 2519 |
+
512,
|
| 2520 |
+
512,
|
| 2521 |
+
512,
|
| 2522 |
+
512,
|
| 2523 |
+
512,
|
| 2524 |
+
512,
|
| 2525 |
+
512,
|
| 2526 |
+
512,
|
| 2527 |
+
512,
|
| 2528 |
+
512,
|
| 2529 |
+
512,
|
| 2530 |
+
512,
|
| 2531 |
+
512,
|
| 2532 |
+
512,
|
| 2533 |
+
512,
|
| 2534 |
+
512,
|
| 2535 |
+
512,
|
| 2536 |
+
512,
|
| 2537 |
+
512,
|
| 2538 |
+
512,
|
| 2539 |
+
512,
|
| 2540 |
+
512,
|
| 2541 |
+
512,
|
| 2542 |
+
512,
|
| 2543 |
+
512,
|
| 2544 |
+
512,
|
| 2545 |
+
512,
|
| 2546 |
+
512,
|
| 2547 |
+
512,
|
| 2548 |
+
512,
|
| 2549 |
+
512,
|
| 2550 |
+
512,
|
| 2551 |
+
512,
|
| 2552 |
+
512,
|
| 2553 |
+
512,
|
| 2554 |
+
512,
|
| 2555 |
+
512,
|
| 2556 |
+
512,
|
| 2557 |
+
512,
|
| 2558 |
+
512,
|
| 2559 |
+
512,
|
| 2560 |
+
512,
|
| 2561 |
+
512,
|
| 2562 |
+
512,
|
| 2563 |
+
512,
|
| 2564 |
+
512,
|
| 2565 |
+
512,
|
| 2566 |
+
512,
|
| 2567 |
+
512,
|
| 2568 |
+
512,
|
| 2569 |
+
512,
|
| 2570 |
+
512,
|
| 2571 |
+
512,
|
| 2572 |
+
512,
|
| 2573 |
+
512,
|
| 2574 |
+
512,
|
| 2575 |
+
512,
|
| 2576 |
+
512,
|
| 2577 |
+
512,
|
| 2578 |
+
512,
|
| 2579 |
+
512,
|
| 2580 |
+
512,
|
| 2581 |
+
512,
|
| 2582 |
+
512,
|
| 2583 |
+
512,
|
| 2584 |
+
512,
|
| 2585 |
+
512,
|
| 2586 |
+
512,
|
| 2587 |
+
512,
|
| 2588 |
+
512,
|
| 2589 |
+
512,
|
| 2590 |
+
512,
|
| 2591 |
+
512,
|
| 2592 |
+
512,
|
| 2593 |
+
512,
|
| 2594 |
+
512,
|
| 2595 |
+
512,
|
| 2596 |
+
512,
|
| 2597 |
+
512,
|
| 2598 |
+
512,
|
| 2599 |
+
512,
|
| 2600 |
+
512,
|
| 2601 |
+
512,
|
| 2602 |
+
512,
|
| 2603 |
+
512,
|
| 2604 |
+
512,
|
| 2605 |
+
512,
|
| 2606 |
+
512,
|
| 2607 |
+
512,
|
| 2608 |
+
512,
|
| 2609 |
+
512,
|
| 2610 |
+
512,
|
| 2611 |
+
512,
|
| 2612 |
+
512,
|
| 2613 |
+
512,
|
| 2614 |
+
512
|
| 2615 |
+
],
|
| 2616 |
+
[
|
| 2617 |
+
512,
|
| 2618 |
+
512,
|
| 2619 |
+
512,
|
| 2620 |
+
512,
|
| 2621 |
+
512,
|
| 2622 |
+
512,
|
| 2623 |
+
512,
|
| 2624 |
+
512,
|
| 2625 |
+
512,
|
| 2626 |
+
512,
|
| 2627 |
+
512,
|
| 2628 |
+
512,
|
| 2629 |
+
512,
|
| 2630 |
+
512,
|
| 2631 |
+
512,
|
| 2632 |
+
512,
|
| 2633 |
+
512,
|
| 2634 |
+
512,
|
| 2635 |
+
512,
|
| 2636 |
+
512,
|
| 2637 |
+
512,
|
| 2638 |
+
512,
|
| 2639 |
+
512,
|
| 2640 |
+
512,
|
| 2641 |
+
512,
|
| 2642 |
+
512,
|
| 2643 |
+
512,
|
| 2644 |
+
512,
|
| 2645 |
+
512,
|
| 2646 |
+
512,
|
| 2647 |
+
512,
|
| 2648 |
+
512,
|
| 2649 |
+
512,
|
| 2650 |
+
512,
|
| 2651 |
+
512,
|
| 2652 |
+
512,
|
| 2653 |
+
512,
|
| 2654 |
+
512,
|
| 2655 |
+
512,
|
| 2656 |
+
512,
|
| 2657 |
+
512,
|
| 2658 |
+
512,
|
| 2659 |
+
512,
|
| 2660 |
+
512,
|
| 2661 |
+
512,
|
| 2662 |
+
512,
|
| 2663 |
+
512,
|
| 2664 |
+
512,
|
| 2665 |
+
512,
|
| 2666 |
+
512,
|
| 2667 |
+
512,
|
| 2668 |
+
512,
|
| 2669 |
+
512,
|
| 2670 |
+
512,
|
| 2671 |
+
512,
|
| 2672 |
+
512,
|
| 2673 |
+
512,
|
| 2674 |
+
512,
|
| 2675 |
+
512,
|
| 2676 |
+
512,
|
| 2677 |
+
512,
|
| 2678 |
+
512,
|
| 2679 |
+
512,
|
| 2680 |
+
512,
|
| 2681 |
+
512,
|
| 2682 |
+
512,
|
| 2683 |
+
512,
|
| 2684 |
+
512,
|
| 2685 |
+
512,
|
| 2686 |
+
512,
|
| 2687 |
+
512,
|
| 2688 |
+
512,
|
| 2689 |
+
512,
|
| 2690 |
+
512,
|
| 2691 |
+
512,
|
| 2692 |
+
512,
|
| 2693 |
+
512,
|
| 2694 |
+
512,
|
| 2695 |
+
512,
|
| 2696 |
+
512,
|
| 2697 |
+
512,
|
| 2698 |
+
512,
|
| 2699 |
+
512,
|
| 2700 |
+
512,
|
| 2701 |
+
512,
|
| 2702 |
+
512,
|
| 2703 |
+
512,
|
| 2704 |
+
512,
|
| 2705 |
+
512,
|
| 2706 |
+
512,
|
| 2707 |
+
512,
|
| 2708 |
+
512,
|
| 2709 |
+
512,
|
| 2710 |
+
512,
|
| 2711 |
+
512,
|
| 2712 |
+
512,
|
| 2713 |
+
512,
|
| 2714 |
+
512,
|
| 2715 |
+
512,
|
| 2716 |
+
512,
|
| 2717 |
+
512,
|
| 2718 |
+
512,
|
| 2719 |
+
512,
|
| 2720 |
+
512,
|
| 2721 |
+
512,
|
| 2722 |
+
512,
|
| 2723 |
+
512,
|
| 2724 |
+
512,
|
| 2725 |
+
512,
|
| 2726 |
+
512,
|
| 2727 |
+
512,
|
| 2728 |
+
512,
|
| 2729 |
+
512,
|
| 2730 |
+
512,
|
| 2731 |
+
512,
|
| 2732 |
+
512,
|
| 2733 |
+
512,
|
| 2734 |
+
512,
|
| 2735 |
+
512,
|
| 2736 |
+
512,
|
| 2737 |
+
512,
|
| 2738 |
+
512,
|
| 2739 |
+
512,
|
| 2740 |
+
512,
|
| 2741 |
+
512,
|
| 2742 |
+
512,
|
| 2743 |
+
512,
|
| 2744 |
+
512
|
| 2745 |
+
],
|
| 2746 |
+
[
|
| 2747 |
+
512,
|
| 2748 |
+
512,
|
| 2749 |
+
512,
|
| 2750 |
+
512,
|
| 2751 |
+
512,
|
| 2752 |
+
512,
|
| 2753 |
+
512,
|
| 2754 |
+
512,
|
| 2755 |
+
512,
|
| 2756 |
+
512,
|
| 2757 |
+
512,
|
| 2758 |
+
512,
|
| 2759 |
+
512,
|
| 2760 |
+
512,
|
| 2761 |
+
512,
|
| 2762 |
+
512,
|
| 2763 |
+
512,
|
| 2764 |
+
512,
|
| 2765 |
+
512,
|
| 2766 |
+
512,
|
| 2767 |
+
512,
|
| 2768 |
+
512,
|
| 2769 |
+
512,
|
| 2770 |
+
512,
|
| 2771 |
+
512,
|
| 2772 |
+
512,
|
| 2773 |
+
512,
|
| 2774 |
+
512,
|
| 2775 |
+
512,
|
| 2776 |
+
512,
|
| 2777 |
+
512,
|
| 2778 |
+
512,
|
| 2779 |
+
512,
|
| 2780 |
+
512,
|
| 2781 |
+
512,
|
| 2782 |
+
512,
|
| 2783 |
+
512,
|
| 2784 |
+
512,
|
| 2785 |
+
512,
|
| 2786 |
+
512,
|
| 2787 |
+
512,
|
| 2788 |
+
512,
|
| 2789 |
+
512,
|
| 2790 |
+
512,
|
| 2791 |
+
512,
|
| 2792 |
+
512,
|
| 2793 |
+
512,
|
| 2794 |
+
512,
|
| 2795 |
+
512,
|
| 2796 |
+
512,
|
| 2797 |
+
512,
|
| 2798 |
+
512,
|
| 2799 |
+
512,
|
| 2800 |
+
512,
|
| 2801 |
+
512,
|
| 2802 |
+
512,
|
| 2803 |
+
512,
|
| 2804 |
+
512,
|
| 2805 |
+
512,
|
| 2806 |
+
512,
|
| 2807 |
+
512,
|
| 2808 |
+
512,
|
| 2809 |
+
512,
|
| 2810 |
+
512,
|
| 2811 |
+
512,
|
| 2812 |
+
512,
|
| 2813 |
+
512,
|
| 2814 |
+
512,
|
| 2815 |
+
512,
|
| 2816 |
+
512,
|
| 2817 |
+
512,
|
| 2818 |
+
512,
|
| 2819 |
+
512,
|
| 2820 |
+
512,
|
| 2821 |
+
512,
|
| 2822 |
+
512,
|
| 2823 |
+
512,
|
| 2824 |
+
512,
|
| 2825 |
+
512,
|
| 2826 |
+
512,
|
| 2827 |
+
512,
|
| 2828 |
+
512,
|
| 2829 |
+
512,
|
| 2830 |
+
512,
|
| 2831 |
+
512,
|
| 2832 |
+
512,
|
| 2833 |
+
512,
|
| 2834 |
+
512,
|
| 2835 |
+
512,
|
| 2836 |
+
512,
|
| 2837 |
+
512,
|
| 2838 |
+
512,
|
| 2839 |
+
512,
|
| 2840 |
+
512,
|
| 2841 |
+
512,
|
| 2842 |
+
512,
|
| 2843 |
+
512,
|
| 2844 |
+
512,
|
| 2845 |
+
512,
|
| 2846 |
+
512,
|
| 2847 |
+
512,
|
| 2848 |
+
512,
|
| 2849 |
+
512,
|
| 2850 |
+
512,
|
| 2851 |
+
512,
|
| 2852 |
+
512,
|
| 2853 |
+
512,
|
| 2854 |
+
512,
|
| 2855 |
+
512,
|
| 2856 |
+
512,
|
| 2857 |
+
512,
|
| 2858 |
+
512,
|
| 2859 |
+
512,
|
| 2860 |
+
512,
|
| 2861 |
+
512,
|
| 2862 |
+
512,
|
| 2863 |
+
512,
|
| 2864 |
+
512,
|
| 2865 |
+
512,
|
| 2866 |
+
512,
|
| 2867 |
+
512,
|
| 2868 |
+
512,
|
| 2869 |
+
512,
|
| 2870 |
+
512,
|
| 2871 |
+
512,
|
| 2872 |
+
512,
|
| 2873 |
+
512,
|
| 2874 |
+
512
|
| 2875 |
+
],
|
| 2876 |
+
[
|
| 2877 |
+
512,
|
| 2878 |
+
512,
|
| 2879 |
+
512,
|
| 2880 |
+
512,
|
| 2881 |
+
512,
|
| 2882 |
+
512,
|
| 2883 |
+
512,
|
| 2884 |
+
512,
|
| 2885 |
+
512,
|
| 2886 |
+
512,
|
| 2887 |
+
512,
|
| 2888 |
+
512,
|
| 2889 |
+
512,
|
| 2890 |
+
512,
|
| 2891 |
+
512,
|
| 2892 |
+
512,
|
| 2893 |
+
512,
|
| 2894 |
+
512,
|
| 2895 |
+
512,
|
| 2896 |
+
512,
|
| 2897 |
+
512,
|
| 2898 |
+
512,
|
| 2899 |
+
512,
|
| 2900 |
+
512,
|
| 2901 |
+
512,
|
| 2902 |
+
512,
|
| 2903 |
+
512,
|
| 2904 |
+
512,
|
| 2905 |
+
512,
|
| 2906 |
+
512,
|
| 2907 |
+
512,
|
| 2908 |
+
512,
|
| 2909 |
+
512,
|
| 2910 |
+
512,
|
| 2911 |
+
512,
|
| 2912 |
+
512,
|
| 2913 |
+
512,
|
| 2914 |
+
512,
|
| 2915 |
+
512,
|
| 2916 |
+
512,
|
| 2917 |
+
512,
|
| 2918 |
+
512,
|
| 2919 |
+
512,
|
| 2920 |
+
512,
|
| 2921 |
+
512,
|
| 2922 |
+
512,
|
| 2923 |
+
512,
|
| 2924 |
+
512,
|
| 2925 |
+
512,
|
| 2926 |
+
512,
|
| 2927 |
+
512,
|
| 2928 |
+
512,
|
| 2929 |
+
512,
|
| 2930 |
+
512,
|
| 2931 |
+
512,
|
| 2932 |
+
512,
|
| 2933 |
+
512,
|
| 2934 |
+
512,
|
| 2935 |
+
512,
|
| 2936 |
+
512,
|
| 2937 |
+
512,
|
| 2938 |
+
512,
|
| 2939 |
+
512,
|
| 2940 |
+
512,
|
| 2941 |
+
512,
|
| 2942 |
+
512,
|
| 2943 |
+
512,
|
| 2944 |
+
512,
|
| 2945 |
+
512,
|
| 2946 |
+
512,
|
| 2947 |
+
512,
|
| 2948 |
+
512,
|
| 2949 |
+
512,
|
| 2950 |
+
512,
|
| 2951 |
+
512,
|
| 2952 |
+
512,
|
| 2953 |
+
512,
|
| 2954 |
+
512,
|
| 2955 |
+
512,
|
| 2956 |
+
512,
|
| 2957 |
+
512,
|
| 2958 |
+
512,
|
| 2959 |
+
512,
|
| 2960 |
+
512,
|
| 2961 |
+
512,
|
| 2962 |
+
512,
|
| 2963 |
+
512,
|
| 2964 |
+
512,
|
| 2965 |
+
512,
|
| 2966 |
+
512,
|
| 2967 |
+
512,
|
| 2968 |
+
512,
|
| 2969 |
+
512,
|
| 2970 |
+
512,
|
| 2971 |
+
512,
|
| 2972 |
+
512,
|
| 2973 |
+
512,
|
| 2974 |
+
512,
|
| 2975 |
+
512,
|
| 2976 |
+
512,
|
| 2977 |
+
512,
|
| 2978 |
+
512,
|
| 2979 |
+
512,
|
| 2980 |
+
512,
|
| 2981 |
+
512,
|
| 2982 |
+
512,
|
| 2983 |
+
512,
|
| 2984 |
+
512,
|
| 2985 |
+
512,
|
| 2986 |
+
512,
|
| 2987 |
+
512,
|
| 2988 |
+
512,
|
| 2989 |
+
512,
|
| 2990 |
+
512,
|
| 2991 |
+
512,
|
| 2992 |
+
512,
|
| 2993 |
+
512,
|
| 2994 |
+
512,
|
| 2995 |
+
512,
|
| 2996 |
+
512,
|
| 2997 |
+
512,
|
| 2998 |
+
512,
|
| 2999 |
+
512,
|
| 3000 |
+
512,
|
| 3001 |
+
512,
|
| 3002 |
+
512,
|
| 3003 |
+
512,
|
| 3004 |
+
512
|
| 3005 |
+
],
|
| 3006 |
+
[
|
| 3007 |
+
512,
|
| 3008 |
+
512,
|
| 3009 |
+
512,
|
| 3010 |
+
512,
|
| 3011 |
+
512,
|
| 3012 |
+
512,
|
| 3013 |
+
512,
|
| 3014 |
+
512,
|
| 3015 |
+
512,
|
| 3016 |
+
512,
|
| 3017 |
+
512,
|
| 3018 |
+
512,
|
| 3019 |
+
512,
|
| 3020 |
+
512,
|
| 3021 |
+
512,
|
| 3022 |
+
512,
|
| 3023 |
+
512,
|
| 3024 |
+
512,
|
| 3025 |
+
512,
|
| 3026 |
+
512,
|
| 3027 |
+
512,
|
| 3028 |
+
512,
|
| 3029 |
+
512,
|
| 3030 |
+
512,
|
| 3031 |
+
512,
|
| 3032 |
+
512,
|
| 3033 |
+
512,
|
| 3034 |
+
512,
|
| 3035 |
+
512,
|
| 3036 |
+
512,
|
| 3037 |
+
512,
|
| 3038 |
+
512,
|
| 3039 |
+
512,
|
| 3040 |
+
512,
|
| 3041 |
+
512,
|
| 3042 |
+
512,
|
| 3043 |
+
512,
|
| 3044 |
+
512,
|
| 3045 |
+
512,
|
| 3046 |
+
512,
|
| 3047 |
+
512,
|
| 3048 |
+
512,
|
| 3049 |
+
512,
|
| 3050 |
+
512,
|
| 3051 |
+
512,
|
| 3052 |
+
512,
|
| 3053 |
+
512,
|
| 3054 |
+
512,
|
| 3055 |
+
512,
|
| 3056 |
+
512,
|
| 3057 |
+
512,
|
| 3058 |
+
512,
|
| 3059 |
+
512,
|
| 3060 |
+
512,
|
| 3061 |
+
512,
|
| 3062 |
+
512,
|
| 3063 |
+
512,
|
| 3064 |
+
512,
|
| 3065 |
+
512,
|
| 3066 |
+
512,
|
| 3067 |
+
512,
|
| 3068 |
+
512,
|
| 3069 |
+
512,
|
| 3070 |
+
512,
|
| 3071 |
+
512,
|
| 3072 |
+
512,
|
| 3073 |
+
512,
|
| 3074 |
+
512,
|
| 3075 |
+
512,
|
| 3076 |
+
512,
|
| 3077 |
+
512,
|
| 3078 |
+
512,
|
| 3079 |
+
512,
|
| 3080 |
+
512,
|
| 3081 |
+
512,
|
| 3082 |
+
512,
|
| 3083 |
+
512,
|
| 3084 |
+
512,
|
| 3085 |
+
512,
|
| 3086 |
+
512,
|
| 3087 |
+
512,
|
| 3088 |
+
512,
|
| 3089 |
+
512,
|
| 3090 |
+
512,
|
| 3091 |
+
512,
|
| 3092 |
+
512,
|
| 3093 |
+
512,
|
| 3094 |
+
512,
|
| 3095 |
+
512,
|
| 3096 |
+
512,
|
| 3097 |
+
512,
|
| 3098 |
+
512,
|
| 3099 |
+
512,
|
| 3100 |
+
512,
|
| 3101 |
+
512,
|
| 3102 |
+
512,
|
| 3103 |
+
512,
|
| 3104 |
+
512,
|
| 3105 |
+
512,
|
| 3106 |
+
512,
|
| 3107 |
+
512,
|
| 3108 |
+
512,
|
| 3109 |
+
512,
|
| 3110 |
+
512,
|
| 3111 |
+
512,
|
| 3112 |
+
512,
|
| 3113 |
+
512,
|
| 3114 |
+
512,
|
| 3115 |
+
512,
|
| 3116 |
+
512,
|
| 3117 |
+
512,
|
| 3118 |
+
512,
|
| 3119 |
+
512,
|
| 3120 |
+
512,
|
| 3121 |
+
512,
|
| 3122 |
+
512,
|
| 3123 |
+
512,
|
| 3124 |
+
512,
|
| 3125 |
+
512,
|
| 3126 |
+
512,
|
| 3127 |
+
512,
|
| 3128 |
+
512,
|
| 3129 |
+
512,
|
| 3130 |
+
512,
|
| 3131 |
+
512,
|
| 3132 |
+
512,
|
| 3133 |
+
512,
|
| 3134 |
+
512
|
| 3135 |
+
],
|
| 3136 |
+
[
|
| 3137 |
+
512,
|
| 3138 |
+
512,
|
| 3139 |
+
512,
|
| 3140 |
+
512,
|
| 3141 |
+
512,
|
| 3142 |
+
512,
|
| 3143 |
+
512,
|
| 3144 |
+
512,
|
| 3145 |
+
512,
|
| 3146 |
+
512,
|
| 3147 |
+
512,
|
| 3148 |
+
512,
|
| 3149 |
+
512,
|
| 3150 |
+
512,
|
| 3151 |
+
512,
|
| 3152 |
+
512,
|
| 3153 |
+
512,
|
| 3154 |
+
512,
|
| 3155 |
+
512,
|
| 3156 |
+
512,
|
| 3157 |
+
512,
|
| 3158 |
+
512,
|
| 3159 |
+
512,
|
| 3160 |
+
512,
|
| 3161 |
+
512,
|
| 3162 |
+
512,
|
| 3163 |
+
512,
|
| 3164 |
+
512,
|
| 3165 |
+
512,
|
| 3166 |
+
512,
|
| 3167 |
+
512,
|
| 3168 |
+
512,
|
| 3169 |
+
512,
|
| 3170 |
+
512,
|
| 3171 |
+
512,
|
| 3172 |
+
512,
|
| 3173 |
+
512,
|
| 3174 |
+
512,
|
| 3175 |
+
512,
|
| 3176 |
+
512,
|
| 3177 |
+
512,
|
| 3178 |
+
512,
|
| 3179 |
+
512,
|
| 3180 |
+
512,
|
| 3181 |
+
512,
|
| 3182 |
+
512,
|
| 3183 |
+
512,
|
| 3184 |
+
512,
|
| 3185 |
+
512,
|
| 3186 |
+
512,
|
| 3187 |
+
512,
|
| 3188 |
+
512,
|
| 3189 |
+
512,
|
| 3190 |
+
512,
|
| 3191 |
+
512,
|
| 3192 |
+
512,
|
| 3193 |
+
512,
|
| 3194 |
+
512,
|
| 3195 |
+
512,
|
| 3196 |
+
512,
|
| 3197 |
+
512,
|
| 3198 |
+
512,
|
| 3199 |
+
512,
|
| 3200 |
+
512,
|
| 3201 |
+
512,
|
| 3202 |
+
512,
|
| 3203 |
+
512,
|
| 3204 |
+
512,
|
| 3205 |
+
512,
|
| 3206 |
+
512,
|
| 3207 |
+
512,
|
| 3208 |
+
512,
|
| 3209 |
+
512,
|
| 3210 |
+
512,
|
| 3211 |
+
512,
|
| 3212 |
+
512,
|
| 3213 |
+
512,
|
| 3214 |
+
512,
|
| 3215 |
+
512,
|
| 3216 |
+
512,
|
| 3217 |
+
512,
|
| 3218 |
+
512,
|
| 3219 |
+
512,
|
| 3220 |
+
512,
|
| 3221 |
+
512,
|
| 3222 |
+
512,
|
| 3223 |
+
512,
|
| 3224 |
+
512,
|
| 3225 |
+
512,
|
| 3226 |
+
512,
|
| 3227 |
+
512,
|
| 3228 |
+
512,
|
| 3229 |
+
512,
|
| 3230 |
+
512,
|
| 3231 |
+
512,
|
| 3232 |
+
512,
|
| 3233 |
+
512,
|
| 3234 |
+
512,
|
| 3235 |
+
512,
|
| 3236 |
+
512,
|
| 3237 |
+
512,
|
| 3238 |
+
512,
|
| 3239 |
+
512,
|
| 3240 |
+
512,
|
| 3241 |
+
512,
|
| 3242 |
+
512,
|
| 3243 |
+
512,
|
| 3244 |
+
512,
|
| 3245 |
+
512,
|
| 3246 |
+
512,
|
| 3247 |
+
512,
|
| 3248 |
+
512,
|
| 3249 |
+
512,
|
| 3250 |
+
512,
|
| 3251 |
+
512,
|
| 3252 |
+
512,
|
| 3253 |
+
512,
|
| 3254 |
+
512,
|
| 3255 |
+
512,
|
| 3256 |
+
512,
|
| 3257 |
+
512,
|
| 3258 |
+
512,
|
| 3259 |
+
512,
|
| 3260 |
+
512,
|
| 3261 |
+
512,
|
| 3262 |
+
512,
|
| 3263 |
+
512,
|
| 3264 |
+
512
|
| 3265 |
+
],
|
| 3266 |
+
[
|
| 3267 |
+
512,
|
| 3268 |
+
512,
|
| 3269 |
+
512,
|
| 3270 |
+
512,
|
| 3271 |
+
512,
|
| 3272 |
+
512,
|
| 3273 |
+
512,
|
| 3274 |
+
512,
|
| 3275 |
+
512,
|
| 3276 |
+
512,
|
| 3277 |
+
512,
|
| 3278 |
+
512,
|
| 3279 |
+
512,
|
| 3280 |
+
512,
|
| 3281 |
+
512,
|
| 3282 |
+
512,
|
| 3283 |
+
512,
|
| 3284 |
+
512,
|
| 3285 |
+
512,
|
| 3286 |
+
512,
|
| 3287 |
+
512,
|
| 3288 |
+
512,
|
| 3289 |
+
512,
|
| 3290 |
+
512,
|
| 3291 |
+
512,
|
| 3292 |
+
512,
|
| 3293 |
+
512,
|
| 3294 |
+
512,
|
| 3295 |
+
512,
|
| 3296 |
+
512,
|
| 3297 |
+
512,
|
| 3298 |
+
512,
|
| 3299 |
+
512,
|
| 3300 |
+
512,
|
| 3301 |
+
512,
|
| 3302 |
+
512,
|
| 3303 |
+
512,
|
| 3304 |
+
512,
|
| 3305 |
+
512,
|
| 3306 |
+
512,
|
| 3307 |
+
512,
|
| 3308 |
+
512,
|
| 3309 |
+
512,
|
| 3310 |
+
512,
|
| 3311 |
+
512,
|
| 3312 |
+
512,
|
| 3313 |
+
512,
|
| 3314 |
+
512,
|
| 3315 |
+
512,
|
| 3316 |
+
512,
|
| 3317 |
+
512,
|
| 3318 |
+
512,
|
| 3319 |
+
512,
|
| 3320 |
+
512,
|
| 3321 |
+
512,
|
| 3322 |
+
512,
|
| 3323 |
+
512,
|
| 3324 |
+
512,
|
| 3325 |
+
512,
|
| 3326 |
+
512,
|
| 3327 |
+
512,
|
| 3328 |
+
512,
|
| 3329 |
+
512,
|
| 3330 |
+
512,
|
| 3331 |
+
512,
|
| 3332 |
+
512,
|
| 3333 |
+
512,
|
| 3334 |
+
512,
|
| 3335 |
+
512,
|
| 3336 |
+
512,
|
| 3337 |
+
512,
|
| 3338 |
+
512,
|
| 3339 |
+
512,
|
| 3340 |
+
512,
|
| 3341 |
+
512,
|
| 3342 |
+
512,
|
| 3343 |
+
512,
|
| 3344 |
+
512,
|
| 3345 |
+
512,
|
| 3346 |
+
512,
|
| 3347 |
+
512,
|
| 3348 |
+
512,
|
| 3349 |
+
512,
|
| 3350 |
+
512,
|
| 3351 |
+
512,
|
| 3352 |
+
512,
|
| 3353 |
+
512,
|
| 3354 |
+
512,
|
| 3355 |
+
512,
|
| 3356 |
+
512,
|
| 3357 |
+
512,
|
| 3358 |
+
512,
|
| 3359 |
+
512,
|
| 3360 |
+
512,
|
| 3361 |
+
512,
|
| 3362 |
+
512,
|
| 3363 |
+
512,
|
| 3364 |
+
512,
|
| 3365 |
+
512,
|
| 3366 |
+
512,
|
| 3367 |
+
512,
|
| 3368 |
+
512,
|
| 3369 |
+
512,
|
| 3370 |
+
512,
|
| 3371 |
+
512,
|
| 3372 |
+
512,
|
| 3373 |
+
512,
|
| 3374 |
+
512,
|
| 3375 |
+
512,
|
| 3376 |
+
512,
|
| 3377 |
+
512,
|
| 3378 |
+
512,
|
| 3379 |
+
512,
|
| 3380 |
+
512,
|
| 3381 |
+
512,
|
| 3382 |
+
512,
|
| 3383 |
+
512,
|
| 3384 |
+
512,
|
| 3385 |
+
512,
|
| 3386 |
+
512,
|
| 3387 |
+
512,
|
| 3388 |
+
512,
|
| 3389 |
+
512,
|
| 3390 |
+
512,
|
| 3391 |
+
512,
|
| 3392 |
+
512,
|
| 3393 |
+
512,
|
| 3394 |
+
512
|
| 3395 |
+
],
|
| 3396 |
+
[
|
| 3397 |
+
512,
|
| 3398 |
+
512,
|
| 3399 |
+
512,
|
| 3400 |
+
512,
|
| 3401 |
+
512,
|
| 3402 |
+
512,
|
| 3403 |
+
512,
|
| 3404 |
+
512,
|
| 3405 |
+
512,
|
| 3406 |
+
512,
|
| 3407 |
+
512,
|
| 3408 |
+
512,
|
| 3409 |
+
512,
|
| 3410 |
+
512,
|
| 3411 |
+
512,
|
| 3412 |
+
512,
|
| 3413 |
+
512,
|
| 3414 |
+
512,
|
| 3415 |
+
512,
|
| 3416 |
+
512,
|
| 3417 |
+
512,
|
| 3418 |
+
512,
|
| 3419 |
+
512,
|
| 3420 |
+
512,
|
| 3421 |
+
512,
|
| 3422 |
+
512,
|
| 3423 |
+
512,
|
| 3424 |
+
512,
|
| 3425 |
+
512,
|
| 3426 |
+
512,
|
| 3427 |
+
512,
|
| 3428 |
+
512,
|
| 3429 |
+
512,
|
| 3430 |
+
512,
|
| 3431 |
+
512,
|
| 3432 |
+
512,
|
| 3433 |
+
512,
|
| 3434 |
+
512,
|
| 3435 |
+
512,
|
| 3436 |
+
512,
|
| 3437 |
+
512,
|
| 3438 |
+
512,
|
| 3439 |
+
512,
|
| 3440 |
+
512,
|
| 3441 |
+
512,
|
| 3442 |
+
512,
|
| 3443 |
+
512,
|
| 3444 |
+
512,
|
| 3445 |
+
512,
|
| 3446 |
+
512,
|
| 3447 |
+
512,
|
| 3448 |
+
512,
|
| 3449 |
+
512,
|
| 3450 |
+
512,
|
| 3451 |
+
512,
|
| 3452 |
+
512,
|
| 3453 |
+
512,
|
| 3454 |
+
512,
|
| 3455 |
+
512,
|
| 3456 |
+
512,
|
| 3457 |
+
512,
|
| 3458 |
+
512,
|
| 3459 |
+
512,
|
| 3460 |
+
512,
|
| 3461 |
+
512,
|
| 3462 |
+
512,
|
| 3463 |
+
512,
|
| 3464 |
+
512,
|
| 3465 |
+
512,
|
| 3466 |
+
512,
|
| 3467 |
+
512,
|
| 3468 |
+
512,
|
| 3469 |
+
512,
|
| 3470 |
+
512,
|
| 3471 |
+
512,
|
| 3472 |
+
512,
|
| 3473 |
+
512,
|
| 3474 |
+
512,
|
| 3475 |
+
512,
|
| 3476 |
+
512,
|
| 3477 |
+
512,
|
| 3478 |
+
512,
|
| 3479 |
+
512,
|
| 3480 |
+
512,
|
| 3481 |
+
512,
|
| 3482 |
+
512,
|
| 3483 |
+
512,
|
| 3484 |
+
512,
|
| 3485 |
+
512,
|
| 3486 |
+
512,
|
| 3487 |
+
512,
|
| 3488 |
+
512,
|
| 3489 |
+
512,
|
| 3490 |
+
512,
|
| 3491 |
+
512,
|
| 3492 |
+
512,
|
| 3493 |
+
512,
|
| 3494 |
+
512,
|
| 3495 |
+
512,
|
| 3496 |
+
512,
|
| 3497 |
+
512,
|
| 3498 |
+
512,
|
| 3499 |
+
512,
|
| 3500 |
+
512,
|
| 3501 |
+
512,
|
| 3502 |
+
512,
|
| 3503 |
+
512,
|
| 3504 |
+
512,
|
| 3505 |
+
512,
|
| 3506 |
+
512,
|
| 3507 |
+
512,
|
| 3508 |
+
512,
|
| 3509 |
+
512,
|
| 3510 |
+
512,
|
| 3511 |
+
512,
|
| 3512 |
+
512,
|
| 3513 |
+
512,
|
| 3514 |
+
512,
|
| 3515 |
+
512,
|
| 3516 |
+
512,
|
| 3517 |
+
512,
|
| 3518 |
+
512,
|
| 3519 |
+
512,
|
| 3520 |
+
512,
|
| 3521 |
+
512,
|
| 3522 |
+
512,
|
| 3523 |
+
512,
|
| 3524 |
+
512
|
| 3525 |
+
],
|
| 3526 |
+
[
|
| 3527 |
+
512,
|
| 3528 |
+
512,
|
| 3529 |
+
512,
|
| 3530 |
+
512,
|
| 3531 |
+
512,
|
| 3532 |
+
512,
|
| 3533 |
+
512,
|
| 3534 |
+
512,
|
| 3535 |
+
512,
|
| 3536 |
+
512,
|
| 3537 |
+
512,
|
| 3538 |
+
512,
|
| 3539 |
+
512,
|
| 3540 |
+
512,
|
| 3541 |
+
512,
|
| 3542 |
+
512,
|
| 3543 |
+
512,
|
| 3544 |
+
512,
|
| 3545 |
+
512,
|
| 3546 |
+
512,
|
| 3547 |
+
512,
|
| 3548 |
+
512,
|
| 3549 |
+
512,
|
| 3550 |
+
512,
|
| 3551 |
+
512,
|
| 3552 |
+
512,
|
| 3553 |
+
512,
|
| 3554 |
+
512,
|
| 3555 |
+
512,
|
| 3556 |
+
512,
|
| 3557 |
+
512,
|
| 3558 |
+
512,
|
| 3559 |
+
512,
|
| 3560 |
+
512,
|
| 3561 |
+
512,
|
| 3562 |
+
512,
|
| 3563 |
+
512,
|
| 3564 |
+
512,
|
| 3565 |
+
512,
|
| 3566 |
+
512,
|
| 3567 |
+
512,
|
| 3568 |
+
512,
|
| 3569 |
+
512,
|
| 3570 |
+
512,
|
| 3571 |
+
512,
|
| 3572 |
+
512,
|
| 3573 |
+
512,
|
| 3574 |
+
512,
|
| 3575 |
+
512,
|
| 3576 |
+
512,
|
| 3577 |
+
512,
|
| 3578 |
+
512,
|
| 3579 |
+
512,
|
| 3580 |
+
512,
|
| 3581 |
+
512,
|
| 3582 |
+
512,
|
| 3583 |
+
512,
|
| 3584 |
+
512,
|
| 3585 |
+
512,
|
| 3586 |
+
512,
|
| 3587 |
+
512,
|
| 3588 |
+
512,
|
| 3589 |
+
512,
|
| 3590 |
+
512,
|
| 3591 |
+
512,
|
| 3592 |
+
512,
|
| 3593 |
+
512,
|
| 3594 |
+
512,
|
| 3595 |
+
512,
|
| 3596 |
+
512,
|
| 3597 |
+
512,
|
| 3598 |
+
512,
|
| 3599 |
+
512,
|
| 3600 |
+
512,
|
| 3601 |
+
512,
|
| 3602 |
+
512,
|
| 3603 |
+
512,
|
| 3604 |
+
512,
|
| 3605 |
+
512,
|
| 3606 |
+
512,
|
| 3607 |
+
512,
|
| 3608 |
+
512,
|
| 3609 |
+
512,
|
| 3610 |
+
512,
|
| 3611 |
+
512,
|
| 3612 |
+
512,
|
| 3613 |
+
512,
|
| 3614 |
+
512,
|
| 3615 |
+
512,
|
| 3616 |
+
512,
|
| 3617 |
+
512,
|
| 3618 |
+
512,
|
| 3619 |
+
512,
|
| 3620 |
+
512,
|
| 3621 |
+
512,
|
| 3622 |
+
512,
|
| 3623 |
+
512,
|
| 3624 |
+
512,
|
| 3625 |
+
512,
|
| 3626 |
+
512,
|
| 3627 |
+
512,
|
| 3628 |
+
512,
|
| 3629 |
+
512,
|
| 3630 |
+
512,
|
| 3631 |
+
512,
|
| 3632 |
+
512,
|
| 3633 |
+
512,
|
| 3634 |
+
512,
|
| 3635 |
+
512,
|
| 3636 |
+
512,
|
| 3637 |
+
512,
|
| 3638 |
+
512,
|
| 3639 |
+
512,
|
| 3640 |
+
512,
|
| 3641 |
+
512,
|
| 3642 |
+
512,
|
| 3643 |
+
512,
|
| 3644 |
+
512,
|
| 3645 |
+
512,
|
| 3646 |
+
512,
|
| 3647 |
+
512,
|
| 3648 |
+
512,
|
| 3649 |
+
512,
|
| 3650 |
+
512,
|
| 3651 |
+
512,
|
| 3652 |
+
512,
|
| 3653 |
+
512,
|
| 3654 |
+
512
|
| 3655 |
+
],
|
| 3656 |
+
[
|
| 3657 |
+
512,
|
| 3658 |
+
512,
|
| 3659 |
+
512,
|
| 3660 |
+
512,
|
| 3661 |
+
512,
|
| 3662 |
+
512,
|
| 3663 |
+
512,
|
| 3664 |
+
512,
|
| 3665 |
+
512,
|
| 3666 |
+
512,
|
| 3667 |
+
512,
|
| 3668 |
+
512,
|
| 3669 |
+
512,
|
| 3670 |
+
512,
|
| 3671 |
+
512,
|
| 3672 |
+
512,
|
| 3673 |
+
512,
|
| 3674 |
+
512,
|
| 3675 |
+
512,
|
| 3676 |
+
512,
|
| 3677 |
+
512,
|
| 3678 |
+
512,
|
| 3679 |
+
512,
|
| 3680 |
+
512,
|
| 3681 |
+
512,
|
| 3682 |
+
512,
|
| 3683 |
+
512,
|
| 3684 |
+
512,
|
| 3685 |
+
512,
|
| 3686 |
+
512,
|
| 3687 |
+
512,
|
| 3688 |
+
512,
|
| 3689 |
+
512,
|
| 3690 |
+
512,
|
| 3691 |
+
512,
|
| 3692 |
+
512,
|
| 3693 |
+
512,
|
| 3694 |
+
512,
|
| 3695 |
+
512,
|
| 3696 |
+
512,
|
| 3697 |
+
512,
|
| 3698 |
+
512,
|
| 3699 |
+
512,
|
| 3700 |
+
512,
|
| 3701 |
+
512,
|
| 3702 |
+
512,
|
| 3703 |
+
512,
|
| 3704 |
+
512,
|
| 3705 |
+
512,
|
| 3706 |
+
512,
|
| 3707 |
+
512,
|
| 3708 |
+
512,
|
| 3709 |
+
512,
|
| 3710 |
+
512,
|
| 3711 |
+
512,
|
| 3712 |
+
512,
|
| 3713 |
+
512,
|
| 3714 |
+
512,
|
| 3715 |
+
512,
|
| 3716 |
+
512,
|
| 3717 |
+
512,
|
| 3718 |
+
512,
|
| 3719 |
+
512,
|
| 3720 |
+
512,
|
| 3721 |
+
512,
|
| 3722 |
+
512,
|
| 3723 |
+
512,
|
| 3724 |
+
512,
|
| 3725 |
+
512,
|
| 3726 |
+
512,
|
| 3727 |
+
512,
|
| 3728 |
+
512,
|
| 3729 |
+
512,
|
| 3730 |
+
512,
|
| 3731 |
+
512,
|
| 3732 |
+
512,
|
| 3733 |
+
512,
|
| 3734 |
+
512,
|
| 3735 |
+
512,
|
| 3736 |
+
512,
|
| 3737 |
+
512,
|
| 3738 |
+
512,
|
| 3739 |
+
512,
|
| 3740 |
+
512,
|
| 3741 |
+
512,
|
| 3742 |
+
512,
|
| 3743 |
+
512,
|
| 3744 |
+
512,
|
| 3745 |
+
512,
|
| 3746 |
+
512,
|
| 3747 |
+
512,
|
| 3748 |
+
512,
|
| 3749 |
+
512,
|
| 3750 |
+
512,
|
| 3751 |
+
512,
|
| 3752 |
+
512,
|
| 3753 |
+
512,
|
| 3754 |
+
512,
|
| 3755 |
+
512,
|
| 3756 |
+
512,
|
| 3757 |
+
512,
|
| 3758 |
+
512,
|
| 3759 |
+
512,
|
| 3760 |
+
512,
|
| 3761 |
+
512,
|
| 3762 |
+
512,
|
| 3763 |
+
512,
|
| 3764 |
+
512,
|
| 3765 |
+
512,
|
| 3766 |
+
512,
|
| 3767 |
+
512,
|
| 3768 |
+
512,
|
| 3769 |
+
512,
|
| 3770 |
+
512,
|
| 3771 |
+
512,
|
| 3772 |
+
512,
|
| 3773 |
+
512,
|
| 3774 |
+
512,
|
| 3775 |
+
512,
|
| 3776 |
+
512,
|
| 3777 |
+
512,
|
| 3778 |
+
512,
|
| 3779 |
+
512,
|
| 3780 |
+
512,
|
| 3781 |
+
512,
|
| 3782 |
+
512,
|
| 3783 |
+
512,
|
| 3784 |
+
512
|
| 3785 |
+
],
|
| 3786 |
+
[
|
| 3787 |
+
512,
|
| 3788 |
+
512,
|
| 3789 |
+
512,
|
| 3790 |
+
512,
|
| 3791 |
+
512,
|
| 3792 |
+
512,
|
| 3793 |
+
512,
|
| 3794 |
+
512,
|
| 3795 |
+
512,
|
| 3796 |
+
512,
|
| 3797 |
+
512,
|
| 3798 |
+
512,
|
| 3799 |
+
512,
|
| 3800 |
+
512,
|
| 3801 |
+
512,
|
| 3802 |
+
512,
|
| 3803 |
+
512,
|
| 3804 |
+
512,
|
| 3805 |
+
512,
|
| 3806 |
+
512,
|
| 3807 |
+
512,
|
| 3808 |
+
512,
|
| 3809 |
+
512,
|
| 3810 |
+
512,
|
| 3811 |
+
512,
|
| 3812 |
+
512,
|
| 3813 |
+
512,
|
| 3814 |
+
512,
|
| 3815 |
+
512,
|
| 3816 |
+
512,
|
| 3817 |
+
512,
|
| 3818 |
+
512,
|
| 3819 |
+
512,
|
| 3820 |
+
512,
|
| 3821 |
+
512,
|
| 3822 |
+
512,
|
| 3823 |
+
512,
|
| 3824 |
+
512,
|
| 3825 |
+
512,
|
| 3826 |
+
512,
|
| 3827 |
+
512,
|
| 3828 |
+
512,
|
| 3829 |
+
512,
|
| 3830 |
+
512,
|
| 3831 |
+
512,
|
| 3832 |
+
512,
|
| 3833 |
+
512,
|
| 3834 |
+
512,
|
| 3835 |
+
512,
|
| 3836 |
+
512,
|
| 3837 |
+
512,
|
| 3838 |
+
512,
|
| 3839 |
+
512,
|
| 3840 |
+
512,
|
| 3841 |
+
512,
|
| 3842 |
+
512,
|
| 3843 |
+
512,
|
| 3844 |
+
512,
|
| 3845 |
+
512,
|
| 3846 |
+
512,
|
| 3847 |
+
512,
|
| 3848 |
+
512,
|
| 3849 |
+
512,
|
| 3850 |
+
512,
|
| 3851 |
+
512,
|
| 3852 |
+
512,
|
| 3853 |
+
512,
|
| 3854 |
+
512,
|
| 3855 |
+
512,
|
| 3856 |
+
512,
|
| 3857 |
+
512,
|
| 3858 |
+
512,
|
| 3859 |
+
512,
|
| 3860 |
+
512,
|
| 3861 |
+
512,
|
| 3862 |
+
512,
|
| 3863 |
+
512,
|
| 3864 |
+
512,
|
| 3865 |
+
512,
|
| 3866 |
+
512,
|
| 3867 |
+
512,
|
| 3868 |
+
512,
|
| 3869 |
+
512,
|
| 3870 |
+
512,
|
| 3871 |
+
512,
|
| 3872 |
+
512,
|
| 3873 |
+
512,
|
| 3874 |
+
512,
|
| 3875 |
+
512,
|
| 3876 |
+
512,
|
| 3877 |
+
512,
|
| 3878 |
+
512,
|
| 3879 |
+
512,
|
| 3880 |
+
512,
|
| 3881 |
+
512,
|
| 3882 |
+
512,
|
| 3883 |
+
512,
|
| 3884 |
+
512,
|
| 3885 |
+
512,
|
| 3886 |
+
512,
|
| 3887 |
+
512,
|
| 3888 |
+
512,
|
| 3889 |
+
512,
|
| 3890 |
+
512,
|
| 3891 |
+
512,
|
| 3892 |
+
512,
|
| 3893 |
+
512,
|
| 3894 |
+
512,
|
| 3895 |
+
512,
|
| 3896 |
+
512,
|
| 3897 |
+
512,
|
| 3898 |
+
512,
|
| 3899 |
+
512,
|
| 3900 |
+
512,
|
| 3901 |
+
512,
|
| 3902 |
+
512,
|
| 3903 |
+
512,
|
| 3904 |
+
512,
|
| 3905 |
+
512,
|
| 3906 |
+
512,
|
| 3907 |
+
512,
|
| 3908 |
+
512,
|
| 3909 |
+
512,
|
| 3910 |
+
512,
|
| 3911 |
+
512,
|
| 3912 |
+
512,
|
| 3913 |
+
512,
|
| 3914 |
+
512
|
| 3915 |
+
],
|
| 3916 |
+
[
|
| 3917 |
+
512,
|
| 3918 |
+
512,
|
| 3919 |
+
512,
|
| 3920 |
+
512,
|
| 3921 |
+
512,
|
| 3922 |
+
512,
|
| 3923 |
+
512,
|
| 3924 |
+
512,
|
| 3925 |
+
512,
|
| 3926 |
+
512,
|
| 3927 |
+
512,
|
| 3928 |
+
512,
|
| 3929 |
+
512,
|
| 3930 |
+
512,
|
| 3931 |
+
512,
|
| 3932 |
+
512,
|
| 3933 |
+
512,
|
| 3934 |
+
512,
|
| 3935 |
+
512,
|
| 3936 |
+
512,
|
| 3937 |
+
512,
|
| 3938 |
+
512,
|
| 3939 |
+
512,
|
| 3940 |
+
512,
|
| 3941 |
+
512,
|
| 3942 |
+
512,
|
| 3943 |
+
512,
|
| 3944 |
+
512,
|
| 3945 |
+
512,
|
| 3946 |
+
512,
|
| 3947 |
+
512,
|
| 3948 |
+
512,
|
| 3949 |
+
512,
|
| 3950 |
+
512,
|
| 3951 |
+
512,
|
| 3952 |
+
512,
|
| 3953 |
+
512,
|
| 3954 |
+
512,
|
| 3955 |
+
512,
|
| 3956 |
+
512,
|
| 3957 |
+
512,
|
| 3958 |
+
512,
|
| 3959 |
+
512,
|
| 3960 |
+
512,
|
| 3961 |
+
512,
|
| 3962 |
+
512,
|
| 3963 |
+
512,
|
| 3964 |
+
512,
|
| 3965 |
+
512,
|
| 3966 |
+
512,
|
| 3967 |
+
512,
|
| 3968 |
+
512,
|
| 3969 |
+
512,
|
| 3970 |
+
512,
|
| 3971 |
+
512,
|
| 3972 |
+
512,
|
| 3973 |
+
512,
|
| 3974 |
+
512,
|
| 3975 |
+
512,
|
| 3976 |
+
512,
|
| 3977 |
+
512,
|
| 3978 |
+
512,
|
| 3979 |
+
512,
|
| 3980 |
+
512,
|
| 3981 |
+
512,
|
| 3982 |
+
512,
|
| 3983 |
+
512,
|
| 3984 |
+
512,
|
| 3985 |
+
512,
|
| 3986 |
+
512,
|
| 3987 |
+
512,
|
| 3988 |
+
512,
|
| 3989 |
+
512,
|
| 3990 |
+
512,
|
| 3991 |
+
512,
|
| 3992 |
+
512,
|
| 3993 |
+
512,
|
| 3994 |
+
512,
|
| 3995 |
+
512,
|
| 3996 |
+
512,
|
| 3997 |
+
512,
|
| 3998 |
+
512,
|
| 3999 |
+
512,
|
| 4000 |
+
512,
|
| 4001 |
+
512,
|
| 4002 |
+
512,
|
| 4003 |
+
512,
|
| 4004 |
+
512,
|
| 4005 |
+
512,
|
| 4006 |
+
512,
|
| 4007 |
+
512,
|
| 4008 |
+
512,
|
| 4009 |
+
512,
|
| 4010 |
+
512,
|
| 4011 |
+
512,
|
| 4012 |
+
512,
|
| 4013 |
+
512,
|
| 4014 |
+
512,
|
| 4015 |
+
512,
|
| 4016 |
+
512,
|
| 4017 |
+
512,
|
| 4018 |
+
512,
|
| 4019 |
+
512,
|
| 4020 |
+
512,
|
| 4021 |
+
512,
|
| 4022 |
+
512,
|
| 4023 |
+
512,
|
| 4024 |
+
512,
|
| 4025 |
+
512,
|
| 4026 |
+
512,
|
| 4027 |
+
512,
|
| 4028 |
+
512,
|
| 4029 |
+
512,
|
| 4030 |
+
512,
|
| 4031 |
+
512,
|
| 4032 |
+
512,
|
| 4033 |
+
512,
|
| 4034 |
+
512,
|
| 4035 |
+
512,
|
| 4036 |
+
512,
|
| 4037 |
+
512,
|
| 4038 |
+
512,
|
| 4039 |
+
512,
|
| 4040 |
+
512,
|
| 4041 |
+
512,
|
| 4042 |
+
512,
|
| 4043 |
+
512,
|
| 4044 |
+
512
|
| 4045 |
+
],
|
| 4046 |
+
[
|
| 4047 |
+
512,
|
| 4048 |
+
512,
|
| 4049 |
+
512,
|
| 4050 |
+
512,
|
| 4051 |
+
512,
|
| 4052 |
+
512,
|
| 4053 |
+
512,
|
| 4054 |
+
512,
|
| 4055 |
+
512,
|
| 4056 |
+
512,
|
| 4057 |
+
512,
|
| 4058 |
+
512,
|
| 4059 |
+
512,
|
| 4060 |
+
512,
|
| 4061 |
+
512,
|
| 4062 |
+
512,
|
| 4063 |
+
512,
|
| 4064 |
+
512,
|
| 4065 |
+
512,
|
| 4066 |
+
512,
|
| 4067 |
+
512,
|
| 4068 |
+
512,
|
| 4069 |
+
512,
|
| 4070 |
+
512,
|
| 4071 |
+
512,
|
| 4072 |
+
512,
|
| 4073 |
+
512,
|
| 4074 |
+
512,
|
| 4075 |
+
512,
|
| 4076 |
+
512,
|
| 4077 |
+
512,
|
| 4078 |
+
512,
|
| 4079 |
+
512,
|
| 4080 |
+
512,
|
| 4081 |
+
512,
|
| 4082 |
+
512,
|
| 4083 |
+
512,
|
| 4084 |
+
512,
|
| 4085 |
+
512,
|
| 4086 |
+
512,
|
| 4087 |
+
512,
|
| 4088 |
+
512,
|
| 4089 |
+
512,
|
| 4090 |
+
512,
|
| 4091 |
+
512,
|
| 4092 |
+
512,
|
| 4093 |
+
512,
|
| 4094 |
+
512,
|
| 4095 |
+
512,
|
| 4096 |
+
512,
|
| 4097 |
+
512,
|
| 4098 |
+
512,
|
| 4099 |
+
512,
|
| 4100 |
+
512,
|
| 4101 |
+
512,
|
| 4102 |
+
512,
|
| 4103 |
+
512,
|
| 4104 |
+
512,
|
| 4105 |
+
512,
|
| 4106 |
+
512,
|
| 4107 |
+
512,
|
| 4108 |
+
512,
|
| 4109 |
+
512,
|
| 4110 |
+
512,
|
| 4111 |
+
512,
|
| 4112 |
+
512,
|
| 4113 |
+
512,
|
| 4114 |
+
512,
|
| 4115 |
+
512,
|
| 4116 |
+
512,
|
| 4117 |
+
512,
|
| 4118 |
+
512,
|
| 4119 |
+
512,
|
| 4120 |
+
512,
|
| 4121 |
+
512,
|
| 4122 |
+
512,
|
| 4123 |
+
512,
|
| 4124 |
+
512,
|
| 4125 |
+
512,
|
| 4126 |
+
512,
|
| 4127 |
+
512,
|
| 4128 |
+
512,
|
| 4129 |
+
512,
|
| 4130 |
+
512,
|
| 4131 |
+
512,
|
| 4132 |
+
512,
|
| 4133 |
+
512,
|
| 4134 |
+
512,
|
| 4135 |
+
512,
|
| 4136 |
+
512,
|
| 4137 |
+
512,
|
| 4138 |
+
512,
|
| 4139 |
+
512,
|
| 4140 |
+
512,
|
| 4141 |
+
512,
|
| 4142 |
+
512,
|
| 4143 |
+
512,
|
| 4144 |
+
512,
|
| 4145 |
+
512,
|
| 4146 |
+
512,
|
| 4147 |
+
512,
|
| 4148 |
+
512,
|
| 4149 |
+
512,
|
| 4150 |
+
512,
|
| 4151 |
+
512,
|
| 4152 |
+
512,
|
| 4153 |
+
512,
|
| 4154 |
+
512,
|
| 4155 |
+
512,
|
| 4156 |
+
512,
|
| 4157 |
+
512,
|
| 4158 |
+
512,
|
| 4159 |
+
512,
|
| 4160 |
+
512,
|
| 4161 |
+
512,
|
| 4162 |
+
512,
|
| 4163 |
+
512,
|
| 4164 |
+
512,
|
| 4165 |
+
512,
|
| 4166 |
+
512,
|
| 4167 |
+
512,
|
| 4168 |
+
512,
|
| 4169 |
+
512,
|
| 4170 |
+
512,
|
| 4171 |
+
512,
|
| 4172 |
+
512,
|
| 4173 |
+
512,
|
| 4174 |
+
512
|
| 4175 |
+
],
|
| 4176 |
+
[
|
| 4177 |
+
512,
|
| 4178 |
+
512,
|
| 4179 |
+
512,
|
| 4180 |
+
512,
|
| 4181 |
+
512,
|
| 4182 |
+
512,
|
| 4183 |
+
512,
|
| 4184 |
+
512,
|
| 4185 |
+
512,
|
| 4186 |
+
512,
|
| 4187 |
+
512,
|
| 4188 |
+
512,
|
| 4189 |
+
512,
|
| 4190 |
+
512,
|
| 4191 |
+
512,
|
| 4192 |
+
512,
|
| 4193 |
+
512,
|
| 4194 |
+
512,
|
| 4195 |
+
512,
|
| 4196 |
+
512,
|
| 4197 |
+
512,
|
| 4198 |
+
512,
|
| 4199 |
+
512,
|
| 4200 |
+
512,
|
| 4201 |
+
512,
|
| 4202 |
+
512,
|
| 4203 |
+
512,
|
| 4204 |
+
512,
|
| 4205 |
+
512,
|
| 4206 |
+
512,
|
| 4207 |
+
512,
|
| 4208 |
+
512,
|
| 4209 |
+
512,
|
| 4210 |
+
512,
|
| 4211 |
+
512,
|
| 4212 |
+
512,
|
| 4213 |
+
512,
|
| 4214 |
+
512,
|
| 4215 |
+
512,
|
| 4216 |
+
512,
|
| 4217 |
+
512,
|
| 4218 |
+
512,
|
| 4219 |
+
512,
|
| 4220 |
+
512,
|
| 4221 |
+
512,
|
| 4222 |
+
512,
|
| 4223 |
+
512,
|
| 4224 |
+
512,
|
| 4225 |
+
512,
|
| 4226 |
+
512,
|
| 4227 |
+
512,
|
| 4228 |
+
512,
|
| 4229 |
+
512,
|
| 4230 |
+
512,
|
| 4231 |
+
512,
|
| 4232 |
+
512,
|
| 4233 |
+
512,
|
| 4234 |
+
512,
|
| 4235 |
+
512,
|
| 4236 |
+
512,
|
| 4237 |
+
512,
|
| 4238 |
+
512,
|
| 4239 |
+
512,
|
| 4240 |
+
512,
|
| 4241 |
+
512,
|
| 4242 |
+
512,
|
| 4243 |
+
512,
|
| 4244 |
+
512,
|
| 4245 |
+
512,
|
| 4246 |
+
512,
|
| 4247 |
+
512,
|
| 4248 |
+
512,
|
| 4249 |
+
512,
|
| 4250 |
+
512,
|
| 4251 |
+
512,
|
| 4252 |
+
512,
|
| 4253 |
+
512,
|
| 4254 |
+
512,
|
| 4255 |
+
512,
|
| 4256 |
+
512,
|
| 4257 |
+
512,
|
| 4258 |
+
512,
|
| 4259 |
+
512,
|
| 4260 |
+
512,
|
| 4261 |
+
512,
|
| 4262 |
+
512,
|
| 4263 |
+
512,
|
| 4264 |
+
512,
|
| 4265 |
+
512,
|
| 4266 |
+
512,
|
| 4267 |
+
512,
|
| 4268 |
+
512,
|
| 4269 |
+
512,
|
| 4270 |
+
512,
|
| 4271 |
+
512,
|
| 4272 |
+
512,
|
| 4273 |
+
512,
|
| 4274 |
+
512,
|
| 4275 |
+
512,
|
| 4276 |
+
512,
|
| 4277 |
+
512,
|
| 4278 |
+
512,
|
| 4279 |
+
512,
|
| 4280 |
+
512,
|
| 4281 |
+
512,
|
| 4282 |
+
512,
|
| 4283 |
+
512,
|
| 4284 |
+
512,
|
| 4285 |
+
512,
|
| 4286 |
+
512,
|
| 4287 |
+
512,
|
| 4288 |
+
512,
|
| 4289 |
+
512,
|
| 4290 |
+
512,
|
| 4291 |
+
512,
|
| 4292 |
+
512,
|
| 4293 |
+
512,
|
| 4294 |
+
512,
|
| 4295 |
+
512,
|
| 4296 |
+
512,
|
| 4297 |
+
512,
|
| 4298 |
+
512,
|
| 4299 |
+
512,
|
| 4300 |
+
512,
|
| 4301 |
+
512,
|
| 4302 |
+
512,
|
| 4303 |
+
512,
|
| 4304 |
+
512
|
| 4305 |
+
],
|
| 4306 |
+
[
|
| 4307 |
+
512,
|
| 4308 |
+
512,
|
| 4309 |
+
512,
|
| 4310 |
+
512,
|
| 4311 |
+
512,
|
| 4312 |
+
512,
|
| 4313 |
+
512,
|
| 4314 |
+
512,
|
| 4315 |
+
512,
|
| 4316 |
+
512,
|
| 4317 |
+
512,
|
| 4318 |
+
512,
|
| 4319 |
+
512,
|
| 4320 |
+
512,
|
| 4321 |
+
512,
|
| 4322 |
+
512,
|
| 4323 |
+
512,
|
| 4324 |
+
512,
|
| 4325 |
+
512,
|
| 4326 |
+
512,
|
| 4327 |
+
512,
|
| 4328 |
+
512,
|
| 4329 |
+
512,
|
| 4330 |
+
512,
|
| 4331 |
+
512,
|
| 4332 |
+
512,
|
| 4333 |
+
512,
|
| 4334 |
+
512,
|
| 4335 |
+
512,
|
| 4336 |
+
512,
|
| 4337 |
+
512,
|
| 4338 |
+
512,
|
| 4339 |
+
512,
|
| 4340 |
+
512,
|
| 4341 |
+
512,
|
| 4342 |
+
512,
|
| 4343 |
+
512,
|
| 4344 |
+
512,
|
| 4345 |
+
512,
|
| 4346 |
+
512,
|
| 4347 |
+
512,
|
| 4348 |
+
512,
|
| 4349 |
+
512,
|
| 4350 |
+
512,
|
| 4351 |
+
512,
|
| 4352 |
+
512,
|
| 4353 |
+
512,
|
| 4354 |
+
512,
|
| 4355 |
+
512,
|
| 4356 |
+
512,
|
| 4357 |
+
512,
|
| 4358 |
+
512,
|
| 4359 |
+
512,
|
| 4360 |
+
512,
|
| 4361 |
+
512,
|
| 4362 |
+
512,
|
| 4363 |
+
512,
|
| 4364 |
+
512,
|
| 4365 |
+
512,
|
| 4366 |
+
512,
|
| 4367 |
+
512,
|
| 4368 |
+
512,
|
| 4369 |
+
512,
|
| 4370 |
+
512,
|
| 4371 |
+
512,
|
| 4372 |
+
512,
|
| 4373 |
+
512,
|
| 4374 |
+
512,
|
| 4375 |
+
512,
|
| 4376 |
+
512,
|
| 4377 |
+
512,
|
| 4378 |
+
512,
|
| 4379 |
+
512,
|
| 4380 |
+
512,
|
| 4381 |
+
512,
|
| 4382 |
+
512,
|
| 4383 |
+
512,
|
| 4384 |
+
512,
|
| 4385 |
+
512,
|
| 4386 |
+
512,
|
| 4387 |
+
512,
|
| 4388 |
+
512,
|
| 4389 |
+
512,
|
| 4390 |
+
512,
|
| 4391 |
+
512,
|
| 4392 |
+
512,
|
| 4393 |
+
512,
|
| 4394 |
+
512,
|
| 4395 |
+
512,
|
| 4396 |
+
512,
|
| 4397 |
+
512,
|
| 4398 |
+
512,
|
| 4399 |
+
512,
|
| 4400 |
+
512,
|
| 4401 |
+
512,
|
| 4402 |
+
512,
|
| 4403 |
+
512,
|
| 4404 |
+
512,
|
| 4405 |
+
512,
|
| 4406 |
+
512,
|
| 4407 |
+
512,
|
| 4408 |
+
512,
|
| 4409 |
+
512,
|
| 4410 |
+
512,
|
| 4411 |
+
512,
|
| 4412 |
+
512,
|
| 4413 |
+
512,
|
| 4414 |
+
512,
|
| 4415 |
+
512,
|
| 4416 |
+
512,
|
| 4417 |
+
512,
|
| 4418 |
+
512,
|
| 4419 |
+
512,
|
| 4420 |
+
512,
|
| 4421 |
+
512,
|
| 4422 |
+
512,
|
| 4423 |
+
512,
|
| 4424 |
+
512,
|
| 4425 |
+
512,
|
| 4426 |
+
512,
|
| 4427 |
+
512,
|
| 4428 |
+
512,
|
| 4429 |
+
512,
|
| 4430 |
+
512,
|
| 4431 |
+
512,
|
| 4432 |
+
512,
|
| 4433 |
+
512,
|
| 4434 |
+
512
|
| 4435 |
+
],
|
| 4436 |
+
[
|
| 4437 |
+
512,
|
| 4438 |
+
512,
|
| 4439 |
+
512,
|
| 4440 |
+
512,
|
| 4441 |
+
512,
|
| 4442 |
+
512,
|
| 4443 |
+
512,
|
| 4444 |
+
512,
|
| 4445 |
+
512,
|
| 4446 |
+
512,
|
| 4447 |
+
512,
|
| 4448 |
+
512,
|
| 4449 |
+
512,
|
| 4450 |
+
512,
|
| 4451 |
+
512,
|
| 4452 |
+
512,
|
| 4453 |
+
512,
|
| 4454 |
+
512,
|
| 4455 |
+
512,
|
| 4456 |
+
512,
|
| 4457 |
+
512,
|
| 4458 |
+
512,
|
| 4459 |
+
512,
|
| 4460 |
+
512,
|
| 4461 |
+
512,
|
| 4462 |
+
512,
|
| 4463 |
+
512,
|
| 4464 |
+
512,
|
| 4465 |
+
512,
|
| 4466 |
+
512,
|
| 4467 |
+
512,
|
| 4468 |
+
512,
|
| 4469 |
+
512,
|
| 4470 |
+
512,
|
| 4471 |
+
512,
|
| 4472 |
+
512,
|
| 4473 |
+
512,
|
| 4474 |
+
512,
|
| 4475 |
+
512,
|
| 4476 |
+
512,
|
| 4477 |
+
512,
|
| 4478 |
+
512,
|
| 4479 |
+
512,
|
| 4480 |
+
512,
|
| 4481 |
+
512,
|
| 4482 |
+
512,
|
| 4483 |
+
512,
|
| 4484 |
+
512,
|
| 4485 |
+
512,
|
| 4486 |
+
512,
|
| 4487 |
+
512,
|
| 4488 |
+
512,
|
| 4489 |
+
512,
|
| 4490 |
+
512,
|
| 4491 |
+
512,
|
| 4492 |
+
512,
|
| 4493 |
+
512,
|
| 4494 |
+
512,
|
| 4495 |
+
512,
|
| 4496 |
+
512,
|
| 4497 |
+
512,
|
| 4498 |
+
512,
|
| 4499 |
+
512,
|
| 4500 |
+
512,
|
| 4501 |
+
512,
|
| 4502 |
+
512,
|
| 4503 |
+
512,
|
| 4504 |
+
512,
|
| 4505 |
+
512,
|
| 4506 |
+
512,
|
| 4507 |
+
512,
|
| 4508 |
+
512,
|
| 4509 |
+
512,
|
| 4510 |
+
512,
|
| 4511 |
+
512,
|
| 4512 |
+
512,
|
| 4513 |
+
512,
|
| 4514 |
+
512,
|
| 4515 |
+
512,
|
| 4516 |
+
512,
|
| 4517 |
+
512,
|
| 4518 |
+
512,
|
| 4519 |
+
512,
|
| 4520 |
+
512,
|
| 4521 |
+
512,
|
| 4522 |
+
512,
|
| 4523 |
+
512,
|
| 4524 |
+
512,
|
| 4525 |
+
512,
|
| 4526 |
+
512,
|
| 4527 |
+
512,
|
| 4528 |
+
512,
|
| 4529 |
+
512,
|
| 4530 |
+
512,
|
| 4531 |
+
512,
|
| 4532 |
+
512,
|
| 4533 |
+
512,
|
| 4534 |
+
512,
|
| 4535 |
+
512,
|
| 4536 |
+
512,
|
| 4537 |
+
512,
|
| 4538 |
+
512,
|
| 4539 |
+
512,
|
| 4540 |
+
512,
|
| 4541 |
+
512,
|
| 4542 |
+
512,
|
| 4543 |
+
512,
|
| 4544 |
+
512,
|
| 4545 |
+
512,
|
| 4546 |
+
512,
|
| 4547 |
+
512,
|
| 4548 |
+
512,
|
| 4549 |
+
512,
|
| 4550 |
+
512,
|
| 4551 |
+
512,
|
| 4552 |
+
512,
|
| 4553 |
+
512,
|
| 4554 |
+
512,
|
| 4555 |
+
512,
|
| 4556 |
+
512,
|
| 4557 |
+
512,
|
| 4558 |
+
512,
|
| 4559 |
+
512,
|
| 4560 |
+
512,
|
| 4561 |
+
512,
|
| 4562 |
+
512,
|
| 4563 |
+
512,
|
| 4564 |
+
512
|
| 4565 |
+
],
|
| 4566 |
+
[
|
| 4567 |
+
512,
|
| 4568 |
+
512,
|
| 4569 |
+
512,
|
| 4570 |
+
512,
|
| 4571 |
+
512,
|
| 4572 |
+
512,
|
| 4573 |
+
512,
|
| 4574 |
+
512,
|
| 4575 |
+
512,
|
| 4576 |
+
512,
|
| 4577 |
+
512,
|
| 4578 |
+
512,
|
| 4579 |
+
512,
|
| 4580 |
+
512,
|
| 4581 |
+
512,
|
| 4582 |
+
512,
|
| 4583 |
+
512,
|
| 4584 |
+
512,
|
| 4585 |
+
512,
|
| 4586 |
+
512,
|
| 4587 |
+
512,
|
| 4588 |
+
512,
|
| 4589 |
+
512,
|
| 4590 |
+
512,
|
| 4591 |
+
512,
|
| 4592 |
+
512,
|
| 4593 |
+
512,
|
| 4594 |
+
512,
|
| 4595 |
+
512,
|
| 4596 |
+
512,
|
| 4597 |
+
512,
|
| 4598 |
+
512,
|
| 4599 |
+
512,
|
| 4600 |
+
512,
|
| 4601 |
+
512,
|
| 4602 |
+
512,
|
| 4603 |
+
512,
|
| 4604 |
+
512,
|
| 4605 |
+
512,
|
| 4606 |
+
512,
|
| 4607 |
+
512,
|
| 4608 |
+
512,
|
| 4609 |
+
512,
|
| 4610 |
+
512,
|
| 4611 |
+
512,
|
| 4612 |
+
512,
|
| 4613 |
+
512,
|
| 4614 |
+
512,
|
| 4615 |
+
512,
|
| 4616 |
+
512,
|
| 4617 |
+
512,
|
| 4618 |
+
512,
|
| 4619 |
+
512,
|
| 4620 |
+
512,
|
| 4621 |
+
512,
|
| 4622 |
+
512,
|
| 4623 |
+
512,
|
| 4624 |
+
512,
|
| 4625 |
+
512,
|
| 4626 |
+
512,
|
| 4627 |
+
512,
|
| 4628 |
+
512,
|
| 4629 |
+
512,
|
| 4630 |
+
512,
|
| 4631 |
+
512,
|
| 4632 |
+
512,
|
| 4633 |
+
512,
|
| 4634 |
+
512,
|
| 4635 |
+
512,
|
| 4636 |
+
512,
|
| 4637 |
+
512,
|
| 4638 |
+
512,
|
| 4639 |
+
512,
|
| 4640 |
+
512,
|
| 4641 |
+
512,
|
| 4642 |
+
512,
|
| 4643 |
+
512,
|
| 4644 |
+
512,
|
| 4645 |
+
512,
|
| 4646 |
+
512,
|
| 4647 |
+
512,
|
| 4648 |
+
512,
|
| 4649 |
+
512,
|
| 4650 |
+
512,
|
| 4651 |
+
512,
|
| 4652 |
+
512,
|
| 4653 |
+
512,
|
| 4654 |
+
512,
|
| 4655 |
+
512,
|
| 4656 |
+
512,
|
| 4657 |
+
512,
|
| 4658 |
+
512,
|
| 4659 |
+
512,
|
| 4660 |
+
512,
|
| 4661 |
+
512,
|
| 4662 |
+
512,
|
| 4663 |
+
512,
|
| 4664 |
+
512,
|
| 4665 |
+
512,
|
| 4666 |
+
512,
|
| 4667 |
+
512,
|
| 4668 |
+
512,
|
| 4669 |
+
512,
|
| 4670 |
+
512,
|
| 4671 |
+
512,
|
| 4672 |
+
512,
|
| 4673 |
+
512,
|
| 4674 |
+
512,
|
| 4675 |
+
512,
|
| 4676 |
+
512,
|
| 4677 |
+
512,
|
| 4678 |
+
512,
|
| 4679 |
+
512,
|
| 4680 |
+
512,
|
| 4681 |
+
512,
|
| 4682 |
+
512,
|
| 4683 |
+
512,
|
| 4684 |
+
512,
|
| 4685 |
+
512,
|
| 4686 |
+
512,
|
| 4687 |
+
512,
|
| 4688 |
+
512,
|
| 4689 |
+
512,
|
| 4690 |
+
512,
|
| 4691 |
+
512,
|
| 4692 |
+
512,
|
| 4693 |
+
512,
|
| 4694 |
+
512
|
| 4695 |
+
],
|
| 4696 |
+
[
|
| 4697 |
+
512,
|
| 4698 |
+
512,
|
| 4699 |
+
512,
|
| 4700 |
+
512,
|
| 4701 |
+
512,
|
| 4702 |
+
512,
|
| 4703 |
+
512,
|
| 4704 |
+
512,
|
| 4705 |
+
512,
|
| 4706 |
+
512,
|
| 4707 |
+
512,
|
| 4708 |
+
512,
|
| 4709 |
+
512,
|
| 4710 |
+
512,
|
| 4711 |
+
512,
|
| 4712 |
+
512,
|
| 4713 |
+
512,
|
| 4714 |
+
512,
|
| 4715 |
+
512,
|
| 4716 |
+
512,
|
| 4717 |
+
512,
|
| 4718 |
+
512,
|
| 4719 |
+
512,
|
| 4720 |
+
512,
|
| 4721 |
+
512,
|
| 4722 |
+
512,
|
| 4723 |
+
512,
|
| 4724 |
+
512,
|
| 4725 |
+
512,
|
| 4726 |
+
512,
|
| 4727 |
+
512,
|
| 4728 |
+
512,
|
| 4729 |
+
512,
|
| 4730 |
+
512,
|
| 4731 |
+
512,
|
| 4732 |
+
512,
|
| 4733 |
+
512,
|
| 4734 |
+
512,
|
| 4735 |
+
512,
|
| 4736 |
+
512,
|
| 4737 |
+
512,
|
| 4738 |
+
512,
|
| 4739 |
+
512,
|
| 4740 |
+
512,
|
| 4741 |
+
512,
|
| 4742 |
+
512,
|
| 4743 |
+
512,
|
| 4744 |
+
512,
|
| 4745 |
+
512,
|
| 4746 |
+
512,
|
| 4747 |
+
512,
|
| 4748 |
+
512,
|
| 4749 |
+
512,
|
| 4750 |
+
512,
|
| 4751 |
+
512,
|
| 4752 |
+
512,
|
| 4753 |
+
512,
|
| 4754 |
+
512,
|
| 4755 |
+
512,
|
| 4756 |
+
512,
|
| 4757 |
+
512,
|
| 4758 |
+
512,
|
| 4759 |
+
512,
|
| 4760 |
+
512,
|
| 4761 |
+
512,
|
| 4762 |
+
512,
|
| 4763 |
+
512,
|
| 4764 |
+
512,
|
| 4765 |
+
512,
|
| 4766 |
+
512,
|
| 4767 |
+
512,
|
| 4768 |
+
512,
|
| 4769 |
+
512,
|
| 4770 |
+
512,
|
| 4771 |
+
512,
|
| 4772 |
+
512,
|
| 4773 |
+
512,
|
| 4774 |
+
512,
|
| 4775 |
+
512,
|
| 4776 |
+
512,
|
| 4777 |
+
512,
|
| 4778 |
+
512,
|
| 4779 |
+
512,
|
| 4780 |
+
512,
|
| 4781 |
+
512,
|
| 4782 |
+
512,
|
| 4783 |
+
512,
|
| 4784 |
+
512,
|
| 4785 |
+
512,
|
| 4786 |
+
512,
|
| 4787 |
+
512,
|
| 4788 |
+
512,
|
| 4789 |
+
512,
|
| 4790 |
+
512,
|
| 4791 |
+
512,
|
| 4792 |
+
512,
|
| 4793 |
+
512,
|
| 4794 |
+
512,
|
| 4795 |
+
512,
|
| 4796 |
+
512,
|
| 4797 |
+
512,
|
| 4798 |
+
512,
|
| 4799 |
+
512,
|
| 4800 |
+
512,
|
| 4801 |
+
512,
|
| 4802 |
+
512,
|
| 4803 |
+
512,
|
| 4804 |
+
512,
|
| 4805 |
+
512,
|
| 4806 |
+
512,
|
| 4807 |
+
512,
|
| 4808 |
+
512,
|
| 4809 |
+
512,
|
| 4810 |
+
512,
|
| 4811 |
+
512,
|
| 4812 |
+
512,
|
| 4813 |
+
512,
|
| 4814 |
+
512,
|
| 4815 |
+
512,
|
| 4816 |
+
512,
|
| 4817 |
+
512,
|
| 4818 |
+
512,
|
| 4819 |
+
512,
|
| 4820 |
+
512,
|
| 4821 |
+
512,
|
| 4822 |
+
512,
|
| 4823 |
+
512,
|
| 4824 |
+
512
|
| 4825 |
+
],
|
| 4826 |
+
[
|
| 4827 |
+
512,
|
| 4828 |
+
512,
|
| 4829 |
+
512,
|
| 4830 |
+
512,
|
| 4831 |
+
512,
|
| 4832 |
+
512,
|
| 4833 |
+
512,
|
| 4834 |
+
512,
|
| 4835 |
+
512,
|
| 4836 |
+
512,
|
| 4837 |
+
512,
|
| 4838 |
+
512,
|
| 4839 |
+
512,
|
| 4840 |
+
512,
|
| 4841 |
+
512,
|
| 4842 |
+
512,
|
| 4843 |
+
512,
|
| 4844 |
+
512,
|
| 4845 |
+
512,
|
| 4846 |
+
512,
|
| 4847 |
+
512,
|
| 4848 |
+
512,
|
| 4849 |
+
512,
|
| 4850 |
+
512,
|
| 4851 |
+
512,
|
| 4852 |
+
512,
|
| 4853 |
+
512,
|
| 4854 |
+
512,
|
| 4855 |
+
512,
|
| 4856 |
+
512,
|
| 4857 |
+
512,
|
| 4858 |
+
512,
|
| 4859 |
+
512,
|
| 4860 |
+
512,
|
| 4861 |
+
512,
|
| 4862 |
+
512,
|
| 4863 |
+
512,
|
| 4864 |
+
512,
|
| 4865 |
+
512,
|
| 4866 |
+
512,
|
| 4867 |
+
512,
|
| 4868 |
+
512,
|
| 4869 |
+
512,
|
| 4870 |
+
512,
|
| 4871 |
+
512,
|
| 4872 |
+
512,
|
| 4873 |
+
512,
|
| 4874 |
+
512,
|
| 4875 |
+
512,
|
| 4876 |
+
512,
|
| 4877 |
+
512,
|
| 4878 |
+
512,
|
| 4879 |
+
512,
|
| 4880 |
+
512,
|
| 4881 |
+
512,
|
| 4882 |
+
512,
|
| 4883 |
+
512,
|
| 4884 |
+
512,
|
| 4885 |
+
512,
|
| 4886 |
+
512,
|
| 4887 |
+
512,
|
| 4888 |
+
512,
|
| 4889 |
+
512,
|
| 4890 |
+
512,
|
| 4891 |
+
512,
|
| 4892 |
+
512,
|
| 4893 |
+
512,
|
| 4894 |
+
512,
|
| 4895 |
+
512,
|
| 4896 |
+
512,
|
| 4897 |
+
512,
|
| 4898 |
+
512,
|
| 4899 |
+
512,
|
| 4900 |
+
512,
|
| 4901 |
+
512,
|
| 4902 |
+
512,
|
| 4903 |
+
512,
|
| 4904 |
+
512,
|
| 4905 |
+
512,
|
| 4906 |
+
512,
|
| 4907 |
+
512,
|
| 4908 |
+
512,
|
| 4909 |
+
512,
|
| 4910 |
+
512,
|
| 4911 |
+
512,
|
| 4912 |
+
512,
|
| 4913 |
+
512,
|
| 4914 |
+
512,
|
| 4915 |
+
512,
|
| 4916 |
+
512,
|
| 4917 |
+
512,
|
| 4918 |
+
512,
|
| 4919 |
+
512,
|
| 4920 |
+
512,
|
| 4921 |
+
512,
|
| 4922 |
+
512,
|
| 4923 |
+
512,
|
| 4924 |
+
512,
|
| 4925 |
+
512,
|
| 4926 |
+
512,
|
| 4927 |
+
512,
|
| 4928 |
+
512,
|
| 4929 |
+
512,
|
| 4930 |
+
512,
|
| 4931 |
+
512,
|
| 4932 |
+
512,
|
| 4933 |
+
512,
|
| 4934 |
+
512,
|
| 4935 |
+
512,
|
| 4936 |
+
512,
|
| 4937 |
+
512,
|
| 4938 |
+
512,
|
| 4939 |
+
512,
|
| 4940 |
+
512,
|
| 4941 |
+
512,
|
| 4942 |
+
512,
|
| 4943 |
+
512,
|
| 4944 |
+
512,
|
| 4945 |
+
512,
|
| 4946 |
+
512,
|
| 4947 |
+
512,
|
| 4948 |
+
512,
|
| 4949 |
+
512,
|
| 4950 |
+
512,
|
| 4951 |
+
512,
|
| 4952 |
+
512,
|
| 4953 |
+
512,
|
| 4954 |
+
512
|
| 4955 |
+
],
|
| 4956 |
+
[
|
| 4957 |
+
512,
|
| 4958 |
+
512,
|
| 4959 |
+
512,
|
| 4960 |
+
512,
|
| 4961 |
+
512,
|
| 4962 |
+
512,
|
| 4963 |
+
512,
|
| 4964 |
+
512,
|
| 4965 |
+
512,
|
| 4966 |
+
512,
|
| 4967 |
+
512,
|
| 4968 |
+
512,
|
| 4969 |
+
512,
|
| 4970 |
+
512,
|
| 4971 |
+
512,
|
| 4972 |
+
512,
|
| 4973 |
+
512,
|
| 4974 |
+
512,
|
| 4975 |
+
512,
|
| 4976 |
+
512,
|
| 4977 |
+
512,
|
| 4978 |
+
512,
|
| 4979 |
+
512,
|
| 4980 |
+
512,
|
| 4981 |
+
512,
|
| 4982 |
+
512,
|
| 4983 |
+
512,
|
| 4984 |
+
512,
|
| 4985 |
+
512,
|
| 4986 |
+
512,
|
| 4987 |
+
512,
|
| 4988 |
+
512,
|
| 4989 |
+
512,
|
| 4990 |
+
512,
|
| 4991 |
+
512,
|
| 4992 |
+
512,
|
| 4993 |
+
512,
|
| 4994 |
+
512,
|
| 4995 |
+
512,
|
| 4996 |
+
512,
|
| 4997 |
+
512,
|
| 4998 |
+
512,
|
| 4999 |
+
512,
|
| 5000 |
+
512,
|
| 5001 |
+
512,
|
| 5002 |
+
512,
|
| 5003 |
+
512,
|
| 5004 |
+
512,
|
| 5005 |
+
512,
|
| 5006 |
+
512,
|
| 5007 |
+
512,
|
| 5008 |
+
512,
|
| 5009 |
+
512,
|
| 5010 |
+
512,
|
| 5011 |
+
512,
|
| 5012 |
+
512,
|
| 5013 |
+
512,
|
| 5014 |
+
512,
|
| 5015 |
+
512,
|
| 5016 |
+
512,
|
| 5017 |
+
512,
|
| 5018 |
+
512,
|
| 5019 |
+
512,
|
| 5020 |
+
512,
|
| 5021 |
+
512,
|
| 5022 |
+
512,
|
| 5023 |
+
512,
|
| 5024 |
+
512,
|
| 5025 |
+
512,
|
| 5026 |
+
512,
|
| 5027 |
+
512,
|
| 5028 |
+
512,
|
| 5029 |
+
512,
|
| 5030 |
+
512,
|
| 5031 |
+
512,
|
| 5032 |
+
512,
|
| 5033 |
+
512,
|
| 5034 |
+
512,
|
| 5035 |
+
512,
|
| 5036 |
+
512,
|
| 5037 |
+
512,
|
| 5038 |
+
512,
|
| 5039 |
+
512,
|
| 5040 |
+
512,
|
| 5041 |
+
512,
|
| 5042 |
+
512,
|
| 5043 |
+
512,
|
| 5044 |
+
512,
|
| 5045 |
+
512,
|
| 5046 |
+
512,
|
| 5047 |
+
512,
|
| 5048 |
+
512,
|
| 5049 |
+
512,
|
| 5050 |
+
512,
|
| 5051 |
+
512,
|
| 5052 |
+
512,
|
| 5053 |
+
512,
|
| 5054 |
+
512,
|
| 5055 |
+
512,
|
| 5056 |
+
512,
|
| 5057 |
+
512,
|
| 5058 |
+
512,
|
| 5059 |
+
512,
|
| 5060 |
+
512,
|
| 5061 |
+
512,
|
| 5062 |
+
512,
|
| 5063 |
+
512,
|
| 5064 |
+
512,
|
| 5065 |
+
512,
|
| 5066 |
+
512,
|
| 5067 |
+
512,
|
| 5068 |
+
512,
|
| 5069 |
+
512,
|
| 5070 |
+
512,
|
| 5071 |
+
512,
|
| 5072 |
+
512,
|
| 5073 |
+
512,
|
| 5074 |
+
512,
|
| 5075 |
+
512,
|
| 5076 |
+
512,
|
| 5077 |
+
512,
|
| 5078 |
+
512,
|
| 5079 |
+
512,
|
| 5080 |
+
512,
|
| 5081 |
+
512,
|
| 5082 |
+
512,
|
| 5083 |
+
512,
|
| 5084 |
+
512
|
| 5085 |
+
],
|
| 5086 |
+
[
|
| 5087 |
+
512,
|
| 5088 |
+
512,
|
| 5089 |
+
512,
|
| 5090 |
+
512,
|
| 5091 |
+
512,
|
| 5092 |
+
512,
|
| 5093 |
+
512,
|
| 5094 |
+
512,
|
| 5095 |
+
512,
|
| 5096 |
+
512,
|
| 5097 |
+
512,
|
| 5098 |
+
512,
|
| 5099 |
+
512,
|
| 5100 |
+
512,
|
| 5101 |
+
512,
|
| 5102 |
+
512,
|
| 5103 |
+
512,
|
| 5104 |
+
512,
|
| 5105 |
+
512,
|
| 5106 |
+
512,
|
| 5107 |
+
512,
|
| 5108 |
+
512,
|
| 5109 |
+
512,
|
| 5110 |
+
512,
|
| 5111 |
+
512,
|
| 5112 |
+
512,
|
| 5113 |
+
512,
|
| 5114 |
+
512,
|
| 5115 |
+
512,
|
| 5116 |
+
512,
|
| 5117 |
+
512,
|
| 5118 |
+
512,
|
| 5119 |
+
512,
|
| 5120 |
+
512,
|
| 5121 |
+
512,
|
| 5122 |
+
512,
|
| 5123 |
+
512,
|
| 5124 |
+
512,
|
| 5125 |
+
512,
|
| 5126 |
+
512,
|
| 5127 |
+
512,
|
| 5128 |
+
512,
|
| 5129 |
+
512,
|
| 5130 |
+
512,
|
| 5131 |
+
512,
|
| 5132 |
+
512,
|
| 5133 |
+
512,
|
| 5134 |
+
512,
|
| 5135 |
+
512,
|
| 5136 |
+
512,
|
| 5137 |
+
512,
|
| 5138 |
+
512,
|
| 5139 |
+
512,
|
| 5140 |
+
512,
|
| 5141 |
+
512,
|
| 5142 |
+
512,
|
| 5143 |
+
512,
|
| 5144 |
+
512,
|
| 5145 |
+
512,
|
| 5146 |
+
512,
|
| 5147 |
+
512,
|
| 5148 |
+
512,
|
| 5149 |
+
512,
|
| 5150 |
+
512,
|
| 5151 |
+
512,
|
| 5152 |
+
512,
|
| 5153 |
+
512,
|
| 5154 |
+
512,
|
| 5155 |
+
512,
|
| 5156 |
+
512,
|
| 5157 |
+
512,
|
| 5158 |
+
512,
|
| 5159 |
+
512,
|
| 5160 |
+
512,
|
| 5161 |
+
512,
|
| 5162 |
+
512,
|
| 5163 |
+
512,
|
| 5164 |
+
512,
|
| 5165 |
+
512,
|
| 5166 |
+
512,
|
| 5167 |
+
512,
|
| 5168 |
+
512,
|
| 5169 |
+
512,
|
| 5170 |
+
512,
|
| 5171 |
+
512,
|
| 5172 |
+
512,
|
| 5173 |
+
512,
|
| 5174 |
+
512,
|
| 5175 |
+
512,
|
| 5176 |
+
512,
|
| 5177 |
+
512,
|
| 5178 |
+
512,
|
| 5179 |
+
512,
|
| 5180 |
+
512,
|
| 5181 |
+
512,
|
| 5182 |
+
512,
|
| 5183 |
+
512,
|
| 5184 |
+
512,
|
| 5185 |
+
512,
|
| 5186 |
+
512,
|
| 5187 |
+
512,
|
| 5188 |
+
512,
|
| 5189 |
+
512,
|
| 5190 |
+
512,
|
| 5191 |
+
512,
|
| 5192 |
+
512,
|
| 5193 |
+
512,
|
| 5194 |
+
512,
|
| 5195 |
+
512,
|
| 5196 |
+
512,
|
| 5197 |
+
512,
|
| 5198 |
+
512,
|
| 5199 |
+
512,
|
| 5200 |
+
512,
|
| 5201 |
+
512,
|
| 5202 |
+
512,
|
| 5203 |
+
512,
|
| 5204 |
+
512,
|
| 5205 |
+
512,
|
| 5206 |
+
512,
|
| 5207 |
+
512,
|
| 5208 |
+
512,
|
| 5209 |
+
512,
|
| 5210 |
+
512,
|
| 5211 |
+
512,
|
| 5212 |
+
512,
|
| 5213 |
+
512,
|
| 5214 |
+
512
|
| 5215 |
+
]
|
| 5216 |
+
],
|
| 5217 |
+
"full_attention_interval": 4,
|
| 5218 |
+
"glean_metadata": {
|
| 5219 |
+
"keep_fraction": 0.5,
|
| 5220 |
+
"method": "REAP whole-expert prune (reap), uniform per-layer keep",
|
| 5221 |
+
"score": {
|
| 5222 |
+
"alpha": 1,
|
| 5223 |
+
"b": 1.0,
|
| 5224 |
+
"beta": 1
|
| 5225 |
+
},
|
| 5226 |
+
"source_model": "Qwen/Qwen3.6-35B-A3B",
|
| 5227 |
+
"stats_path": "outputs/qwen35_stats1024.pt"
|
| 5228 |
+
},
|
| 5229 |
+
"head_dim": 256,
|
| 5230 |
+
"hidden_act": "silu",
|
| 5231 |
+
"hidden_size": 2048,
|
| 5232 |
+
"initializer_range": 0.02,
|
| 5233 |
+
"layer_types": [
|
| 5234 |
+
"linear_attention",
|
| 5235 |
+
"linear_attention",
|
| 5236 |
+
"linear_attention",
|
| 5237 |
+
"full_attention",
|
| 5238 |
+
"linear_attention",
|
| 5239 |
+
"linear_attention",
|
| 5240 |
+
"linear_attention",
|
| 5241 |
+
"full_attention",
|
| 5242 |
+
"linear_attention",
|
| 5243 |
+
"linear_attention",
|
| 5244 |
+
"linear_attention",
|
| 5245 |
+
"full_attention",
|
| 5246 |
+
"linear_attention",
|
| 5247 |
+
"linear_attention",
|
| 5248 |
+
"linear_attention",
|
| 5249 |
+
"full_attention",
|
| 5250 |
+
"linear_attention",
|
| 5251 |
+
"linear_attention",
|
| 5252 |
+
"linear_attention",
|
| 5253 |
+
"full_attention",
|
| 5254 |
+
"linear_attention",
|
| 5255 |
+
"linear_attention",
|
| 5256 |
+
"linear_attention",
|
| 5257 |
+
"full_attention",
|
| 5258 |
+
"linear_attention",
|
| 5259 |
+
"linear_attention",
|
| 5260 |
+
"linear_attention",
|
| 5261 |
+
"full_attention",
|
| 5262 |
+
"linear_attention",
|
| 5263 |
+
"linear_attention",
|
| 5264 |
+
"linear_attention",
|
| 5265 |
+
"full_attention",
|
| 5266 |
+
"linear_attention",
|
| 5267 |
+
"linear_attention",
|
| 5268 |
+
"linear_attention",
|
| 5269 |
+
"full_attention",
|
| 5270 |
+
"linear_attention",
|
| 5271 |
+
"linear_attention",
|
| 5272 |
+
"linear_attention",
|
| 5273 |
+
"full_attention"
|
| 5274 |
+
],
|
| 5275 |
+
"linear_conv_kernel_dim": 4,
|
| 5276 |
+
"linear_key_head_dim": 128,
|
| 5277 |
+
"linear_num_key_heads": 16,
|
| 5278 |
+
"linear_num_value_heads": 32,
|
| 5279 |
+
"linear_value_head_dim": 128,
|
| 5280 |
+
"mamba_ssm_dtype": "float32",
|
| 5281 |
+
"max_position_embeddings": 262144,
|
| 5282 |
+
"model_type": "pruned_qwen3_5_moe",
|
| 5283 |
+
"moe_intermediate_size": 512,
|
| 5284 |
+
"mtp_num_hidden_layers": 1,
|
| 5285 |
+
"mtp_use_dedicated_embeddings": false,
|
| 5286 |
+
"num_attention_heads": 16,
|
| 5287 |
+
"num_experts": 256,
|
| 5288 |
+
"num_experts_per_tok": 8,
|
| 5289 |
+
"num_hidden_layers": 40,
|
| 5290 |
+
"num_key_value_heads": 2,
|
| 5291 |
+
"output_router_logits": false,
|
| 5292 |
+
"pad_token_id": null,
|
| 5293 |
+
"partial_rotary_factor": 0.25,
|
| 5294 |
+
"rms_norm_eps": 1e-06,
|
| 5295 |
+
"rope_parameters": {
|
| 5296 |
+
"mrope_interleaved": true,
|
| 5297 |
+
"mrope_section": [
|
| 5298 |
+
11,
|
| 5299 |
+
11,
|
| 5300 |
+
10
|
| 5301 |
+
],
|
| 5302 |
+
"partial_rotary_factor": 0.25,
|
| 5303 |
+
"rope_theta": 10000000,
|
| 5304 |
+
"rope_type": "default"
|
| 5305 |
+
},
|
| 5306 |
+
"router_aux_loss_coef": 0.001,
|
| 5307 |
+
"shared_expert_intermediate_size": 512,
|
| 5308 |
+
"tie_word_embeddings": false,
|
| 5309 |
+
"transformers_version": "5.13.1",
|
| 5310 |
+
"use_cache": true,
|
| 5311 |
+
"vocab_size": 248320
|
| 5312 |
+
}
|
qwen35_reap_keep50/configuration_pruned_qwen3_5_moe.py
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Configuration for GLEAN-pruned Qwen3.5-MoE: variable-width, variable-count experts.
|
| 2 |
+
|
| 3 |
+
Requires the ``qwen3_5_moe`` architecture (transformers >= 5.x); checkpoints
|
| 4 |
+
carrying this module import the upstream classes rather than vendoring the
|
| 5 |
+
~1.5k-line hybrid (GatedDeltaNet + attention) stack.
|
| 6 |
+
"""
|
| 7 |
+
|
| 8 |
+
from transformers.models.qwen3_5_moe.configuration_qwen3_5_moe import (
|
| 9 |
+
Qwen3_5MoeTextConfig,
|
| 10 |
+
)
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
class PrunedQwen3_5MoeTextConfig(Qwen3_5MoeTextConfig):
|
| 14 |
+
"""Qwen3_5MoeTextConfig plus a per-(layer, expert) width table.
|
| 15 |
+
|
| 16 |
+
``expert_widths[l]`` lists the SwiGLU intermediate width of each surviving
|
| 17 |
+
routed expert in decoder layer ``l``, in original expert order. Lists are
|
| 18 |
+
ragged: layers may keep different numbers of experts (deleted experts
|
| 19 |
+
simply don't appear — the router in layer ``l`` has
|
| 20 |
+
``len(expert_widths[l])`` rows), and each width may differ. ``None`` means
|
| 21 |
+
an unpruned model (uniform ``num_experts`` x ``moe_intermediate_size``).
|
| 22 |
+
|
| 23 |
+
The inherited ``num_experts`` / ``moe_intermediate_size`` keep their
|
| 24 |
+
ORIGINAL (pre-pruning) values for provenance; the width table is
|
| 25 |
+
authoritative for the built architecture. The shared expert and its
|
| 26 |
+
sigmoid gate are untouched by pruning and keep their stock config fields.
|
| 27 |
+
"""
|
| 28 |
+
|
| 29 |
+
model_type = "pruned_qwen3_5_moe"
|
| 30 |
+
|
| 31 |
+
expert_widths: list[list[int]] | None = None
|
qwen35_reap_keep50/generation_config.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 248044,
|
| 4 |
+
"eos_token_id": 248044,
|
| 5 |
+
"output_attentions": false,
|
| 6 |
+
"output_hidden_states": false,
|
| 7 |
+
"transformers_version": "5.13.1",
|
| 8 |
+
"use_cache": true
|
| 9 |
+
}
|
qwen35_reap_keep50/modeling_pruned_qwen3_5_moe.py
ADDED
|
@@ -0,0 +1,122 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""GLEAN-pruned Qwen3.5-MoE: HF-loadable model with ragged (variable-width) experts.
|
| 2 |
+
|
| 3 |
+
Same pattern as ``modeling_pruned_olmoe``: ``super().__init__`` builds the
|
| 4 |
+
uniform architecture from the config (free on the meta device during
|
| 5 |
+
``from_pretrained``), then every MoE block's router and fused experts are
|
| 6 |
+
rebuilt to their pruned shape — surviving experts only, each at its own width,
|
| 7 |
+
router rows sliced to match. The token mixers (GatedDeltaNet / attention), the
|
| 8 |
+
shared expert, and its sigmoid gate are stock and untouched.
|
| 9 |
+
|
| 10 |
+
Unlike OLMoE's per-expert ``nn.Linear`` modules, Qwen3.5-MoE fuses experts
|
| 11 |
+
into 3-D parameters, which cannot hold ragged widths — so the pruned experts
|
| 12 |
+
module stores per-expert 2-D parameters in ``nn.ParameterList``s
|
| 13 |
+
(``gate_up_projs.{j}`` ``[2*w_j, H]``, ``down_projs.{j}`` ``[H, w_j]``) and
|
| 14 |
+
runs the same routed per-expert loop as upstream ``Qwen3_5MoeExperts.forward``
|
| 15 |
+
(verified against transformers 5.13.1; re-verify after upgrades).
|
| 16 |
+
|
| 17 |
+
Caveats: ``output_router_logits=True`` (the load-balancing aux loss) assumes a
|
| 18 |
+
uniform ``config.num_experts`` and is unsupported on ragged models; the eager
|
| 19 |
+
per-expert loop bypasses the fused ``_experts_implementation`` kernels.
|
| 20 |
+
"""
|
| 21 |
+
|
| 22 |
+
import torch
|
| 23 |
+
import torch.nn.functional as F
|
| 24 |
+
from torch import nn
|
| 25 |
+
from transformers.activations import ACT2FN
|
| 26 |
+
from transformers.models.qwen3_5_moe.modeling_qwen3_5_moe import (
|
| 27 |
+
Qwen3_5MoeForCausalLM,
|
| 28 |
+
)
|
| 29 |
+
|
| 30 |
+
from .configuration_pruned_qwen3_5_moe import PrunedQwen3_5MoeTextConfig
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
class PrunedQwen3_5MoeExperts(nn.Module):
|
| 34 |
+
"""Ragged replacement for the fused ``Qwen3_5MoeExperts``.
|
| 35 |
+
|
| 36 |
+
Forward replicates the upstream routed per-expert loop exactly, indexing
|
| 37 |
+
per-expert parameters instead of slices of a stacked 3-D tensor.
|
| 38 |
+
"""
|
| 39 |
+
|
| 40 |
+
def __init__(self, config: PrunedQwen3_5MoeTextConfig, widths: list[int]):
|
| 41 |
+
super().__init__()
|
| 42 |
+
self.num_experts = len(widths)
|
| 43 |
+
self.hidden_dim = config.hidden_size
|
| 44 |
+
self.gate_up_projs = nn.ParameterList(
|
| 45 |
+
nn.Parameter(torch.empty(2 * w, config.hidden_size)) for w in widths
|
| 46 |
+
)
|
| 47 |
+
self.down_projs = nn.ParameterList(
|
| 48 |
+
nn.Parameter(torch.empty(config.hidden_size, w)) for w in widths
|
| 49 |
+
)
|
| 50 |
+
self.act_fn = ACT2FN[config.hidden_act]
|
| 51 |
+
|
| 52 |
+
def forward(
|
| 53 |
+
self,
|
| 54 |
+
hidden_states: torch.Tensor,
|
| 55 |
+
top_k_index: torch.Tensor,
|
| 56 |
+
top_k_weights: torch.Tensor,
|
| 57 |
+
) -> torch.Tensor:
|
| 58 |
+
final_hidden_states = torch.zeros_like(hidden_states)
|
| 59 |
+
with torch.no_grad():
|
| 60 |
+
expert_mask = F.one_hot(top_k_index, num_classes=self.num_experts)
|
| 61 |
+
expert_mask = expert_mask.permute(2, 1, 0)
|
| 62 |
+
expert_hit = torch.greater(expert_mask.sum(dim=(-1, -2)), 0).nonzero()
|
| 63 |
+
|
| 64 |
+
for expert_idx in expert_hit:
|
| 65 |
+
expert_idx = int(expert_idx[0])
|
| 66 |
+
top_k_pos, token_idx = torch.where(expert_mask[expert_idx])
|
| 67 |
+
current_state = hidden_states[token_idx]
|
| 68 |
+
gate, up = F.linear(current_state, self.gate_up_projs[expert_idx]).chunk(2, dim=-1)
|
| 69 |
+
current_hidden_states = self.act_fn(gate) * up
|
| 70 |
+
current_hidden_states = F.linear(current_hidden_states, self.down_projs[expert_idx])
|
| 71 |
+
current_hidden_states = current_hidden_states * top_k_weights[token_idx, top_k_pos, None]
|
| 72 |
+
final_hidden_states.index_add_(
|
| 73 |
+
0, token_idx, current_hidden_states.to(final_hidden_states.dtype)
|
| 74 |
+
)
|
| 75 |
+
|
| 76 |
+
return final_hidden_states
|
| 77 |
+
|
| 78 |
+
|
| 79 |
+
class PrunedQwen3_5MoeForCausalLM(Qwen3_5MoeForCausalLM):
|
| 80 |
+
"""Qwen3.5-MoE with per-layer surviving-expert lists at per-expert widths."""
|
| 81 |
+
|
| 82 |
+
config_class = PrunedQwen3_5MoeTextConfig
|
| 83 |
+
|
| 84 |
+
def __init__(self, config: PrunedQwen3_5MoeTextConfig):
|
| 85 |
+
super().__init__(config)
|
| 86 |
+
widths_table = getattr(config, "expert_widths", None)
|
| 87 |
+
if widths_table is None:
|
| 88 |
+
return # unpruned: plain Qwen3.5-MoE
|
| 89 |
+
if len(widths_table) != len(self.model.layers):
|
| 90 |
+
raise ValueError(
|
| 91 |
+
f"expert_widths has {len(widths_table)} rows but the model has "
|
| 92 |
+
f"{len(self.model.layers)} decoder layers"
|
| 93 |
+
)
|
| 94 |
+
for layer, widths in zip(self.model.layers, widths_table):
|
| 95 |
+
if any(w <= 0 for w in widths):
|
| 96 |
+
raise ValueError("expert_widths must list surviving experts only (>0)")
|
| 97 |
+
block = layer.mlp
|
| 98 |
+
if len(widths) < block.gate.top_k:
|
| 99 |
+
raise ValueError(
|
| 100 |
+
f"a layer keeps {len(widths)} experts < top_k={block.gate.top_k}"
|
| 101 |
+
)
|
| 102 |
+
# keep the stock router class (OutputRecorder isinstance, forward
|
| 103 |
+
# unchanged) but shrink it to the surviving experts' rows
|
| 104 |
+
block.gate.num_experts = len(widths)
|
| 105 |
+
block.gate.weight = nn.Parameter(
|
| 106 |
+
torch.empty(
|
| 107 |
+
len(widths),
|
| 108 |
+
config.hidden_size,
|
| 109 |
+
dtype=block.gate.weight.dtype,
|
| 110 |
+
device=block.gate.weight.device,
|
| 111 |
+
)
|
| 112 |
+
)
|
| 113 |
+
block.experts = PrunedQwen3_5MoeExperts(config, list(widths))
|
| 114 |
+
|
| 115 |
+
@torch.no_grad()
|
| 116 |
+
def _init_weights(self, module):
|
| 117 |
+
super()._init_weights(module)
|
| 118 |
+
# the base isinstance(Qwen3_5MoeExperts) branch never sees our ragged
|
| 119 |
+
# module; raw nn.Parameters get no default init otherwise
|
| 120 |
+
if isinstance(module, PrunedQwen3_5MoeExperts):
|
| 121 |
+
for p in list(module.gate_up_projs) + list(module.down_projs):
|
| 122 |
+
nn.init.normal_(p, mean=0.0, std=self.config.initializer_range)
|
qwen35_reap_keep50/reap_verify.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"keep": 0.5,
|
| 3 |
+
"criterion": "reap",
|
| 4 |
+
"ppl": 14.886332511901855,
|
| 5 |
+
"n_params_b": 18.543997568,
|
| 6 |
+
"eval_seq": 32,
|
| 7 |
+
"seq_len": 2048,
|
| 8 |
+
"dataset": "c4"
|
| 9 |
+
}
|
qwen35_reap_keep50/tokenizer_config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|im_end|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"local_files_only": false,
|
| 14 |
+
"model_max_length": 262144,
|
| 15 |
+
"model_specific_special_tokens": {
|
| 16 |
+
"audio_bos_token": "<|audio_start|>",
|
| 17 |
+
"audio_eos_token": "<|audio_end|>",
|
| 18 |
+
"audio_token": "<|audio_pad|>",
|
| 19 |
+
"image_token": "<|image_pad|>",
|
| 20 |
+
"video_token": "<|video_pad|>",
|
| 21 |
+
"vision_bos_token": "<|vision_start|>",
|
| 22 |
+
"vision_eos_token": "<|vision_end|>"
|
| 23 |
+
},
|
| 24 |
+
"pad_token": "<|endoftext|>",
|
| 25 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 26 |
+
"split_special_tokens": false,
|
| 27 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 28 |
+
"unk_token": null,
|
| 29 |
+
"video_token": "<|video_pad|>",
|
| 30 |
+
"vision_bos_token": "<|vision_start|>",
|
| 31 |
+
"vision_eos_token": "<|vision_end|>"
|
| 32 |
+
}
|
redo_policy/score_divergence.json
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"keep": 25,
|
| 4 |
+
"validated": true,
|
| 5 |
+
"kept": 262144,
|
| 6 |
+
"total": 1048576,
|
| 7 |
+
"jaccard_kept": 0.6221832369530846,
|
| 8 |
+
"disagree_all": 0.11645317077636719,
|
| 9 |
+
"math_pruned_general_keeps": 0.0776354471842448,
|
| 10 |
+
"dead_math": 442,
|
| 11 |
+
"dead_general": 405,
|
| 12 |
+
"dead_overlap": 359
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"keep": 50,
|
| 16 |
+
"validated": true,
|
| 17 |
+
"kept": 524288,
|
| 18 |
+
"total": 1048576,
|
| 19 |
+
"jaccard_kept": 0.7086550917816143,
|
| 20 |
+
"disagree_all": 0.17051124572753906,
|
| 21 |
+
"math_pruned_general_keeps": 0.17051124572753906,
|
| 22 |
+
"dead_math": 217,
|
| 23 |
+
"dead_general": 186,
|
| 24 |
+
"dead_overlap": 150
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"keep": 75,
|
| 28 |
+
"validated": true,
|
| 29 |
+
"kept": 786432,
|
| 30 |
+
"total": 1048576,
|
| 31 |
+
"jaccard_kept": 0.828006127197458,
|
| 32 |
+
"disagree_all": 0.14113235473632812,
|
| 33 |
+
"math_pruned_general_keeps": 0.28226470947265625,
|
| 34 |
+
"dead_math": 88,
|
| 35 |
+
"dead_general": 82,
|
| 36 |
+
"dead_overlap": 56
|
| 37 |
+
}
|
| 38 |
+
]
|
teacher_trajectories/dolci_math_curated.stats.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"input": [
|
| 3 |
+
"outputs/teacher_trajectories/dolci_math_chat_n4_t0.8.jsonl",
|
| 4 |
+
"outputs/teacher_trajectories/dolci_math_chat_n4_t0.8.chunks27-32.jsonl"
|
| 5 |
+
],
|
| 6 |
+
"output": "outputs/teacher_trajectories/dolci_math_curated.jsonl",
|
| 7 |
+
"min_agreement": 1,
|
| 8 |
+
"require_finished": true,
|
| 9 |
+
"require_gold_match": true,
|
| 10 |
+
"max_prompt_idx": null,
|
| 11 |
+
"prompts": 63977,
|
| 12 |
+
"selected_prompts": 6673,
|
| 13 |
+
"selected_trajectories": 10110,
|
| 14 |
+
"selected_completion_tokens": 4946904,
|
| 15 |
+
"mean_completion_tokens": 489.3080118694362,
|
| 16 |
+
"prompt_keep_rate": 0.10430310892977164,
|
| 17 |
+
"consensus_vote_counts_by_prompt": {
|
| 18 |
+
"1": 4527,
|
| 19 |
+
"3": 563,
|
| 20 |
+
"2": 1219,
|
| 21 |
+
"4": 364
|
| 22 |
+
},
|
| 23 |
+
"reasons": {
|
| 24 |
+
"unfinished": 16552,
|
| 25 |
+
"gold_mismatch": 40740,
|
| 26 |
+
"kept": 6673,
|
| 27 |
+
"no_answer": 12
|
| 28 |
+
}
|
| 29 |
+
}
|
teacher_trajectories/dolci_math_curated_opd.stats.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"input": [
|
| 3 |
+
"outputs/teacher_trajectories/dolci_math_chat_n4_t0.8.jsonl",
|
| 4 |
+
"outputs/teacher_trajectories/dolci_math_chat_n4_t0.8.chunks27-32.jsonl"
|
| 5 |
+
],
|
| 6 |
+
"output": "outputs/teacher_trajectories/dolci_math_curated_opd.jsonl",
|
| 7 |
+
"min_agreement": 1,
|
| 8 |
+
"require_finished": false,
|
| 9 |
+
"unfinished_min_agreement": 2,
|
| 10 |
+
"require_gold_match": true,
|
| 11 |
+
"max_prompt_idx": null,
|
| 12 |
+
"prompts": 63977,
|
| 13 |
+
"selected_prompts": 7322,
|
| 14 |
+
"selected_trajectories": 12115,
|
| 15 |
+
"selected_completion_tokens": 6476634,
|
| 16 |
+
"mean_completion_tokens": 534.5962855963681,
|
| 17 |
+
"prompt_keep_rate": 0.11444737952701753,
|
| 18 |
+
"consensus_vote_counts_by_prompt": {
|
| 19 |
+
"1": 4112,
|
| 20 |
+
"3": 767,
|
| 21 |
+
"2": 2035,
|
| 22 |
+
"4": 408
|
| 23 |
+
},
|
| 24 |
+
"reasons": {
|
| 25 |
+
"gold_mismatch": 53958,
|
| 26 |
+
"kept": 7322,
|
| 27 |
+
"low_agreement_unfinished": 2694,
|
| 28 |
+
"no_answer": 3
|
| 29 |
+
}
|
| 30 |
+
}
|
teacher_trajectories/dolci_math_nogold_matched.stats.json
ADDED
|
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"input": "outputs/teacher_trajectories/dolci_math_nogold.jsonl",
|
| 3 |
+
"output": "outputs/teacher_trajectories/dolci_math_nogold_matched.jsonl",
|
| 4 |
+
"seed": 1224,
|
| 5 |
+
"target_tokens": 6476634,
|
| 6 |
+
"selected_tokens": 6476712,
|
| 7 |
+
"selected_trajectories": 9918,
|
| 8 |
+
"unique_prompts": 8748,
|
| 9 |
+
"pool_trajectories": 57420
|
| 10 |
+
}
|
teacher_trajectories/dolci_math_nogold_matched_top128.score.log
ADDED
|
@@ -0,0 +1,647 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
reconstructing exact chat prompts ...
|
| 2 |
+
loading teacher on cuda:0 ...
|
| 3 |
+
|
| 4 |
+
shard 00000: 128/9918 records | 86,738 tokens | 8.71 records/s
|
| 5 |
+
shard 00001: 256/9918 records | 167,821 tokens | 8.96 records/s
|
| 6 |
+
shard 00002: 384/9918 records | 252,309 tokens | 9.04 records/s
|
| 7 |
+
shard 00003: 512/9918 records | 334,964 tokens | 9.09 records/s
|
| 8 |
+
shard 00004: 640/9918 records | 417,335 tokens | 9.13 records/s
|
| 9 |
+
shard 00005: 768/9918 records | 500,766 tokens | 9.14 records/s
|
| 10 |
+
shard 00006: 896/9918 records | 581,333 tokens | 9.16 records/s
|
| 11 |
+
shard 00007: 1024/9918 records | 661,718 tokens | 9.18 records/s
|
| 12 |
+
shard 00008: 1152/9918 records | 748,886 tokens | 9.19 records/s
|
| 13 |
+
shard 00009: 1280/9918 records | 836,216 tokens | 9.19 records/s
|
| 14 |
+
shard 00010: 1408/9918 records | 920,766 tokens | 9.20 records/s
|
| 15 |
+
shard 00011: 1536/9918 records | 1,006,776 tokens | 9.21 records/s
|
| 16 |
+
shard 00012: 1664/9918 records | 1,089,613 tokens | 9.21 records/s
|
| 17 |
+
shard 00013: 1792/9918 records | 1,176,076 tokens | 9.21 records/s
|
| 18 |
+
shard 00014: 1920/9918 records | 1,261,191 tokens | 9.21 records/s
|
| 19 |
+
shard 00015: 2048/9918 records | 1,344,996 tokens | 9.21 records/s
|
| 20 |
+
shard 00016: 2176/9918 records | 1,428,549 tokens | 9.22 records/s
|
| 21 |
+
shard 00017: 2304/9918 records | 1,509,478 tokens | 9.22 records/s
|
| 22 |
+
shard 00018: 2432/9918 records | 1,595,067 tokens | 9.23 records/s
|
| 23 |
+
shard 00019: 2560/9918 records | 1,678,874 tokens | 9.23 records/s
|
| 24 |
+
shard 00020: 2688/9918 records | 1,763,838 tokens | 9.23 records/s
|
| 25 |
+
shard 00021: 2816/9918 records | 1,838,106 tokens | 9.23 records/s
|
| 26 |
+
shard 00022: 2944/9918 records | 1,915,047 tokens | 9.23 records/s
|
| 27 |
+
shard 00023: 3072/9918 records | 1,991,387 tokens | 9.24 records/s
|
| 28 |
+
shard 00024: 3200/9918 records | 2,067,294 tokens | 9.25 records/s
|
| 29 |
+
shard 00025: 3328/9918 records | 2,140,318 tokens | 9.26 records/s
|
| 30 |
+
shard 00026: 3456/9918 records | 2,216,508 tokens | 9.27 records/s
|
| 31 |
+
shard 00027: 3584/9918 records | 2,288,848 tokens | 9.27 records/s
|
| 32 |
+
shard 00028: 3712/9918 records | 2,365,928 tokens | 9.27 records/s
|
| 33 |
+
shard 00029: 3840/9918 records | 2,439,058 tokens | 9.28 records/s
|
| 34 |
+
shard 00030: 3968/9918 records | 2,517,122 tokens | 9.28 records/s
|
| 35 |
+
shard 00031: 4096/9918 records | 2,593,654 tokens | 9.28 records/s
|
| 36 |
+
shard 00032: 4224/9918 records | 2,667,587 tokens | 9.29 records/s
|
| 37 |
+
shard 00033: 4352/9918 records | 2,742,631 tokens | 9.29 records/s
|
| 38 |
+
shard 00034: 4480/9918 records | 2,814,842 tokens | 9.29 records/s
|
| 39 |
+
shard 00035: 4608/9918 records | 2,890,157 tokens | 9.30 records/s
|
| 40 |
+
shard 00036: 4736/9918 records | 2,966,385 tokens | 9.30 records/s
|
| 41 |
+
shard 00037: 4864/9918 records | 3,039,781 tokens | 9.30 records/s
|
| 42 |
+
shard 00038: 4992/9918 records | 3,116,074 tokens | 9.31 records/s
|
| 43 |
+
shard 00039: 5120/9918 records | 3,203,251 tokens | 9.30 records/s
|
| 44 |
+
shard 00040: 5248/9918 records | 3,293,236 tokens | 9.30 records/s
|
| 45 |
+
shard 00041: 5376/9918 records | 3,382,951 tokens | 9.29 records/s
|
| 46 |
+
shard 00042: 5504/9918 records | 3,471,094 tokens | 9.28 records/s
|
| 47 |
+
shard 00043: 5632/9918 records | 3,562,058 tokens | 9.27 records/s
|
| 48 |
+
shard 00044: 5760/9918 records | 3,650,120 tokens | 9.26 records/s
|
| 49 |
+
shard 00045: 5888/9918 records | 3,738,179 tokens | 9.25 records/s
|
| 50 |
+
shard 00046: 6016/9918 records | 3,827,029 tokens | 9.24 records/s
|
| 51 |
+
shard 00047: 6144/9918 records | 3,917,892 tokens | 9.23 records/s
|
| 52 |
+
shard 00048: 6272/9918 records | 4,005,920 tokens | 9.22 records/s
|
| 53 |
+
shard 00049: 6400/9918 records | 4,095,241 tokens | 9.21 records/s
|
| 54 |
+
shard 00050: 6528/9918 records | 4,183,072 tokens | 9.20 records/s
|
| 55 |
+
shard 00051: 6656/9918 records | 4,269,396 tokens | 9.20 records/s
|
| 56 |
+
shard 00052: 6784/9918 records | 4,353,524 tokens | 9.20 records/s
|
| 57 |
+
shard 00053: 6912/9918 records | 4,445,816 tokens | 9.19 records/s
|
| 58 |
+
shard 00054: 7040/9918 records | 4,537,739 tokens | 9.18 records/s
|
| 59 |
+
shard 00055: 7168/9918 records | 4,627,901 tokens | 9.18 records/s
|
| 60 |
+
shard 00056: 7296/9918 records | 4,716,890 tokens | 9.17 records/s
|
| 61 |
+
shard 00057: 7424/9918 records | 4,802,719 tokens | 9.17 records/s
|
| 62 |
+
shard 00058: 7552/9918 records | 4,888,043 tokens | 9.17 records/s
|
| 63 |
+
shard 00059: 7680/9918 records | 4,972,545 tokens | 9.17 records/s
|
| 64 |
+
shard 00060: 7808/9918 records | 5,056,045 tokens | 9.17 records/s
|
| 65 |
+
shard 00061: 7936/9918 records | 5,144,939 tokens | 9.17 records/s
|
| 66 |
+
shard 00062: 8064/9918 records | 5,228,021 tokens | 9.17 records/s
|
| 67 |
+
shard 00063: 8192/9918 records | 5,311,363 tokens | 9.17 records/s
|
| 68 |
+
shard 00064: 8320/9918 records | 5,395,159 tokens | 9.18 records/s
|
| 69 |
+
shard 00065: 8448/9918 records | 5,478,974 tokens | 9.18 records/s
|
| 70 |
+
shard 00066: 8576/9918 records | 5,562,357 tokens | 9.18 records/s
|
| 71 |
+
shard 00067: 8704/9918 records | 5,648,649 tokens | 9.18 records/s
|
| 72 |
+
shard 00068: 8832/9918 records | 5,732,310 tokens | 9.18 records/s
|
| 73 |
+
shard 00069: 8960/9918 records | 5,814,685 tokens | 9.18 records/s
|
| 74 |
+
shard 00070: 9088/9918 records | 5,902,712 tokens | 9.18 records/s
|
| 75 |
+
shard 00071: 9216/9918 records | 5,991,814 tokens | 9.18 records/s
|
| 76 |
+
shard 00072: 9344/9918 records | 6,081,881 tokens | 9.18 records/s
|
| 77 |
+
shard 00073: 9472/9918 records | 6,174,078 tokens | 9.18 records/s
|
| 78 |
+
shard 00074: 9600/9918 records | 6,263,194 tokens | 9.18 records/s
|
| 79 |
+
shard 00075: 9728/9918 records | 6,345,278 tokens | 9.18 records/s
|
| 80 |
+
shard 00076: 9856/9918 records | 6,436,191 tokens | 9.18 records/s
|
| 81 |
+
shard 00077: 9918/9918 records | 6,476,712 tokens | 9.18 records/s
|
| 82 |
+
{
|
| 83 |
+
"version": 1,
|
| 84 |
+
"complete": true,
|
| 85 |
+
"teacher": "allenai/OLMoE-1B-7B-0125-Instruct",
|
| 86 |
+
"tokenizer": "allenai/OLMoE-1B-7B-0125-Instruct",
|
| 87 |
+
"source": "/home/henry/Documents/PythonProjects/variable-reap/outputs/teacher_trajectories/dolci_math_nogold_matched.jsonl",
|
| 88 |
+
"source_size": 56024209,
|
| 89 |
+
"frame": "chat",
|
| 90 |
+
"topk": 128,
|
| 91 |
+
"max_prompt_len": 1024,
|
| 92 |
+
"max_seq_len": 2048,
|
| 93 |
+
"pad_token_id": 50280,
|
| 94 |
+
"eos_token_id": 50279,
|
| 95 |
+
"total_records": 9918,
|
| 96 |
+
"total_tokens": 6476712,
|
| 97 |
+
"shards": [
|
| 98 |
+
{
|
| 99 |
+
"path": "shard_00000.pt",
|
| 100 |
+
"records": 128,
|
| 101 |
+
"tokens": 86738,
|
| 102 |
+
"first_record": 0,
|
| 103 |
+
"last_record": 127
|
| 104 |
+
},
|
| 105 |
+
{
|
| 106 |
+
"path": "shard_00001.pt",
|
| 107 |
+
"records": 128,
|
| 108 |
+
"tokens": 81083,
|
| 109 |
+
"first_record": 128,
|
| 110 |
+
"last_record": 255
|
| 111 |
+
},
|
| 112 |
+
{
|
| 113 |
+
"path": "shard_00002.pt",
|
| 114 |
+
"records": 128,
|
| 115 |
+
"tokens": 84488,
|
| 116 |
+
"first_record": 256,
|
| 117 |
+
"last_record": 383
|
| 118 |
+
},
|
| 119 |
+
{
|
| 120 |
+
"path": "shard_00003.pt",
|
| 121 |
+
"records": 128,
|
| 122 |
+
"tokens": 82655,
|
| 123 |
+
"first_record": 384,
|
| 124 |
+
"last_record": 511
|
| 125 |
+
},
|
| 126 |
+
{
|
| 127 |
+
"path": "shard_00004.pt",
|
| 128 |
+
"records": 128,
|
| 129 |
+
"tokens": 82371,
|
| 130 |
+
"first_record": 512,
|
| 131 |
+
"last_record": 639
|
| 132 |
+
},
|
| 133 |
+
{
|
| 134 |
+
"path": "shard_00005.pt",
|
| 135 |
+
"records": 128,
|
| 136 |
+
"tokens": 83431,
|
| 137 |
+
"first_record": 640,
|
| 138 |
+
"last_record": 767
|
| 139 |
+
},
|
| 140 |
+
{
|
| 141 |
+
"path": "shard_00006.pt",
|
| 142 |
+
"records": 128,
|
| 143 |
+
"tokens": 80567,
|
| 144 |
+
"first_record": 768,
|
| 145 |
+
"last_record": 895
|
| 146 |
+
},
|
| 147 |
+
{
|
| 148 |
+
"path": "shard_00007.pt",
|
| 149 |
+
"records": 128,
|
| 150 |
+
"tokens": 80385,
|
| 151 |
+
"first_record": 896,
|
| 152 |
+
"last_record": 1023
|
| 153 |
+
},
|
| 154 |
+
{
|
| 155 |
+
"path": "shard_00008.pt",
|
| 156 |
+
"records": 128,
|
| 157 |
+
"tokens": 87168,
|
| 158 |
+
"first_record": 1024,
|
| 159 |
+
"last_record": 1151
|
| 160 |
+
},
|
| 161 |
+
{
|
| 162 |
+
"path": "shard_00009.pt",
|
| 163 |
+
"records": 128,
|
| 164 |
+
"tokens": 87330,
|
| 165 |
+
"first_record": 1152,
|
| 166 |
+
"last_record": 1279
|
| 167 |
+
},
|
| 168 |
+
{
|
| 169 |
+
"path": "shard_00010.pt",
|
| 170 |
+
"records": 128,
|
| 171 |
+
"tokens": 84550,
|
| 172 |
+
"first_record": 1280,
|
| 173 |
+
"last_record": 1407
|
| 174 |
+
},
|
| 175 |
+
{
|
| 176 |
+
"path": "shard_00011.pt",
|
| 177 |
+
"records": 128,
|
| 178 |
+
"tokens": 86010,
|
| 179 |
+
"first_record": 1408,
|
| 180 |
+
"last_record": 1535
|
| 181 |
+
},
|
| 182 |
+
{
|
| 183 |
+
"path": "shard_00012.pt",
|
| 184 |
+
"records": 128,
|
| 185 |
+
"tokens": 82837,
|
| 186 |
+
"first_record": 1536,
|
| 187 |
+
"last_record": 1663
|
| 188 |
+
},
|
| 189 |
+
{
|
| 190 |
+
"path": "shard_00013.pt",
|
| 191 |
+
"records": 128,
|
| 192 |
+
"tokens": 86463,
|
| 193 |
+
"first_record": 1664,
|
| 194 |
+
"last_record": 1791
|
| 195 |
+
},
|
| 196 |
+
{
|
| 197 |
+
"path": "shard_00014.pt",
|
| 198 |
+
"records": 128,
|
| 199 |
+
"tokens": 85115,
|
| 200 |
+
"first_record": 1792,
|
| 201 |
+
"last_record": 1919
|
| 202 |
+
},
|
| 203 |
+
{
|
| 204 |
+
"path": "shard_00015.pt",
|
| 205 |
+
"records": 128,
|
| 206 |
+
"tokens": 83805,
|
| 207 |
+
"first_record": 1920,
|
| 208 |
+
"last_record": 2047
|
| 209 |
+
},
|
| 210 |
+
{
|
| 211 |
+
"path": "shard_00016.pt",
|
| 212 |
+
"records": 128,
|
| 213 |
+
"tokens": 83553,
|
| 214 |
+
"first_record": 2048,
|
| 215 |
+
"last_record": 2175
|
| 216 |
+
},
|
| 217 |
+
{
|
| 218 |
+
"path": "shard_00017.pt",
|
| 219 |
+
"records": 128,
|
| 220 |
+
"tokens": 80929,
|
| 221 |
+
"first_record": 2176,
|
| 222 |
+
"last_record": 2303
|
| 223 |
+
},
|
| 224 |
+
{
|
| 225 |
+
"path": "shard_00018.pt",
|
| 226 |
+
"records": 128,
|
| 227 |
+
"tokens": 85589,
|
| 228 |
+
"first_record": 2304,
|
| 229 |
+
"last_record": 2431
|
| 230 |
+
},
|
| 231 |
+
{
|
| 232 |
+
"path": "shard_00019.pt",
|
| 233 |
+
"records": 128,
|
| 234 |
+
"tokens": 83807,
|
| 235 |
+
"first_record": 2432,
|
| 236 |
+
"last_record": 2559
|
| 237 |
+
},
|
| 238 |
+
{
|
| 239 |
+
"path": "shard_00020.pt",
|
| 240 |
+
"records": 128,
|
| 241 |
+
"tokens": 84964,
|
| 242 |
+
"first_record": 2560,
|
| 243 |
+
"last_record": 2687
|
| 244 |
+
},
|
| 245 |
+
{
|
| 246 |
+
"path": "shard_00021.pt",
|
| 247 |
+
"records": 128,
|
| 248 |
+
"tokens": 74268,
|
| 249 |
+
"first_record": 2688,
|
| 250 |
+
"last_record": 2815
|
| 251 |
+
},
|
| 252 |
+
{
|
| 253 |
+
"path": "shard_00022.pt",
|
| 254 |
+
"records": 128,
|
| 255 |
+
"tokens": 76941,
|
| 256 |
+
"first_record": 2816,
|
| 257 |
+
"last_record": 2943
|
| 258 |
+
},
|
| 259 |
+
{
|
| 260 |
+
"path": "shard_00023.pt",
|
| 261 |
+
"records": 128,
|
| 262 |
+
"tokens": 76340,
|
| 263 |
+
"first_record": 2944,
|
| 264 |
+
"last_record": 3071
|
| 265 |
+
},
|
| 266 |
+
{
|
| 267 |
+
"path": "shard_00024.pt",
|
| 268 |
+
"records": 128,
|
| 269 |
+
"tokens": 75907,
|
| 270 |
+
"first_record": 3072,
|
| 271 |
+
"last_record": 3199
|
| 272 |
+
},
|
| 273 |
+
{
|
| 274 |
+
"path": "shard_00025.pt",
|
| 275 |
+
"records": 128,
|
| 276 |
+
"tokens": 73024,
|
| 277 |
+
"first_record": 3200,
|
| 278 |
+
"last_record": 3327
|
| 279 |
+
},
|
| 280 |
+
{
|
| 281 |
+
"path": "shard_00026.pt",
|
| 282 |
+
"records": 128,
|
| 283 |
+
"tokens": 76190,
|
| 284 |
+
"first_record": 3328,
|
| 285 |
+
"last_record": 3455
|
| 286 |
+
},
|
| 287 |
+
{
|
| 288 |
+
"path": "shard_00027.pt",
|
| 289 |
+
"records": 128,
|
| 290 |
+
"tokens": 72340,
|
| 291 |
+
"first_record": 3456,
|
| 292 |
+
"last_record": 3583
|
| 293 |
+
},
|
| 294 |
+
{
|
| 295 |
+
"path": "shard_00028.pt",
|
| 296 |
+
"records": 128,
|
| 297 |
+
"tokens": 77080,
|
| 298 |
+
"first_record": 3584,
|
| 299 |
+
"last_record": 3711
|
| 300 |
+
},
|
| 301 |
+
{
|
| 302 |
+
"path": "shard_00029.pt",
|
| 303 |
+
"records": 128,
|
| 304 |
+
"tokens": 73130,
|
| 305 |
+
"first_record": 3712,
|
| 306 |
+
"last_record": 3839
|
| 307 |
+
},
|
| 308 |
+
{
|
| 309 |
+
"path": "shard_00030.pt",
|
| 310 |
+
"records": 128,
|
| 311 |
+
"tokens": 78064,
|
| 312 |
+
"first_record": 3840,
|
| 313 |
+
"last_record": 3967
|
| 314 |
+
},
|
| 315 |
+
{
|
| 316 |
+
"path": "shard_00031.pt",
|
| 317 |
+
"records": 128,
|
| 318 |
+
"tokens": 76532,
|
| 319 |
+
"first_record": 3968,
|
| 320 |
+
"last_record": 4095
|
| 321 |
+
},
|
| 322 |
+
{
|
| 323 |
+
"path": "shard_00032.pt",
|
| 324 |
+
"records": 128,
|
| 325 |
+
"tokens": 73933,
|
| 326 |
+
"first_record": 4096,
|
| 327 |
+
"last_record": 4223
|
| 328 |
+
},
|
| 329 |
+
{
|
| 330 |
+
"path": "shard_00033.pt",
|
| 331 |
+
"records": 128,
|
| 332 |
+
"tokens": 75044,
|
| 333 |
+
"first_record": 4224,
|
| 334 |
+
"last_record": 4351
|
| 335 |
+
},
|
| 336 |
+
{
|
| 337 |
+
"path": "shard_00034.pt",
|
| 338 |
+
"records": 128,
|
| 339 |
+
"tokens": 72211,
|
| 340 |
+
"first_record": 4352,
|
| 341 |
+
"last_record": 4479
|
| 342 |
+
},
|
| 343 |
+
{
|
| 344 |
+
"path": "shard_00035.pt",
|
| 345 |
+
"records": 128,
|
| 346 |
+
"tokens": 75315,
|
| 347 |
+
"first_record": 4480,
|
| 348 |
+
"last_record": 4607
|
| 349 |
+
},
|
| 350 |
+
{
|
| 351 |
+
"path": "shard_00036.pt",
|
| 352 |
+
"records": 128,
|
| 353 |
+
"tokens": 76228,
|
| 354 |
+
"first_record": 4608,
|
| 355 |
+
"last_record": 4735
|
| 356 |
+
},
|
| 357 |
+
{
|
| 358 |
+
"path": "shard_00037.pt",
|
| 359 |
+
"records": 128,
|
| 360 |
+
"tokens": 73396,
|
| 361 |
+
"first_record": 4736,
|
| 362 |
+
"last_record": 4863
|
| 363 |
+
},
|
| 364 |
+
{
|
| 365 |
+
"path": "shard_00038.pt",
|
| 366 |
+
"records": 128,
|
| 367 |
+
"tokens": 76293,
|
| 368 |
+
"first_record": 4864,
|
| 369 |
+
"last_record": 4991
|
| 370 |
+
},
|
| 371 |
+
{
|
| 372 |
+
"path": "shard_00039.pt",
|
| 373 |
+
"records": 128,
|
| 374 |
+
"tokens": 87177,
|
| 375 |
+
"first_record": 4992,
|
| 376 |
+
"last_record": 5119
|
| 377 |
+
},
|
| 378 |
+
{
|
| 379 |
+
"path": "shard_00040.pt",
|
| 380 |
+
"records": 128,
|
| 381 |
+
"tokens": 89985,
|
| 382 |
+
"first_record": 5120,
|
| 383 |
+
"last_record": 5247
|
| 384 |
+
},
|
| 385 |
+
{
|
| 386 |
+
"path": "shard_00041.pt",
|
| 387 |
+
"records": 128,
|
| 388 |
+
"tokens": 89715,
|
| 389 |
+
"first_record": 5248,
|
| 390 |
+
"last_record": 5375
|
| 391 |
+
},
|
| 392 |
+
{
|
| 393 |
+
"path": "shard_00042.pt",
|
| 394 |
+
"records": 128,
|
| 395 |
+
"tokens": 88143,
|
| 396 |
+
"first_record": 5376,
|
| 397 |
+
"last_record": 5503
|
| 398 |
+
},
|
| 399 |
+
{
|
| 400 |
+
"path": "shard_00043.pt",
|
| 401 |
+
"records": 128,
|
| 402 |
+
"tokens": 90964,
|
| 403 |
+
"first_record": 5504,
|
| 404 |
+
"last_record": 5631
|
| 405 |
+
},
|
| 406 |
+
{
|
| 407 |
+
"path": "shard_00044.pt",
|
| 408 |
+
"records": 128,
|
| 409 |
+
"tokens": 88062,
|
| 410 |
+
"first_record": 5632,
|
| 411 |
+
"last_record": 5759
|
| 412 |
+
},
|
| 413 |
+
{
|
| 414 |
+
"path": "shard_00045.pt",
|
| 415 |
+
"records": 128,
|
| 416 |
+
"tokens": 88059,
|
| 417 |
+
"first_record": 5760,
|
| 418 |
+
"last_record": 5887
|
| 419 |
+
},
|
| 420 |
+
{
|
| 421 |
+
"path": "shard_00046.pt",
|
| 422 |
+
"records": 128,
|
| 423 |
+
"tokens": 88850,
|
| 424 |
+
"first_record": 5888,
|
| 425 |
+
"last_record": 6015
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"path": "shard_00047.pt",
|
| 429 |
+
"records": 128,
|
| 430 |
+
"tokens": 90863,
|
| 431 |
+
"first_record": 6016,
|
| 432 |
+
"last_record": 6143
|
| 433 |
+
},
|
| 434 |
+
{
|
| 435 |
+
"path": "shard_00048.pt",
|
| 436 |
+
"records": 128,
|
| 437 |
+
"tokens": 88028,
|
| 438 |
+
"first_record": 6144,
|
| 439 |
+
"last_record": 6271
|
| 440 |
+
},
|
| 441 |
+
{
|
| 442 |
+
"path": "shard_00049.pt",
|
| 443 |
+
"records": 128,
|
| 444 |
+
"tokens": 89321,
|
| 445 |
+
"first_record": 6272,
|
| 446 |
+
"last_record": 6399
|
| 447 |
+
},
|
| 448 |
+
{
|
| 449 |
+
"path": "shard_00050.pt",
|
| 450 |
+
"records": 128,
|
| 451 |
+
"tokens": 87831,
|
| 452 |
+
"first_record": 6400,
|
| 453 |
+
"last_record": 6527
|
| 454 |
+
},
|
| 455 |
+
{
|
| 456 |
+
"path": "shard_00051.pt",
|
| 457 |
+
"records": 128,
|
| 458 |
+
"tokens": 86324,
|
| 459 |
+
"first_record": 6528,
|
| 460 |
+
"last_record": 6655
|
| 461 |
+
},
|
| 462 |
+
{
|
| 463 |
+
"path": "shard_00052.pt",
|
| 464 |
+
"records": 128,
|
| 465 |
+
"tokens": 84128,
|
| 466 |
+
"first_record": 6656,
|
| 467 |
+
"last_record": 6783
|
| 468 |
+
},
|
| 469 |
+
{
|
| 470 |
+
"path": "shard_00053.pt",
|
| 471 |
+
"records": 128,
|
| 472 |
+
"tokens": 92292,
|
| 473 |
+
"first_record": 6784,
|
| 474 |
+
"last_record": 6911
|
| 475 |
+
},
|
| 476 |
+
{
|
| 477 |
+
"path": "shard_00054.pt",
|
| 478 |
+
"records": 128,
|
| 479 |
+
"tokens": 91923,
|
| 480 |
+
"first_record": 6912,
|
| 481 |
+
"last_record": 7039
|
| 482 |
+
},
|
| 483 |
+
{
|
| 484 |
+
"path": "shard_00055.pt",
|
| 485 |
+
"records": 128,
|
| 486 |
+
"tokens": 90162,
|
| 487 |
+
"first_record": 7040,
|
| 488 |
+
"last_record": 7167
|
| 489 |
+
},
|
| 490 |
+
{
|
| 491 |
+
"path": "shard_00056.pt",
|
| 492 |
+
"records": 128,
|
| 493 |
+
"tokens": 88989,
|
| 494 |
+
"first_record": 7168,
|
| 495 |
+
"last_record": 7295
|
| 496 |
+
},
|
| 497 |
+
{
|
| 498 |
+
"path": "shard_00057.pt",
|
| 499 |
+
"records": 128,
|
| 500 |
+
"tokens": 85829,
|
| 501 |
+
"first_record": 7296,
|
| 502 |
+
"last_record": 7423
|
| 503 |
+
},
|
| 504 |
+
{
|
| 505 |
+
"path": "shard_00058.pt",
|
| 506 |
+
"records": 128,
|
| 507 |
+
"tokens": 85324,
|
| 508 |
+
"first_record": 7424,
|
| 509 |
+
"last_record": 7551
|
| 510 |
+
},
|
| 511 |
+
{
|
| 512 |
+
"path": "shard_00059.pt",
|
| 513 |
+
"records": 128,
|
| 514 |
+
"tokens": 84502,
|
| 515 |
+
"first_record": 7552,
|
| 516 |
+
"last_record": 7679
|
| 517 |
+
},
|
| 518 |
+
{
|
| 519 |
+
"path": "shard_00060.pt",
|
| 520 |
+
"records": 128,
|
| 521 |
+
"tokens": 83500,
|
| 522 |
+
"first_record": 7680,
|
| 523 |
+
"last_record": 7807
|
| 524 |
+
},
|
| 525 |
+
{
|
| 526 |
+
"path": "shard_00061.pt",
|
| 527 |
+
"records": 128,
|
| 528 |
+
"tokens": 88894,
|
| 529 |
+
"first_record": 7808,
|
| 530 |
+
"last_record": 7935
|
| 531 |
+
},
|
| 532 |
+
{
|
| 533 |
+
"path": "shard_00062.pt",
|
| 534 |
+
"records": 128,
|
| 535 |
+
"tokens": 83082,
|
| 536 |
+
"first_record": 7936,
|
| 537 |
+
"last_record": 8063
|
| 538 |
+
},
|
| 539 |
+
{
|
| 540 |
+
"path": "shard_00063.pt",
|
| 541 |
+
"records": 128,
|
| 542 |
+
"tokens": 83342,
|
| 543 |
+
"first_record": 8064,
|
| 544 |
+
"last_record": 8191
|
| 545 |
+
},
|
| 546 |
+
{
|
| 547 |
+
"path": "shard_00064.pt",
|
| 548 |
+
"records": 128,
|
| 549 |
+
"tokens": 83796,
|
| 550 |
+
"first_record": 8192,
|
| 551 |
+
"last_record": 8319
|
| 552 |
+
},
|
| 553 |
+
{
|
| 554 |
+
"path": "shard_00065.pt",
|
| 555 |
+
"records": 128,
|
| 556 |
+
"tokens": 83815,
|
| 557 |
+
"first_record": 8320,
|
| 558 |
+
"last_record": 8447
|
| 559 |
+
},
|
| 560 |
+
{
|
| 561 |
+
"path": "shard_00066.pt",
|
| 562 |
+
"records": 128,
|
| 563 |
+
"tokens": 83383,
|
| 564 |
+
"first_record": 8448,
|
| 565 |
+
"last_record": 8575
|
| 566 |
+
},
|
| 567 |
+
{
|
| 568 |
+
"path": "shard_00067.pt",
|
| 569 |
+
"records": 128,
|
| 570 |
+
"tokens": 86292,
|
| 571 |
+
"first_record": 8576,
|
| 572 |
+
"last_record": 8703
|
| 573 |
+
},
|
| 574 |
+
{
|
| 575 |
+
"path": "shard_00068.pt",
|
| 576 |
+
"records": 128,
|
| 577 |
+
"tokens": 83661,
|
| 578 |
+
"first_record": 8704,
|
| 579 |
+
"last_record": 8831
|
| 580 |
+
},
|
| 581 |
+
{
|
| 582 |
+
"path": "shard_00069.pt",
|
| 583 |
+
"records": 128,
|
| 584 |
+
"tokens": 82375,
|
| 585 |
+
"first_record": 8832,
|
| 586 |
+
"last_record": 8959
|
| 587 |
+
},
|
| 588 |
+
{
|
| 589 |
+
"path": "shard_00070.pt",
|
| 590 |
+
"records": 128,
|
| 591 |
+
"tokens": 88027,
|
| 592 |
+
"first_record": 8960,
|
| 593 |
+
"last_record": 9087
|
| 594 |
+
},
|
| 595 |
+
{
|
| 596 |
+
"path": "shard_00071.pt",
|
| 597 |
+
"records": 128,
|
| 598 |
+
"tokens": 89102,
|
| 599 |
+
"first_record": 9088,
|
| 600 |
+
"last_record": 9215
|
| 601 |
+
},
|
| 602 |
+
{
|
| 603 |
+
"path": "shard_00072.pt",
|
| 604 |
+
"records": 128,
|
| 605 |
+
"tokens": 90067,
|
| 606 |
+
"first_record": 9216,
|
| 607 |
+
"last_record": 9343
|
| 608 |
+
},
|
| 609 |
+
{
|
| 610 |
+
"path": "shard_00073.pt",
|
| 611 |
+
"records": 128,
|
| 612 |
+
"tokens": 92197,
|
| 613 |
+
"first_record": 9344,
|
| 614 |
+
"last_record": 9471
|
| 615 |
+
},
|
| 616 |
+
{
|
| 617 |
+
"path": "shard_00074.pt",
|
| 618 |
+
"records": 128,
|
| 619 |
+
"tokens": 89116,
|
| 620 |
+
"first_record": 9472,
|
| 621 |
+
"last_record": 9599
|
| 622 |
+
},
|
| 623 |
+
{
|
| 624 |
+
"path": "shard_00075.pt",
|
| 625 |
+
"records": 128,
|
| 626 |
+
"tokens": 82084,
|
| 627 |
+
"first_record": 9600,
|
| 628 |
+
"last_record": 9727
|
| 629 |
+
},
|
| 630 |
+
{
|
| 631 |
+
"path": "shard_00076.pt",
|
| 632 |
+
"records": 128,
|
| 633 |
+
"tokens": 90913,
|
| 634 |
+
"first_record": 9728,
|
| 635 |
+
"last_record": 9855
|
| 636 |
+
},
|
| 637 |
+
{
|
| 638 |
+
"path": "shard_00077.pt",
|
| 639 |
+
"records": 62,
|
| 640 |
+
"tokens": 40521,
|
| 641 |
+
"first_record": 9856,
|
| 642 |
+
"last_record": 9917
|
| 643 |
+
}
|
| 644 |
+
],
|
| 645 |
+
"requested_records": 9918,
|
| 646 |
+
"source_records": 9918
|
| 647 |
+
}
|
teacher_trajectories/gen_state.chunks27-32.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"chunks_done": 32, "n_chunks": 32, "end_chunk": 32, "samples_per_prompt": 4}
|
teacher_trajectories/generalgen.log
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
104214 prompts, 51 chunks, generating [0, 51)
|
| 2 |
+
104214 prompts, 51 chunks, generating [0, 10)
|
| 3 |
+
chunk 1/10: 3.5M tokens in 1069s
|
teacher_trajectories/generalgen_A.log
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
104214 prompts, 51 chunks, generating [1, 3)
|
| 2 |
+
chunk 2/3: 3.5M tokens in 1418s
|
| 3 |
+
chunk 3/3: 3.5M tokens in 1520s
|
| 4 |
+
TEACHER TRAJECTORIES DONE
|
teacher_trajectories/generalgen_C.log
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
104214 prompts, 51 chunks, generating [5, 7)
|
| 2 |
+
chunk 6/7: 3.4M tokens in 1014s
|
| 3 |
+
chunk 7/7: 3.5M tokens in 1040s
|
| 4 |
+
TEACHER TRAJECTORIES DONE
|
teacher_trajectories/server_general.log
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
teacher_trajectories/server_general_A.log
ADDED
|
@@ -0,0 +1,41 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:339]
|
| 2 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:339] █ █ █▄ ▄█
|
| 3 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:339] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.25.0
|
| 4 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:339] █▄█▀ █ █ █ █ model allenai/OLMoE-1B-7B-0125-Instruct
|
| 5 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:339] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
|
| 6 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:339]
|
| 7 |
+
(APIServer pid=113486) INFO 07-17 07:11:17 [api_utils.py:273] non-default args: {'model_tag': 'allenai/OLMoE-1B-7B-0125-Instruct', 'host': '127.0.0.1', 'port': 8383, 'model': 'allenai/OLMoE-1B-7B-0125-Instruct', 'max_model_len': 2048, 'enforce_eager': True, 'served_model_name': ['student'], 'gpu_memory_utilization': 0.85}
|
| 8 |
+
(APIServer pid=113486) Traceback (most recent call last):
|
| 9 |
+
(APIServer pid=113486) File "<frozen runpy>", line 198, in _run_module_as_main
|
| 10 |
+
(APIServer pid=113486) File "<frozen runpy>", line 88, in _run_code
|
| 11 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/entrypoints/cli/main.py", line 101, in <module>
|
| 12 |
+
(APIServer pid=113486) main()
|
| 13 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/entrypoints/cli/main.py", line 95, in main
|
| 14 |
+
(APIServer pid=113486) args.dispatch_function(args)
|
| 15 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/entrypoints/cli/serve.py", line 148, in cmd
|
| 16 |
+
(APIServer pid=113486) uvloop.run(run_server(args))
|
| 17 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/uvloop/__init__.py", line 96, in run
|
| 18 |
+
(APIServer pid=113486) return __asyncio.run(
|
| 19 |
+
(APIServer pid=113486) ^^^^^^^^^^^^^^
|
| 20 |
+
(APIServer pid=113486) File "/home/henry/.local/share/uv/python/cpython-3.12.12-linux-x86_64-gnu/lib/python3.12/asyncio/runners.py", line 195, in run
|
| 21 |
+
(APIServer pid=113486) return runner.run(main)
|
| 22 |
+
(APIServer pid=113486) ^^^^^^^^^^^^^^^^
|
| 23 |
+
(APIServer pid=113486) File "/home/henry/.local/share/uv/python/cpython-3.12.12-linux-x86_64-gnu/lib/python3.12/asyncio/runners.py", line 118, in run
|
| 24 |
+
(APIServer pid=113486) return self._loop.run_until_complete(task)
|
| 25 |
+
(APIServer pid=113486) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 26 |
+
(APIServer pid=113486) File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
|
| 27 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/uvloop/__init__.py", line 48, in wrapper
|
| 28 |
+
(APIServer pid=113486) return await main
|
| 29 |
+
(APIServer pid=113486) ^^^^^^^^^^
|
| 30 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 697, in run_server
|
| 31 |
+
(APIServer pid=113486) listen_address, sock = setup_server(args, reuse_port=False)
|
| 32 |
+
(APIServer pid=113486) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 33 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/tracing/otel.py", line 178, in sync_wrapper
|
| 34 |
+
(APIServer pid=113486) return func(*args, **kwargs)
|
| 35 |
+
(APIServer pid=113486) ^^^^^^^^^^^^^^^^^^^^^
|
| 36 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 576, in setup_server
|
| 37 |
+
(APIServer pid=113486) sock = create_server_socket(sock_addr, reuse_port=reuse_port)
|
| 38 |
+
(APIServer pid=113486) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
| 39 |
+
(APIServer pid=113486) File "/home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 525, in create_server_socket
|
| 40 |
+
(APIServer pid=113486) sock.bind(addr)
|
| 41 |
+
(APIServer pid=113486) OSError: [Errno 98] Address already in use
|
teacher_trajectories/server_general_C.log
ADDED
|
@@ -0,0 +1,331 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:339]
|
| 2 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:339] █ █ █▄ ▄█
|
| 3 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:339] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.25.0
|
| 4 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:339] █▄█▀ █ █ █ █ model allenai/OLMoE-1B-7B-0125-Instruct
|
| 5 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:339] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
|
| 6 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:339]
|
| 7 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [api_utils.py:273] non-default args: {'model_tag': 'allenai/OLMoE-1B-7B-0125-Instruct', 'host': '127.0.0.1', 'port': 8385, 'model': 'allenai/OLMoE-1B-7B-0125-Instruct', 'max_model_len': 2048, 'enforce_eager': True, 'served_model_name': ['student'], 'gpu_memory_utilization': 0.85}
|
| 8 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [model.py:619] Resolved architecture: OlmoeForCausalLM
|
| 9 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [model.py:1776] Using max model len 2048
|
| 10 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [vllm.py:1042] Asynchronous scheduling is enabled.
|
| 11 |
+
(APIServer pid=114640) WARNING 07-17 07:15:16 [vllm.py:1096] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
|
| 12 |
+
(APIServer pid=114640) WARNING 07-17 07:15:16 [vllm.py:1144] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
|
| 13 |
+
(APIServer pid=114640) INFO 07-17 07:15:16 [kernel.py:292] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['vllm_c', 'native'], fused_add_rms_norm=['vllm_c', 'native'])
|
| 14 |
+
(APIServer pid=114640) INFO 07-17 07:15:17 [vllm.py:1322] Cudagraph is disabled under eager mode
|
| 15 |
+
(APIServer pid=114640) INFO 07-17 07:15:17 [compilation.py:312] Enabled custom fusions: norm_quant, act_quant
|
| 16 |
+
(EngineCore pid=114758) INFO 07-17 07:15:24 [core.py:114] Initializing a V1 LLM engine (v0.25.0) with config: model='allenai/OLMoE-1B-7B-0125-Instruct', speculative_config=None, tokenizer='allenai/OLMoE-1B-7B-0125-Instruct', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=2048, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=False, quantization=None, quantization_config=None, enforce_eager=True, enable_return_routed_experts=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='', reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_metrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=student, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': <CompilationMode.NONE: 0>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['all'], 'ir_enable_torch_wrap': False, 'splitting_ops': [], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': [], 'compile_ranges_endpoints': [2048], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_asserts': False, 'scalar_asserts': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.NONE: 0>, 'cudagraph_num_of_warmups': 0, 'cudagraph_capture_sizes': [], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False}, 'max_cudagraph_capture_size': 0, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['vllm_c', 'native'], fused_add_rms_norm=['vllm_c', 'native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, moe_backend='auto', linear_backend='auto')
|
| 17 |
+
(EngineCore pid=114758) INFO 07-17 07:15:25 [parallel_state.py:1607] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://192.168.0.15:44865 backend=nccl
|
| 18 |
+
(EngineCore pid=114758) INFO 07-17 07:15:25 [parallel_state.py:1942] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank 0, EPLB rank N/A
|
| 19 |
+
(EngineCore pid=114758) INFO 07-17 07:15:26 [topk_topp_sampler.py:55] Using FlashInfer for top-p & top-k sampling.
|
| 20 |
+
(EngineCore pid=114758) INFO 07-17 07:15:26 [gpu_model_runner.py:5209] Starting to load model allenai/OLMoE-1B-7B-0125-Instruct...
|
| 21 |
+
(EngineCore pid=114758) INFO 07-17 07:15:26 [cuda.py:476] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION'].
|
| 22 |
+
(EngineCore pid=114758) INFO 07-17 07:15:26 [flash_attn.py:718] Using FlashAttention version 2
|
| 23 |
+
(EngineCore pid=114758) INFO 07-17 07:15:26 [unquantized.py:262] Using TRITON Unquantized MoE backend out of potential backends: ['FlashInfer TRTLLM', 'FlashInfer CUTLASS', 'TRITON', 'BATCHED_TRITON'].
|
| 24 |
+
(EngineCore pid=114758) INFO 07-17 07:15:27 [weight_utils.py:849] Filesystem type for checkpoints: EXT4. Checkpoint size: 12.89 GiB. Available RAM: 102.39 GiB.
|
| 25 |
+
(EngineCore pid=114758) INFO 07-17 07:15:27 [weight_utils.py:872] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre). If you want to force prefetching, start vLLM with --safetensors-load-strategy=prefetch.
|
| 26 |
+
(EngineCore pid=114758)
|
| 27 |
+
(EngineCore pid=114758)
|
| 28 |
+
(EngineCore pid=114758)
|
| 29 |
+
(EngineCore pid=114758)
|
| 30 |
+
(EngineCore pid=114758)
|
| 31 |
+
(EngineCore pid=114758)
|
| 32 |
+
(EngineCore pid=114758) INFO 07-17 07:15:29 [default_loader.py:430] Loading weights took 1.89 seconds
|
| 33 |
+
(EngineCore pid=114758) INFO 07-17 07:15:29 [unquantized.py:334] Using MoEPrepareAndFinalizeNoDPEPModular
|
| 34 |
+
(EngineCore pid=114758) INFO 07-17 07:15:29 [gpu_model_runner.py:5306] Model loading took 12.89 GiB memory and 2.708411 seconds
|
| 35 |
+
(EngineCore pid=114758) WARNING 07-17 07:15:30 [fused_moe.py:1106] Using default MoE config. Performance might be sub-optimal! Config file not found at /home/henry/Documents/PythonProjects/variable-reap/vllm-plugin/.venv25/lib/python3.12/site-packages/vllm/model_executor/layers/fused_moe/configs/E=64,N=1024,device_name=NVIDIA_GeForce_RTX_3090.json
|
| 36 |
+
(EngineCore pid=114758) INFO 07-17 07:15:31 [gpu_worker.py:538] Available KV cache memory: 6.73 GiB
|
| 37 |
+
(EngineCore pid=114758) INFO 07-17 07:15:31 [kv_cache_utils.py:2146] GPU KV cache size: 55,104 tokens
|
| 38 |
+
(EngineCore pid=114758) INFO 07-17 07:15:31 [kv_cache_utils.py:2147] Maximum concurrency for 2,048 tokens per request: 26.91x
|
| 39 |
+
(EngineCore pid=114758) INFO 07-17 07:15:31 [cutedsl_warmup.py:97] Skipping CuTeDSL warmup because no compile units were requested.
|
| 40 |
+
(EngineCore pid=114758) INFO 07-17 07:15:31 [jit_monitor.py:73] Kernel JIT monitor activated; monitored JIT compilations during inference will use mode=warn.
|
| 41 |
+
(EngineCore pid=114758) INFO 07-17 07:15:31 [core.py:344] init engine (profile, create kv cache, warmup model) took 1.97 s
|
| 42 |
+
(EngineCore pid=114758) INFO 07-17 07:15:32 [vllm.py:1042] Asynchronous scheduling is enabled.
|
| 43 |
+
(EngineCore pid=114758) WARNING 07-17 07:15:32 [vllm.py:1096] Enforce eager set, disabling torch.compile and CUDAGraphs. This is equivalent to setting -cc.mode=none -cc.cudagraph_mode=none
|
| 44 |
+
(EngineCore pid=114758) WARNING 07-17 07:15:32 [vllm.py:1144] Inductor compilation was disabled by user settings, optimizations settings that are only active during inductor compilation will be ignored.
|
| 45 |
+
(EngineCore pid=114758) INFO 07-17 07:15:32 [kernel.py:292] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['vllm_c', 'native'], fused_add_rms_norm=['vllm_c', 'native'])
|
| 46 |
+
(EngineCore pid=114758) INFO 07-17 07:15:32 [vllm.py:1322] Cudagraph is disabled under eager mode
|
| 47 |
+
(EngineCore pid=114758) INFO 07-17 07:15:32 [compilation.py:312] Enabled custom fusions: norm_quant, act_quant
|
| 48 |
+
(APIServer pid=114640) INFO 07-17 07:15:32 [api_server.py:612] Supported tasks: ['generate']
|
| 49 |
+
(APIServer pid=114640) WARNING 07-17 07:15:32 [__init__.py:36] SECURITY WARNING: Development endpoints are enabled! This should NOT be used in production!
|
| 50 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [hf.py:548] Detected the chat template content format to be 'string'. You can set `--chat-template-content-format` to override this.
|
| 51 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [api_server.py:616] Starting vLLM server on http://127.0.0.1:8385
|
| 52 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:37] Available routes are:
|
| 53 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /openapi.json, Methods: HEAD, GET
|
| 54 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /docs, Methods: HEAD, GET
|
| 55 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /docs/oauth2-redirect, Methods: HEAD, GET
|
| 56 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /redoc, Methods: HEAD, GET
|
| 57 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /load, Methods: GET
|
| 58 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /version, Methods: GET
|
| 59 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /health, Methods: GET
|
| 60 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /metrics, Methods: GET
|
| 61 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /tokenize, Methods: POST
|
| 62 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /detokenize, Methods: POST
|
| 63 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/models, Methods: GET
|
| 64 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /ping, Methods: GET
|
| 65 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /ping, Methods: POST
|
| 66 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /invocations, Methods: POST
|
| 67 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /reset_prefix_cache, Methods: POST
|
| 68 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /reset_mm_cache, Methods: POST
|
| 69 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /reset_encoder_cache, Methods: POST
|
| 70 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /pause, Methods: POST
|
| 71 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /resume, Methods: POST
|
| 72 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /is_paused, Methods: GET
|
| 73 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /init_weight_transfer_engine, Methods: POST
|
| 74 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /start_weight_update, Methods: POST
|
| 75 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /update_weights, Methods: POST
|
| 76 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /finish_weight_update, Methods: POST
|
| 77 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /get_world_size, Methods: GET
|
| 78 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /collective_rpc, Methods: POST
|
| 79 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /server_info, Methods: GET
|
| 80 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /sleep, Methods: POST
|
| 81 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /wake_up, Methods: POST
|
| 82 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /is_sleeping, Methods: GET
|
| 83 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/chat/completions, Methods: POST
|
| 84 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/chat/completions/batch, Methods: POST
|
| 85 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/responses, Methods: POST
|
| 86 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/responses/{response_id}, Methods: GET
|
| 87 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/responses/{response_id}/cancel, Methods: POST
|
| 88 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/completions, Methods: POST
|
| 89 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/messages, Methods: POST
|
| 90 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/messages/count_tokens, Methods: POST
|
| 91 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /generative_scoring, Methods: POST
|
| 92 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /scale_elastic_ep, Methods: POST
|
| 93 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /is_scaling_elastic_ep, Methods: POST
|
| 94 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/chat/completions/render, Methods: POST
|
| 95 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/completions/render, Methods: POST
|
| 96 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/chat/completions/derender, Methods: POST
|
| 97 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /v1/completions/derender, Methods: POST
|
| 98 |
+
(APIServer pid=114640) INFO 07-17 07:15:34 [launcher.py:46] Route: /inference/v1/generate, Methods: POST
|
| 99 |
+
(APIServer pid=114640) INFO: Started server process [114640]
|
| 100 |
+
(APIServer pid=114640) INFO: Waiting for application startup.
|
| 101 |
+
(APIServer pid=114640) INFO: Application startup complete.
|
| 102 |
+
(APIServer pid=114640) INFO: 127.0.0.1:34120 - "GET /health HTTP/1.1" 200 OK
|
| 103 |
+
(EngineCore pid=114758) WARNING 07-17 07:15:35 [jit_monitor.py:129] Triton kernel JIT compilation during inference: fused_moe_kernel. This causes a latency spike; consider extending warmup to cover this shape/config.
|
| 104 |
+
(APIServer pid=114640) INFO 07-17 07:15:45 [loggers.py:273] Engine 000: Avg prompt throughput: 1275.7 tokens/s, Avg generation throughput: 3910.1 tokens/s, Running: 217 reqs, Waiting: 7921 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 71.2%
|
| 105 |
+
(APIServer pid=114640) INFO 07-17 07:15:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3688.1 tokens/s, Running: 108 reqs, Waiting: 7956 reqs, GPU KV cache usage: 98.9%, Prefix cache hit rate: 71.2%
|
| 106 |
+
(APIServer pid=114640) INFO 07-17 07:16:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2335.5 tokens/s, Running: 119 reqs, Waiting: 7881 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 71.2%
|
| 107 |
+
(APIServer pid=114640) INFO 07-17 07:16:15 [loggers.py:273] Engine 000: Avg prompt throughput: 1507.4 tokens/s, Avg generation throughput: 4544.8 tokens/s, Running: 245 reqs, Waiting: 7610 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 64.7%
|
| 108 |
+
(APIServer pid=114640) INFO 07-17 07:16:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3832.9 tokens/s, Running: 115 reqs, Waiting: 7654 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 64.7%
|
| 109 |
+
(APIServer pid=114640) INFO 07-17 07:16:35 [loggers.py:273] Engine 000: Avg prompt throughput: 591.7 tokens/s, Avg generation throughput: 3009.1 tokens/s, Running: 167 reqs, Waiting: 7512 reqs, GPU KV cache usage: 98.8%, Prefix cache hit rate: 59.4%
|
| 110 |
+
(APIServer pid=114640) INFO 07-17 07:16:45 [loggers.py:273] Engine 000: Avg prompt throughput: 534.0 tokens/s, Avg generation throughput: 3807.8 tokens/s, Running: 211 reqs, Waiting: 7394 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.1%
|
| 111 |
+
(APIServer pid=114640) INFO 07-17 07:16:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3239.3 tokens/s, Running: 98 reqs, Waiting: 7448 reqs, GPU KV cache usage: 99.5%, Prefix cache hit rate: 60.1%
|
| 112 |
+
(APIServer pid=114640) INFO 07-17 07:17:05 [loggers.py:273] Engine 000: Avg prompt throughput: 953.8 tokens/s, Avg generation throughput: 3089.5 tokens/s, Running: 256 reqs, Waiting: 7187 reqs, GPU KV cache usage: 96.5%, Prefix cache hit rate: 56.9%
|
| 113 |
+
(APIServer pid=114640) INFO 07-17 07:17:15 [loggers.py:273] Engine 000: Avg prompt throughput: 282.1 tokens/s, Avg generation throughput: 4527.6 tokens/s, Running: 135 reqs, Waiting: 7214 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 54.5%
|
| 114 |
+
(APIServer pid=114640) INFO 07-17 07:17:25 [loggers.py:273] Engine 000: Avg prompt throughput: 37.9 tokens/s, Avg generation throughput: 2899.9 tokens/s, Running: 154 reqs, Waiting: 7112 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 53.9%
|
| 115 |
+
(APIServer pid=114640) INFO 07-17 07:17:35 [loggers.py:273] Engine 000: Avg prompt throughput: 746.4 tokens/s, Avg generation throughput: 3528.4 tokens/s, Running: 142 reqs, Waiting: 7028 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 54.4%
|
| 116 |
+
(APIServer pid=114640) INFO 07-17 07:17:45 [loggers.py:273] Engine 000: Avg prompt throughput: 594.7 tokens/s, Avg generation throughput: 3840.1 tokens/s, Running: 137 reqs, Waiting: 6933 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 53.4%
|
| 117 |
+
(APIServer pid=114640) INFO 07-17 07:17:55 [loggers.py:273] Engine 000: Avg prompt throughput: 233.3 tokens/s, Avg generation throughput: 3001.7 tokens/s, Running: 143 reqs, Waiting: 6844 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 52.7%
|
| 118 |
+
(APIServer pid=114640) INFO 07-17 07:18:05 [loggers.py:273] Engine 000: Avg prompt throughput: 488.8 tokens/s, Avg generation throughput: 3381.1 tokens/s, Running: 136 reqs, Waiting: 6760 reqs, GPU KV cache usage: 99.5%, Prefix cache hit rate: 51.0%
|
| 119 |
+
(APIServer pid=114640) INFO 07-17 07:18:15 [loggers.py:273] Engine 000: Avg prompt throughput: 619.5 tokens/s, Avg generation throughput: 3265.0 tokens/s, Running: 121 reqs, Waiting: 6698 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 52.6%
|
| 120 |
+
(APIServer pid=114640) INFO 07-17 07:18:25 [loggers.py:273] Engine 000: Avg prompt throughput: 487.6 tokens/s, Avg generation throughput: 3126.9 tokens/s, Running: 163 reqs, Waiting: 6576 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 50.5%
|
| 121 |
+
(APIServer pid=114640) INFO 07-17 07:18:35 [loggers.py:273] Engine 000: Avg prompt throughput: 583.6 tokens/s, Avg generation throughput: 3508.0 tokens/s, Running: 159 reqs, Waiting: 6471 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 52.7%
|
| 122 |
+
(APIServer pid=114640) INFO 07-17 07:18:45 [loggers.py:273] Engine 000: Avg prompt throughput: 512.7 tokens/s, Avg generation throughput: 3249.9 tokens/s, Running: 221 reqs, Waiting: 6335 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 55.3%
|
| 123 |
+
(APIServer pid=114640) INFO 07-17 07:18:55 [loggers.py:273] Engine 000: Avg prompt throughput: 79.6 tokens/s, Avg generation throughput: 3715.4 tokens/s, Running: 120 reqs, Waiting: 6354 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 55.3%
|
| 124 |
+
(APIServer pid=114640) INFO 07-17 07:19:05 [loggers.py:273] Engine 000: Avg prompt throughput: 595.6 tokens/s, Avg generation throughput: 2819.9 tokens/s, Running: 187 reqs, Waiting: 6216 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 56.8%
|
| 125 |
+
(APIServer pid=114640) INFO 07-17 07:19:15 [loggers.py:273] Engine 000: Avg prompt throughput: 242.2 tokens/s, Avg generation throughput: 3617.6 tokens/s, Running: 182 reqs, Waiting: 6140 reqs, GPU KV cache usage: 97.9%, Prefix cache hit rate: 53.6%
|
| 126 |
+
(APIServer pid=114640) INFO 07-17 07:19:25 [loggers.py:273] Engine 000: Avg prompt throughput: 482.4 tokens/s, Avg generation throughput: 3606.4 tokens/s, Running: 139 reqs, Waiting: 6106 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 53.4%
|
| 127 |
+
(APIServer pid=114640) INFO 07-17 07:19:35 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2646.6 tokens/s, Running: 112 reqs, Waiting: 6080 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 53.4%
|
| 128 |
+
(APIServer pid=114640) INFO 07-17 07:19:45 [loggers.py:273] Engine 000: Avg prompt throughput: 941.6 tokens/s, Avg generation throughput: 4357.0 tokens/s, Running: 176 reqs, Waiting: 5897 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 55.1%
|
| 129 |
+
(APIServer pid=114640) INFO 07-17 07:19:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3357.2 tokens/s, Running: 114 reqs, Waiting: 5888 reqs, GPU KV cache usage: 99.0%, Prefix cache hit rate: 55.1%
|
| 130 |
+
(APIServer pid=114640) INFO 07-17 07:20:05 [loggers.py:273] Engine 000: Avg prompt throughput: 417.1 tokens/s, Avg generation throughput: 3118.7 tokens/s, Running: 154 reqs, Waiting: 5768 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 56.9%
|
| 131 |
+
(APIServer pid=114640) INFO 07-17 07:20:15 [loggers.py:273] Engine 000: Avg prompt throughput: 918.0 tokens/s, Avg generation throughput: 4118.9 tokens/s, Running: 249 reqs, Waiting: 5560 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 60.5%
|
| 132 |
+
(APIServer pid=114640) INFO 07-17 07:20:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3615.5 tokens/s, Running: 110 reqs, Waiting: 5639 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 60.5%
|
| 133 |
+
(APIServer pid=114640) INFO 07-17 07:20:35 [loggers.py:273] Engine 000: Avg prompt throughput: 476.6 tokens/s, Avg generation throughput: 2807.2 tokens/s, Running: 167 reqs, Waiting: 5496 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 60.5%
|
| 134 |
+
(APIServer pid=114640) INFO 07-17 07:20:45 [loggers.py:273] Engine 000: Avg prompt throughput: 398.8 tokens/s, Avg generation throughput: 3556.8 tokens/s, Running: 136 reqs, Waiting: 5449 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.1%
|
| 135 |
+
(APIServer pid=114640) INFO 07-17 07:20:55 [loggers.py:273] Engine 000: Avg prompt throughput: 268.0 tokens/s, Avg generation throughput: 3118.2 tokens/s, Running: 101 reqs, Waiting: 5414 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 60.1%
|
| 136 |
+
(APIServer pid=114640) INFO 07-17 07:21:05 [loggers.py:273] Engine 000: Avg prompt throughput: 415.6 tokens/s, Avg generation throughput: 3015.9 tokens/s, Running: 137 reqs, Waiting: 5304 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.5%
|
| 137 |
+
(APIServer pid=114640) INFO 07-17 07:21:15 [loggers.py:273] Engine 000: Avg prompt throughput: 597.2 tokens/s, Avg generation throughput: 3774.0 tokens/s, Running: 151 reqs, Waiting: 5187 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 63.5%
|
| 138 |
+
(APIServer pid=114640) INFO 07-17 07:21:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2962.1 tokens/s, Running: 111 reqs, Waiting: 5165 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 63.5%
|
| 139 |
+
(APIServer pid=114640) INFO 07-17 07:21:35 [loggers.py:273] Engine 000: Avg prompt throughput: 733.1 tokens/s, Avg generation throughput: 2981.7 tokens/s, Running: 220 reqs, Waiting: 4980 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 62.7%
|
| 140 |
+
(APIServer pid=114640) INFO 07-17 07:21:45 [loggers.py:273] Engine 000: Avg prompt throughput: 436.0 tokens/s, Avg generation throughput: 4018.3 tokens/s, Running: 149 reqs, Waiting: 4981 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 62.7%
|
| 141 |
+
(APIServer pid=114640) INFO 07-17 07:21:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2802.2 tokens/s, Running: 95 reqs, Waiting: 4983 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 62.7%
|
| 142 |
+
(APIServer pid=114640) INFO 07-17 07:22:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2363.5 tokens/s, Running: 130 reqs, Waiting: 4900 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 62.7%
|
| 143 |
+
(APIServer pid=114640) INFO 07-17 07:22:15 [loggers.py:273] Engine 000: Avg prompt throughput: 1068.0 tokens/s, Avg generation throughput: 4933.2 tokens/s, Running: 168 reqs, Waiting: 4732 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 63.4%
|
| 144 |
+
(APIServer pid=114640) INFO 07-17 07:22:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2989.7 tokens/s, Running: 106 reqs, Waiting: 4734 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 63.4%
|
| 145 |
+
(APIServer pid=114640) INFO 07-17 07:22:35 [loggers.py:273] Engine 000: Avg prompt throughput: 166.4 tokens/s, Avg generation throughput: 2422.3 tokens/s, Running: 123 reqs, Waiting: 4660 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 62.2%
|
| 146 |
+
(APIServer pid=114640) INFO 07-17 07:22:45 [loggers.py:273] Engine 000: Avg prompt throughput: 1179.2 tokens/s, Avg generation throughput: 4664.0 tokens/s, Running: 215 reqs, Waiting: 4454 reqs, GPU KV cache usage: 99.4%, Prefix cache hit rate: 62.0%
|
| 147 |
+
(APIServer pid=114640) INFO 07-17 07:22:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3607.0 tokens/s, Running: 106 reqs, Waiting: 4504 reqs, GPU KV cache usage: 99.0%, Prefix cache hit rate: 62.0%
|
| 148 |
+
(APIServer pid=114640) INFO 07-17 07:23:05 [loggers.py:273] Engine 000: Avg prompt throughput: 288.8 tokens/s, Avg generation throughput: 2537.3 tokens/s, Running: 142 reqs, Waiting: 4388 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.2%
|
| 149 |
+
(APIServer pid=114640) INFO 07-17 07:23:15 [loggers.py:273] Engine 000: Avg prompt throughput: 867.6 tokens/s, Avg generation throughput: 3923.2 tokens/s, Running: 233 reqs, Waiting: 4195 reqs, GPU KV cache usage: 99.5%, Prefix cache hit rate: 63.7%
|
| 150 |
+
(APIServer pid=114640) INFO 07-17 07:23:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3591.1 tokens/s, Running: 129 reqs, Waiting: 4232 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 63.7%
|
| 151 |
+
(APIServer pid=114640) INFO 07-17 07:23:35 [loggers.py:273] Engine 000: Avg prompt throughput: 199.7 tokens/s, Avg generation throughput: 3147.1 tokens/s, Running: 116 reqs, Waiting: 4165 reqs, GPU KV cache usage: 99.1%, Prefix cache hit rate: 59.8%
|
| 152 |
+
(APIServer pid=114640) INFO 07-17 07:23:45 [loggers.py:273] Engine 000: Avg prompt throughput: 835.1 tokens/s, Avg generation throughput: 3413.0 tokens/s, Running: 180 reqs, Waiting: 4000 reqs, GPU KV cache usage: 99.5%, Prefix cache hit rate: 61.2%
|
| 153 |
+
(APIServer pid=114640) INFO 07-17 07:23:55 [loggers.py:273] Engine 000: Avg prompt throughput: 405.6 tokens/s, Avg generation throughput: 3850.2 tokens/s, Running: 136 reqs, Waiting: 3964 reqs, GPU KV cache usage: 98.3%, Prefix cache hit rate: 60.7%
|
| 154 |
+
(APIServer pid=114640) INFO 07-17 07:24:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2786.0 tokens/s, Running: 97 reqs, Waiting: 3953 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 60.7%
|
| 155 |
+
(APIServer pid=114640) INFO 07-17 07:24:15 [loggers.py:273] Engine 000: Avg prompt throughput: 903.9 tokens/s, Avg generation throughput: 2835.5 tokens/s, Running: 218 reqs, Waiting: 3760 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 59.0%
|
| 156 |
+
(APIServer pid=114640) INFO 07-17 07:24:25 [loggers.py:273] Engine 000: Avg prompt throughput: 316.4 tokens/s, Avg generation throughput: 4077.5 tokens/s, Running: 145 reqs, Waiting: 3758 reqs, GPU KV cache usage: 99.5%, Prefix cache hit rate: 59.1%
|
| 157 |
+
(APIServer pid=114640) INFO 07-17 07:24:35 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2766.5 tokens/s, Running: 115 reqs, Waiting: 3721 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 59.1%
|
| 158 |
+
(APIServer pid=114640) INFO 07-17 07:24:45 [loggers.py:273] Engine 000: Avg prompt throughput: 281.3 tokens/s, Avg generation throughput: 2714.4 tokens/s, Running: 189 reqs, Waiting: 3576 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 59.2%
|
| 159 |
+
(APIServer pid=114640) INFO 07-17 07:24:55 [loggers.py:273] Engine 000: Avg prompt throughput: 928.8 tokens/s, Avg generation throughput: 4746.0 tokens/s, Running: 184 reqs, Waiting: 3456 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 59.6%
|
| 160 |
+
(APIServer pid=114640) INFO 07-17 07:25:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3150.9 tokens/s, Running: 128 reqs, Waiting: 3433 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.6%
|
| 161 |
+
(APIServer pid=114640) INFO 07-17 07:25:15 [loggers.py:273] Engine 000: Avg prompt throughput: 686.9 tokens/s, Avg generation throughput: 2787.5 tokens/s, Running: 191 reqs, Waiting: 3288 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 57.9%
|
| 162 |
+
(APIServer pid=114640) INFO 07-17 07:25:25 [loggers.py:273] Engine 000: Avg prompt throughput: 579.2 tokens/s, Avg generation throughput: 4740.4 tokens/s, Running: 219 reqs, Waiting: 3147 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 61.5%
|
| 163 |
+
(APIServer pid=114640) INFO 07-17 07:25:35 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3331.9 tokens/s, Running: 110 reqs, Waiting: 3202 reqs, GPU KV cache usage: 99.4%, Prefix cache hit rate: 61.5%
|
| 164 |
+
(APIServer pid=114640) INFO 07-17 07:25:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2407.5 tokens/s, Running: 92 reqs, Waiting: 3170 reqs, GPU KV cache usage: 98.8%, Prefix cache hit rate: 61.5%
|
| 165 |
+
(APIServer pid=114640) INFO 07-17 07:25:55 [loggers.py:273] Engine 000: Avg prompt throughput: 1099.5 tokens/s, Avg generation throughput: 4171.3 tokens/s, Running: 213 reqs, Waiting: 2952 reqs, GPU KV cache usage: 97.8%, Prefix cache hit rate: 63.6%
|
| 166 |
+
(APIServer pid=114640) INFO 07-17 07:26:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3499.0 tokens/s, Running: 116 reqs, Waiting: 2998 reqs, GPU KV cache usage: 99.4%, Prefix cache hit rate: 63.6%
|
| 167 |
+
(APIServer pid=114640) INFO 07-17 07:26:15 [loggers.py:273] Engine 000: Avg prompt throughput: 116.8 tokens/s, Avg generation throughput: 2488.9 tokens/s, Running: 143 reqs, Waiting: 2894 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 62.8%
|
| 168 |
+
(APIServer pid=114640) INFO 07-17 07:26:25 [loggers.py:273] Engine 000: Avg prompt throughput: 999.2 tokens/s, Avg generation throughput: 3831.9 tokens/s, Running: 254 reqs, Waiting: 2667 reqs, GPU KV cache usage: 90.7%, Prefix cache hit rate: 63.5%
|
| 169 |
+
(APIServer pid=114640) INFO 07-17 07:26:35 [loggers.py:273] Engine 000: Avg prompt throughput: 169.6 tokens/s, Avg generation throughput: 4115.8 tokens/s, Running: 120 reqs, Waiting: 2714 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 63.8%
|
| 170 |
+
(APIServer pid=114640) INFO 07-17 07:26:45 [loggers.py:273] Engine 000: Avg prompt throughput: 249.8 tokens/s, Avg generation throughput: 2590.2 tokens/s, Running: 160 reqs, Waiting: 2588 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 63.3%
|
| 171 |
+
(APIServer pid=114640) INFO 07-17 07:26:55 [loggers.py:273] Engine 000: Avg prompt throughput: 1049.3 tokens/s, Avg generation throughput: 3741.0 tokens/s, Running: 211 reqs, Waiting: 2440 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 63.3%
|
| 172 |
+
(APIServer pid=114640) INFO 07-17 07:27:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3279.2 tokens/s, Running: 109 reqs, Waiting: 2480 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 63.3%
|
| 173 |
+
(APIServer pid=114640) INFO 07-17 07:27:15 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2394.5 tokens/s, Running: 102 reqs, Waiting: 2436 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 63.3%
|
| 174 |
+
(APIServer pid=114640) INFO 07-17 07:27:25 [loggers.py:273] Engine 000: Avg prompt throughput: 1214.8 tokens/s, Avg generation throughput: 3507.5 tokens/s, Running: 222 reqs, Waiting: 2216 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 63.3%
|
| 175 |
+
(APIServer pid=114640) INFO 07-17 07:27:35 [loggers.py:273] Engine 000: Avg prompt throughput: 292.0 tokens/s, Avg generation throughput: 4258.7 tokens/s, Running: 143 reqs, Waiting: 2205 reqs, GPU KV cache usage: 98.9%, Prefix cache hit rate: 64.8%
|
| 176 |
+
(APIServer pid=114640) INFO 07-17 07:27:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2717.3 tokens/s, Running: 124 reqs, Waiting: 2148 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 64.8%
|
| 177 |
+
(APIServer pid=114640) INFO 07-17 07:27:55 [loggers.py:273] Engine 000: Avg prompt throughput: 582.8 tokens/s, Avg generation throughput: 2965.9 tokens/s, Running: 158 reqs, Waiting: 2040 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 63.0%
|
| 178 |
+
(APIServer pid=114640) INFO 07-17 07:28:05 [loggers.py:273] Engine 000: Avg prompt throughput: 620.1 tokens/s, Avg generation throughput: 4109.2 tokens/s, Running: 178 reqs, Waiting: 1929 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.2%
|
| 179 |
+
(APIServer pid=114640) INFO 07-17 07:28:15 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3079.7 tokens/s, Running: 114 reqs, Waiting: 1931 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.2%
|
| 180 |
+
(APIServer pid=114640) INFO 07-17 07:28:25 [loggers.py:273] Engine 000: Avg prompt throughput: 547.3 tokens/s, Avg generation throughput: 3258.1 tokens/s, Running: 152 reqs, Waiting: 1805 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 61.9%
|
| 181 |
+
(APIServer pid=114640) INFO 07-17 07:28:35 [loggers.py:273] Engine 000: Avg prompt throughput: 501.2 tokens/s, Avg generation throughput: 3917.4 tokens/s, Running: 174 reqs, Waiting: 1699 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 63.8%
|
| 182 |
+
(APIServer pid=114640) INFO 07-17 07:28:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3086.8 tokens/s, Running: 110 reqs, Waiting: 1699 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 63.8%
|
| 183 |
+
(APIServer pid=114640) INFO 07-17 07:28:55 [loggers.py:273] Engine 000: Avg prompt throughput: 603.5 tokens/s, Avg generation throughput: 2933.5 tokens/s, Running: 180 reqs, Waiting: 1555 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 64.0%
|
| 184 |
+
(APIServer pid=114640) INFO 07-17 07:29:05 [loggers.py:273] Engine 000: Avg prompt throughput: 157.6 tokens/s, Avg generation throughput: 3746.9 tokens/s, Running: 175 reqs, Waiting: 1479 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.3%
|
| 185 |
+
(APIServer pid=114640) INFO 07-17 07:29:15 [loggers.py:273] Engine 000: Avg prompt throughput: 366.8 tokens/s, Avg generation throughput: 3153.3 tokens/s, Running: 156 reqs, Waiting: 1416 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 58.5%
|
| 186 |
+
(APIServer pid=114640) INFO 07-17 07:29:25 [loggers.py:273] Engine 000: Avg prompt throughput: 268.4 tokens/s, Avg generation throughput: 3149.1 tokens/s, Running: 130 reqs, Waiting: 1376 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 57.7%
|
| 187 |
+
(APIServer pid=114640) INFO 07-17 07:29:35 [loggers.py:273] Engine 000: Avg prompt throughput: 872.6 tokens/s, Avg generation throughput: 4096.3 tokens/s, Running: 179 reqs, Waiting: 1212 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 58.6%
|
| 188 |
+
(APIServer pid=114640) INFO 07-17 07:29:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3091.5 tokens/s, Running: 123 reqs, Waiting: 1192 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.6%
|
| 189 |
+
(APIServer pid=114640) INFO 07-17 07:29:55 [loggers.py:273] Engine 000: Avg prompt throughput: 883.5 tokens/s, Avg generation throughput: 3621.3 tokens/s, Running: 162 reqs, Waiting: 1040 reqs, GPU KV cache usage: 97.2%, Prefix cache hit rate: 56.1%
|
| 190 |
+
(APIServer pid=114640) INFO 07-17 07:30:05 [loggers.py:273] Engine 000: Avg prompt throughput: 36.4 tokens/s, Avg generation throughput: 3044.9 tokens/s, Running: 131 reqs, Waiting: 1000 reqs, GPU KV cache usage: 96.2%, Prefix cache hit rate: 56.2%
|
| 191 |
+
(APIServer pid=114640) INFO 07-17 07:30:15 [loggers.py:273] Engine 000: Avg prompt throughput: 798.0 tokens/s, Avg generation throughput: 3699.6 tokens/s, Running: 123 reqs, Waiting: 911 reqs, GPU KV cache usage: 98.4%, Prefix cache hit rate: 57.7%
|
| 192 |
+
(APIServer pid=114640) INFO 07-17 07:30:25 [loggers.py:273] Engine 000: Avg prompt throughput: 598.9 tokens/s, Avg generation throughput: 2895.0 tokens/s, Running: 224 reqs, Waiting: 728 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 57.3%
|
| 193 |
+
(APIServer pid=114640) INFO 07-17 07:30:35 [loggers.py:273] Engine 000: Avg prompt throughput: 123.8 tokens/s, Avg generation throughput: 4034.0 tokens/s, Running: 139 reqs, Waiting: 718 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 57.5%
|
| 194 |
+
(APIServer pid=114640) INFO 07-17 07:30:45 [loggers.py:273] Engine 000: Avg prompt throughput: 166.8 tokens/s, Avg generation throughput: 2897.7 tokens/s, Running: 116 reqs, Waiting: 676 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 57.1%
|
| 195 |
+
(APIServer pid=114640) INFO 07-17 07:30:55 [loggers.py:273] Engine 000: Avg prompt throughput: 381.2 tokens/s, Avg generation throughput: 3042.8 tokens/s, Running: 186 reqs, Waiting: 538 reqs, GPU KV cache usage: 98.3%, Prefix cache hit rate: 61.2%
|
| 196 |
+
(APIServer pid=114640) INFO 07-17 07:31:05 [loggers.py:273] Engine 000: Avg prompt throughput: 851.9 tokens/s, Avg generation throughput: 4313.0 tokens/s, Running: 178 reqs, Waiting: 448 reqs, GPU KV cache usage: 99.4%, Prefix cache hit rate: 62.3%
|
| 197 |
+
(APIServer pid=114640) INFO 07-17 07:31:15 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3098.5 tokens/s, Running: 106 reqs, Waiting: 462 reqs, GPU KV cache usage: 98.9%, Prefix cache hit rate: 62.3%
|
| 198 |
+
(APIServer pid=114640) INFO 07-17 07:31:25 [loggers.py:273] Engine 000: Avg prompt throughput: 218.0 tokens/s, Avg generation throughput: 2617.5 tokens/s, Running: 187 reqs, Waiting: 307 reqs, GPU KV cache usage: 97.6%, Prefix cache hit rate: 59.7%
|
| 199 |
+
(APIServer pid=114640) INFO 07-17 07:31:35 [loggers.py:273] Engine 000: Avg prompt throughput: 846.7 tokens/s, Avg generation throughput: 3900.3 tokens/s, Running: 215 reqs, Waiting: 188 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 60.3%
|
| 200 |
+
(APIServer pid=114640) INFO 07-17 07:31:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3257.6 tokens/s, Running: 128 reqs, Waiting: 199 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.3%
|
| 201 |
+
(APIServer pid=114640) INFO 07-17 07:31:55 [loggers.py:273] Engine 000: Avg prompt throughput: 223.2 tokens/s, Avg generation throughput: 2874.4 tokens/s, Running: 99 reqs, Waiting: 174 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 60.2%
|
| 202 |
+
(APIServer pid=114640) INFO 07-17 07:32:05 [loggers.py:273] Engine 000: Avg prompt throughput: 617.1 tokens/s, Avg generation throughput: 3714.9 tokens/s, Running: 173 reqs, Waiting: 0 reqs, GPU KV cache usage: 89.9%, Prefix cache hit rate: 60.3%
|
| 203 |
+
(APIServer pid=114640) INFO 07-17 07:32:15 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3560.9 tokens/s, Running: 111 reqs, Waiting: 0 reqs, GPU KV cache usage: 96.3%, Prefix cache hit rate: 60.3%
|
| 204 |
+
(APIServer pid=114640) INFO 07-17 07:32:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2281.9 tokens/s, Running: 38 reqs, Waiting: 0 reqs, GPU KV cache usage: 54.9%, Prefix cache hit rate: 60.3%
|
| 205 |
+
(APIServer pid=114640) INFO: 127.0.0.1:34130 - "POST /v1/completions HTTP/1.1" 200 OK
|
| 206 |
+
(APIServer pid=114640) INFO 07-17 07:32:35 [loggers.py:273] Engine 000: Avg prompt throughput: 1423.7 tokens/s, Avg generation throughput: 2762.8 tokens/s, Running: 256 reqs, Waiting: 7893 reqs, GPU KV cache usage: 70.7%, Prefix cache hit rate: 61.7%
|
| 207 |
+
(APIServer pid=114640) INFO 07-17 07:32:45 [loggers.py:273] Engine 000: Avg prompt throughput: 82.6 tokens/s, Avg generation throughput: 4682.5 tokens/s, Running: 138 reqs, Waiting: 7961 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 62.4%
|
| 208 |
+
(APIServer pid=114640) INFO 07-17 07:32:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2606.8 tokens/s, Running: 88 reqs, Waiting: 7955 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 62.4%
|
| 209 |
+
(APIServer pid=114640) INFO 07-17 07:33:05 [loggers.py:273] Engine 000: Avg prompt throughput: 900.2 tokens/s, Avg generation throughput: 2589.9 tokens/s, Running: 256 reqs, Waiting: 7686 reqs, GPU KV cache usage: 83.6%, Prefix cache hit rate: 63.4%
|
| 210 |
+
(APIServer pid=114640) INFO 07-17 07:33:15 [loggers.py:273] Engine 000: Avg prompt throughput: 289.2 tokens/s, Avg generation throughput: 4322.5 tokens/s, Running: 144 reqs, Waiting: 7710 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 63.5%
|
| 211 |
+
(APIServer pid=114640) INFO 07-17 07:33:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2838.5 tokens/s, Running: 106 reqs, Waiting: 7679 reqs, GPU KV cache usage: 99.0%, Prefix cache hit rate: 63.5%
|
| 212 |
+
(APIServer pid=114640) INFO 07-17 07:33:35 [loggers.py:273] Engine 000: Avg prompt throughput: 625.0 tokens/s, Avg generation throughput: 2942.5 tokens/s, Running: 154 reqs, Waiting: 7556 reqs, GPU KV cache usage: 97.7%, Prefix cache hit rate: 61.5%
|
| 213 |
+
(APIServer pid=114640) INFO 07-17 07:33:45 [loggers.py:273] Engine 000: Avg prompt throughput: 932.3 tokens/s, Avg generation throughput: 4427.9 tokens/s, Running: 187 reqs, Waiting: 7402 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 62.0%
|
| 214 |
+
(APIServer pid=114640) INFO 07-17 07:33:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3064.1 tokens/s, Running: 96 reqs, Waiting: 7435 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 62.0%
|
| 215 |
+
(APIServer pid=114640) INFO 07-17 07:34:05 [loggers.py:273] Engine 000: Avg prompt throughput: 274.4 tokens/s, Avg generation throughput: 2745.0 tokens/s, Running: 176 reqs, Waiting: 7288 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 61.8%
|
| 216 |
+
(APIServer pid=114640) INFO 07-17 07:34:15 [loggers.py:273] Engine 000: Avg prompt throughput: 940.8 tokens/s, Avg generation throughput: 3966.3 tokens/s, Running: 256 reqs, Waiting: 7103 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.3%
|
| 217 |
+
(APIServer pid=114640) INFO 07-17 07:34:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3596.1 tokens/s, Running: 105 reqs, Waiting: 7202 reqs, GPU KV cache usage: 98.6%, Prefix cache hit rate: 60.3%
|
| 218 |
+
(APIServer pid=114640) INFO 07-17 07:34:35 [loggers.py:273] Engine 000: Avg prompt throughput: 2.8 tokens/s, Avg generation throughput: 2700.2 tokens/s, Running: 117 reqs, Waiting: 7123 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.5%
|
| 219 |
+
(APIServer pid=114640) INFO 07-17 07:34:45 [loggers.py:273] Engine 000: Avg prompt throughput: 860.2 tokens/s, Avg generation throughput: 3683.0 tokens/s, Running: 177 reqs, Waiting: 6962 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.8%
|
| 220 |
+
(APIServer pid=114640) INFO 07-17 07:34:55 [loggers.py:273] Engine 000: Avg prompt throughput: 243.6 tokens/s, Avg generation throughput: 3623.1 tokens/s, Running: 128 reqs, Waiting: 6924 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.3%
|
| 221 |
+
(APIServer pid=114640) INFO 07-17 07:35:05 [loggers.py:273] Engine 000: Avg prompt throughput: 296.4 tokens/s, Avg generation throughput: 3103.7 tokens/s, Running: 156 reqs, Waiting: 6832 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 56.9%
|
| 222 |
+
(APIServer pid=114640) INFO 07-17 07:35:15 [loggers.py:273] Engine 000: Avg prompt throughput: 248.2 tokens/s, Avg generation throughput: 3037.3 tokens/s, Running: 144 reqs, Waiting: 6772 reqs, GPU KV cache usage: 97.2%, Prefix cache hit rate: 56.7%
|
| 223 |
+
(APIServer pid=114640) INFO 07-17 07:35:25 [loggers.py:273] Engine 000: Avg prompt throughput: 536.8 tokens/s, Avg generation throughput: 4252.9 tokens/s, Running: 156 reqs, Waiting: 6668 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 64.2%
|
| 224 |
+
(APIServer pid=114640) INFO 07-17 07:35:35 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2873.1 tokens/s, Running: 95 reqs, Waiting: 6675 reqs, GPU KV cache usage: 98.1%, Prefix cache hit rate: 64.2%
|
| 225 |
+
(APIServer pid=114640) INFO 07-17 07:35:45 [loggers.py:273] Engine 000: Avg prompt throughput: 543.7 tokens/s, Avg generation throughput: 2632.3 tokens/s, Running: 176 reqs, Waiting: 6524 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 61.1%
|
| 226 |
+
(APIServer pid=114640) INFO 07-17 07:35:55 [loggers.py:273] Engine 000: Avg prompt throughput: 717.7 tokens/s, Avg generation throughput: 4454.2 tokens/s, Running: 187 reqs, Waiting: 6423 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 61.3%
|
| 227 |
+
(APIServer pid=114640) INFO 07-17 07:36:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3197.0 tokens/s, Running: 98 reqs, Waiting: 6465 reqs, GPU KV cache usage: 98.8%, Prefix cache hit rate: 61.3%
|
| 228 |
+
(APIServer pid=114640) INFO 07-17 07:36:15 [loggers.py:273] Engine 000: Avg prompt throughput: 165.1 tokens/s, Avg generation throughput: 2319.8 tokens/s, Running: 175 reqs, Waiting: 6325 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 61.3%
|
| 229 |
+
(APIServer pid=114640) INFO 07-17 07:36:25 [loggers.py:273] Engine 000: Avg prompt throughput: 771.1 tokens/s, Avg generation throughput: 4011.8 tokens/s, Running: 199 reqs, Waiting: 6216 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.5%
|
| 230 |
+
(APIServer pid=114640) INFO 07-17 07:36:35 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3133.8 tokens/s, Running: 100 reqs, Waiting: 6256 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 58.5%
|
| 231 |
+
(APIServer pid=114640) INFO 07-17 07:36:45 [loggers.py:273] Engine 000: Avg prompt throughput: 543.0 tokens/s, Avg generation throughput: 2986.8 tokens/s, Running: 211 reqs, Waiting: 6068 reqs, GPU KV cache usage: 98.1%, Prefix cache hit rate: 58.1%
|
| 232 |
+
(APIServer pid=114640) INFO 07-17 07:36:55 [loggers.py:273] Engine 000: Avg prompt throughput: 208.9 tokens/s, Avg generation throughput: 3864.9 tokens/s, Running: 206 reqs, Waiting: 5996 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.1%
|
| 233 |
+
(APIServer pid=114640) INFO 07-17 07:37:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3222.9 tokens/s, Running: 122 reqs, Waiting: 6009 reqs, GPU KV cache usage: 98.8%, Prefix cache hit rate: 58.1%
|
| 234 |
+
(APIServer pid=114640) INFO 07-17 07:37:15 [loggers.py:273] Engine 000: Avg prompt throughput: 604.3 tokens/s, Avg generation throughput: 3260.4 tokens/s, Running: 161 reqs, Waiting: 5880 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.1%
|
| 235 |
+
(APIServer pid=114640) INFO 07-17 07:37:25 [loggers.py:273] Engine 000: Avg prompt throughput: 609.6 tokens/s, Avg generation throughput: 4257.2 tokens/s, Running: 171 reqs, Waiting: 5748 reqs, GPU KV cache usage: 98.4%, Prefix cache hit rate: 59.5%
|
| 236 |
+
(APIServer pid=114640) INFO 07-17 07:37:35 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3110.2 tokens/s, Running: 105 reqs, Waiting: 5752 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 59.5%
|
| 237 |
+
(APIServer pid=114640) INFO 07-17 07:37:45 [loggers.py:273] Engine 000: Avg prompt throughput: 745.0 tokens/s, Avg generation throughput: 3044.5 tokens/s, Running: 227 reqs, Waiting: 5540 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.6%
|
| 238 |
+
(APIServer pid=114640) INFO 07-17 07:37:55 [loggers.py:273] Engine 000: Avg prompt throughput: 589.8 tokens/s, Avg generation throughput: 4258.3 tokens/s, Running: 209 reqs, Waiting: 5440 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 59.7%
|
| 239 |
+
(APIServer pid=114640) INFO 07-17 07:38:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3372.4 tokens/s, Running: 132 reqs, Waiting: 5428 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.7%
|
| 240 |
+
(APIServer pid=114640) INFO 07-17 07:38:15 [loggers.py:273] Engine 000: Avg prompt throughput: 809.5 tokens/s, Avg generation throughput: 3682.6 tokens/s, Running: 149 reqs, Waiting: 5309 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.5%
|
| 241 |
+
(APIServer pid=114640) INFO 07-17 07:38:25 [loggers.py:273] Engine 000: Avg prompt throughput: 364.4 tokens/s, Avg generation throughput: 3714.3 tokens/s, Running: 138 reqs, Waiting: 5232 reqs, GPU KV cache usage: 99.3%, Prefix cache hit rate: 58.8%
|
| 242 |
+
(APIServer pid=114640) INFO 07-17 07:38:35 [loggers.py:273] Engine 000: Avg prompt throughput: 147.2 tokens/s, Avg generation throughput: 3095.5 tokens/s, Running: 155 reqs, Waiting: 5136 reqs, GPU KV cache usage: 95.7%, Prefix cache hit rate: 58.2%
|
| 243 |
+
(APIServer pid=114640) INFO 07-17 07:38:45 [loggers.py:273] Engine 000: Avg prompt throughput: 531.5 tokens/s, Avg generation throughput: 3526.3 tokens/s, Running: 165 reqs, Waiting: 5047 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 57.6%
|
| 244 |
+
(APIServer pid=114640) INFO 07-17 07:38:55 [loggers.py:273] Engine 000: Avg prompt throughput: 433.7 tokens/s, Avg generation throughput: 3795.5 tokens/s, Running: 181 reqs, Waiting: 4948 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 57.9%
|
| 245 |
+
(APIServer pid=114640) INFO 07-17 07:39:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3294.4 tokens/s, Running: 117 reqs, Waiting: 4941 reqs, GPU KV cache usage: 98.4%, Prefix cache hit rate: 57.9%
|
| 246 |
+
(APIServer pid=114640) INFO 07-17 07:39:15 [loggers.py:273] Engine 000: Avg prompt throughput: 581.5 tokens/s, Avg generation throughput: 2992.8 tokens/s, Running: 170 reqs, Waiting: 4824 reqs, GPU KV cache usage: 99.5%, Prefix cache hit rate: 57.0%
|
| 247 |
+
(APIServer pid=114640) INFO 07-17 07:39:25 [loggers.py:273] Engine 000: Avg prompt throughput: 774.5 tokens/s, Avg generation throughput: 3083.7 tokens/s, Running: 215 reqs, Waiting: 4706 reqs, GPU KV cache usage: 98.6%, Prefix cache hit rate: 58.6%
|
| 248 |
+
(APIServer pid=114640) INFO 07-17 07:39:35 [loggers.py:273] Engine 000: Avg prompt throughput: 26.1 tokens/s, Avg generation throughput: 3475.0 tokens/s, Running: 113 reqs, Waiting: 4762 reqs, GPU KV cache usage: 97.3%, Prefix cache hit rate: 58.7%
|
| 249 |
+
(APIServer pid=114640) INFO 07-17 07:39:45 [loggers.py:273] Engine 000: Avg prompt throughput: 288.4 tokens/s, Avg generation throughput: 2824.0 tokens/s, Running: 174 reqs, Waiting: 4617 reqs, GPU KV cache usage: 95.2%, Prefix cache hit rate: 59.3%
|
| 250 |
+
(APIServer pid=114640) INFO 07-17 07:39:55 [loggers.py:273] Engine 000: Avg prompt throughput: 321.3 tokens/s, Avg generation throughput: 3403.7 tokens/s, Running: 112 reqs, Waiting: 4622 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 58.9%
|
| 251 |
+
(APIServer pid=114640) INFO 07-17 07:40:05 [loggers.py:273] Engine 000: Avg prompt throughput: 445.0 tokens/s, Avg generation throughput: 3473.8 tokens/s, Running: 133 reqs, Waiting: 4524 reqs, GPU KV cache usage: 99.6%, Prefix cache hit rate: 60.3%
|
| 252 |
+
(APIServer pid=114640) INFO 07-17 07:40:15 [loggers.py:273] Engine 000: Avg prompt throughput: 416.0 tokens/s, Avg generation throughput: 3166.8 tokens/s, Running: 139 reqs, Waiting: 4432 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 61.7%
|
| 253 |
+
(APIServer pid=114640) INFO 07-17 07:40:25 [loggers.py:273] Engine 000: Avg prompt throughput: 283.6 tokens/s, Avg generation throughput: 2985.8 tokens/s, Running: 149 reqs, Waiting: 4360 reqs, GPU KV cache usage: 99.1%, Prefix cache hit rate: 62.4%
|
| 254 |
+
(APIServer pid=114640) INFO 07-17 07:40:35 [loggers.py:273] Engine 000: Avg prompt throughput: 927.0 tokens/s, Avg generation throughput: 3649.9 tokens/s, Running: 200 reqs, Waiting: 4218 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 63.1%
|
| 255 |
+
(APIServer pid=114640) INFO 07-17 07:40:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3314.7 tokens/s, Running: 113 reqs, Waiting: 4253 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 63.1%
|
| 256 |
+
(APIServer pid=114640) INFO 07-17 07:40:55 [loggers.py:273] Engine 000: Avg prompt throughput: 229.0 tokens/s, Avg generation throughput: 2389.3 tokens/s, Running: 168 reqs, Waiting: 4140 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 63.8%
|
| 257 |
+
(APIServer pid=114640) INFO 07-17 07:41:05 [loggers.py:273] Engine 000: Avg prompt throughput: 627.0 tokens/s, Avg generation throughput: 3971.3 tokens/s, Running: 224 reqs, Waiting: 3968 reqs, GPU KV cache usage: 97.3%, Prefix cache hit rate: 63.8%
|
| 258 |
+
(APIServer pid=114640) INFO 07-17 07:41:15 [loggers.py:273] Engine 000: Avg prompt throughput: 295.9 tokens/s, Avg generation throughput: 3754.0 tokens/s, Running: 117 reqs, Waiting: 4011 reqs, GPU KV cache usage: 98.9%, Prefix cache hit rate: 64.7%
|
| 259 |
+
(APIServer pid=114640) INFO 07-17 07:41:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2510.2 tokens/s, Running: 98 reqs, Waiting: 3961 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.7%
|
| 260 |
+
(APIServer pid=114640) INFO 07-17 07:41:35 [loggers.py:273] Engine 000: Avg prompt throughput: 996.4 tokens/s, Avg generation throughput: 3622.1 tokens/s, Running: 256 reqs, Waiting: 3712 reqs, GPU KV cache usage: 90.6%, Prefix cache hit rate: 64.8%
|
| 261 |
+
(APIServer pid=114640) INFO 07-17 07:41:45 [loggers.py:273] Engine 000: Avg prompt throughput: 78.2 tokens/s, Avg generation throughput: 4041.9 tokens/s, Running: 123 reqs, Waiting: 3769 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.8%
|
| 262 |
+
(APIServer pid=114640) INFO 07-17 07:41:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2440.4 tokens/s, Running: 124 reqs, Waiting: 3700 reqs, GPU KV cache usage: 98.6%, Prefix cache hit rate: 64.8%
|
| 263 |
+
(APIServer pid=114640) INFO 07-17 07:42:05 [loggers.py:273] Engine 000: Avg prompt throughput: 1071.1 tokens/s, Avg generation throughput: 3537.6 tokens/s, Running: 256 reqs, Waiting: 3475 reqs, GPU KV cache usage: 98.5%, Prefix cache hit rate: 64.2%
|
| 264 |
+
(APIServer pid=114640) INFO 07-17 07:42:15 [loggers.py:273] Engine 000: Avg prompt throughput: 185.1 tokens/s, Avg generation throughput: 4191.2 tokens/s, Running: 148 reqs, Waiting: 3484 reqs, GPU KV cache usage: 98.8%, Prefix cache hit rate: 64.1%
|
| 265 |
+
(APIServer pid=114640) INFO 07-17 07:42:25 [loggers.py:273] Engine 000: Avg prompt throughput: 91.3 tokens/s, Avg generation throughput: 2920.9 tokens/s, Running: 128 reqs, Waiting: 3428 reqs, GPU KV cache usage: 98.9%, Prefix cache hit rate: 62.7%
|
| 266 |
+
(APIServer pid=114640) INFO 07-17 07:42:35 [loggers.py:273] Engine 000: Avg prompt throughput: 551.2 tokens/s, Avg generation throughput: 3084.0 tokens/s, Running: 150 reqs, Waiting: 3340 reqs, GPU KV cache usage: 98.5%, Prefix cache hit rate: 61.3%
|
| 267 |
+
(APIServer pid=114640) INFO 07-17 07:42:45 [loggers.py:273] Engine 000: Avg prompt throughput: 714.3 tokens/s, Avg generation throughput: 4758.7 tokens/s, Running: 166 reqs, Waiting: 3204 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 61.7%
|
| 268 |
+
(APIServer pid=114640) INFO 07-17 07:42:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2982.7 tokens/s, Running: 110 reqs, Waiting: 3198 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 61.7%
|
| 269 |
+
(APIServer pid=114640) INFO 07-17 07:43:05 [loggers.py:273] Engine 000: Avg prompt throughput: 308.8 tokens/s, Avg generation throughput: 3099.8 tokens/s, Running: 134 reqs, Waiting: 3096 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 60.0%
|
| 270 |
+
(APIServer pid=114640) INFO 07-17 07:43:15 [loggers.py:273] Engine 000: Avg prompt throughput: 709.3 tokens/s, Avg generation throughput: 3840.7 tokens/s, Running: 171 reqs, Waiting: 2983 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.2%
|
| 271 |
+
(APIServer pid=114640) INFO 07-17 07:43:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3094.4 tokens/s, Running: 128 reqs, Waiting: 2956 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.2%
|
| 272 |
+
(APIServer pid=114640) INFO 07-17 07:43:35 [loggers.py:273] Engine 000: Avg prompt throughput: 690.5 tokens/s, Avg generation throughput: 3310.5 tokens/s, Running: 194 reqs, Waiting: 2800 reqs, GPU KV cache usage: 99.4%, Prefix cache hit rate: 58.5%
|
| 273 |
+
(APIServer pid=114640) INFO 07-17 07:43:45 [loggers.py:273] Engine 000: Avg prompt throughput: 299.3 tokens/s, Avg generation throughput: 3494.8 tokens/s, Running: 211 reqs, Waiting: 2692 reqs, GPU KV cache usage: 96.9%, Prefix cache hit rate: 59.0%
|
| 274 |
+
(APIServer pid=114640) INFO 07-17 07:43:55 [loggers.py:273] Engine 000: Avg prompt throughput: 213.8 tokens/s, Avg generation throughput: 3481.7 tokens/s, Running: 106 reqs, Waiting: 2725 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 59.6%
|
| 275 |
+
(APIServer pid=114640) INFO 07-17 07:44:05 [loggers.py:273] Engine 000: Avg prompt throughput: 412.8 tokens/s, Avg generation throughput: 3237.1 tokens/s, Running: 158 reqs, Waiting: 2589 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.5%
|
| 276 |
+
(APIServer pid=114640) INFO 07-17 07:44:15 [loggers.py:273] Engine 000: Avg prompt throughput: 447.9 tokens/s, Avg generation throughput: 3791.4 tokens/s, Running: 183 reqs, Waiting: 2476 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 61.7%
|
| 277 |
+
(APIServer pid=114640) INFO 07-17 07:44:25 [loggers.py:273] Engine 000: Avg prompt throughput: 204.7 tokens/s, Avg generation throughput: 3402.3 tokens/s, Running: 166 reqs, Waiting: 2405 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 62.1%
|
| 278 |
+
(APIServer pid=114640) INFO 07-17 07:44:35 [loggers.py:273] Engine 000: Avg prompt throughput: 264.5 tokens/s, Avg generation throughput: 3002.4 tokens/s, Running: 162 reqs, Waiting: 2344 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 61.3%
|
| 279 |
+
(APIServer pid=114640) INFO 07-17 07:44:45 [loggers.py:273] Engine 000: Avg prompt throughput: 744.4 tokens/s, Avg generation throughput: 3536.9 tokens/s, Running: 253 reqs, Waiting: 2159 reqs, GPU KV cache usage: 91.2%, Prefix cache hit rate: 62.3%
|
| 280 |
+
(APIServer pid=114640) INFO 07-17 07:44:55 [loggers.py:273] Engine 000: Avg prompt throughput: 24.8 tokens/s, Avg generation throughput: 3870.2 tokens/s, Running: 147 reqs, Waiting: 2207 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 62.3%
|
| 281 |
+
(APIServer pid=114640) INFO 07-17 07:45:05 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2952.7 tokens/s, Running: 119 reqs, Waiting: 2172 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 62.3%
|
| 282 |
+
(APIServer pid=114640) INFO 07-17 07:45:15 [loggers.py:273] Engine 000: Avg prompt throughput: 1057.3 tokens/s, Avg generation throughput: 4199.4 tokens/s, Running: 188 reqs, Waiting: 2005 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 58.5%
|
| 283 |
+
(APIServer pid=114640) INFO 07-17 07:45:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3416.4 tokens/s, Running: 114 reqs, Waiting: 2000 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 58.5%
|
| 284 |
+
(APIServer pid=114640) INFO 07-17 07:45:35 [loggers.py:273] Engine 000: Avg prompt throughput: 459.9 tokens/s, Avg generation throughput: 3120.7 tokens/s, Running: 155 reqs, Waiting: 1887 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 59.7%
|
| 285 |
+
(APIServer pid=114640) INFO 07-17 07:45:45 [loggers.py:273] Engine 000: Avg prompt throughput: 690.5 tokens/s, Avg generation throughput: 3359.8 tokens/s, Running: 215 reqs, Waiting: 1741 reqs, GPU KV cache usage: 97.2%, Prefix cache hit rate: 60.0%
|
| 286 |
+
(APIServer pid=114640) INFO 07-17 07:45:55 [loggers.py:273] Engine 000: Avg prompt throughput: 14.2 tokens/s, Avg generation throughput: 3588.6 tokens/s, Running: 120 reqs, Waiting: 1766 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.8%
|
| 287 |
+
(APIServer pid=114640) INFO 07-17 07:46:05 [loggers.py:273] Engine 000: Avg prompt throughput: 579.5 tokens/s, Avg generation throughput: 3361.0 tokens/s, Running: 157 reqs, Waiting: 1641 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 60.4%
|
| 288 |
+
(APIServer pid=114640) INFO 07-17 07:46:15 [loggers.py:273] Engine 000: Avg prompt throughput: 154.0 tokens/s, Avg generation throughput: 3570.0 tokens/s, Running: 129 reqs, Waiting: 1594 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.6%
|
| 289 |
+
(APIServer pid=114640) INFO 07-17 07:46:25 [loggers.py:273] Engine 000: Avg prompt throughput: 356.4 tokens/s, Avg generation throughput: 3209.2 tokens/s, Running: 134 reqs, Waiting: 1512 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 59.9%
|
| 290 |
+
(APIServer pid=114640) INFO 07-17 07:46:35 [loggers.py:273] Engine 000: Avg prompt throughput: 572.7 tokens/s, Avg generation throughput: 3611.6 tokens/s, Running: 176 reqs, Waiting: 1364 reqs, GPU KV cache usage: 98.5%, Prefix cache hit rate: 60.6%
|
| 291 |
+
(APIServer pid=114640) INFO 07-17 07:46:45 [loggers.py:273] Engine 000: Avg prompt throughput: 302.9 tokens/s, Avg generation throughput: 3532.0 tokens/s, Running: 116 reqs, Waiting: 1355 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 60.1%
|
| 292 |
+
(APIServer pid=114640) INFO 07-17 07:46:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2623.2 tokens/s, Running: 97 reqs, Waiting: 1315 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 60.1%
|
| 293 |
+
(APIServer pid=114640) INFO 07-17 07:47:05 [loggers.py:273] Engine 000: Avg prompt throughput: 928.9 tokens/s, Avg generation throughput: 3949.0 tokens/s, Running: 256 reqs, Waiting: 1040 reqs, GPU KV cache usage: 97.6%, Prefix cache hit rate: 64.3%
|
| 294 |
+
(APIServer pid=114640) INFO 07-17 07:47:15 [loggers.py:273] Engine 000: Avg prompt throughput: 188.8 tokens/s, Avg generation throughput: 4374.0 tokens/s, Running: 133 reqs, Waiting: 1067 reqs, GPU KV cache usage: 99.1%, Prefix cache hit rate: 64.7%
|
| 295 |
+
(APIServer pid=114640) INFO 07-17 07:47:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2592.8 tokens/s, Running: 112 reqs, Waiting: 1017 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 64.7%
|
| 296 |
+
(APIServer pid=114640) INFO 07-17 07:47:35 [loggers.py:273] Engine 000: Avg prompt throughput: 1018.3 tokens/s, Avg generation throughput: 3506.5 tokens/s, Running: 254 reqs, Waiting: 746 reqs, GPU KV cache usage: 74.3%, Prefix cache hit rate: 64.8%
|
| 297 |
+
(APIServer pid=114640) INFO 07-17 07:47:45 [loggers.py:273] Engine 000: Avg prompt throughput: 97.9 tokens/s, Avg generation throughput: 4570.2 tokens/s, Running: 138 reqs, Waiting: 795 reqs, GPU KV cache usage: 99.7%, Prefix cache hit rate: 64.6%
|
| 298 |
+
(APIServer pid=114640) INFO 07-17 07:47:55 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2673.9 tokens/s, Running: 123 reqs, Waiting: 741 reqs, GPU KV cache usage: 99.9%, Prefix cache hit rate: 64.6%
|
| 299 |
+
(APIServer pid=114640) INFO 07-17 07:48:05 [loggers.py:273] Engine 000: Avg prompt throughput: 896.7 tokens/s, Avg generation throughput: 3841.0 tokens/s, Running: 169 reqs, Waiting: 605 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 65.5%
|
| 300 |
+
(APIServer pid=114640) INFO 07-17 07:48:15 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 3061.3 tokens/s, Running: 107 reqs, Waiting: 616 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 65.5%
|
| 301 |
+
(APIServer pid=114640) INFO 07-17 07:48:25 [loggers.py:273] Engine 000: Avg prompt throughput: 212.6 tokens/s, Avg generation throughput: 2727.9 tokens/s, Running: 169 reqs, Waiting: 491 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 65.6%
|
| 302 |
+
(APIServer pid=114640) INFO 07-17 07:48:35 [loggers.py:273] Engine 000: Avg prompt throughput: 818.1 tokens/s, Avg generation throughput: 3571.1 tokens/s, Running: 256 reqs, Waiting: 304 reqs, GPU KV cache usage: 92.7%, Prefix cache hit rate: 66.6%
|
| 303 |
+
(APIServer pid=114640) INFO 07-17 07:48:45 [loggers.py:273] Engine 000: Avg prompt throughput: 38.2 tokens/s, Avg generation throughput: 3975.5 tokens/s, Running: 163 reqs, Waiting: 308 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 66.6%
|
| 304 |
+
(APIServer pid=114640) INFO 07-17 07:48:55 [loggers.py:273] Engine 000: Avg prompt throughput: 201.8 tokens/s, Avg generation throughput: 2881.4 tokens/s, Running: 147 reqs, Waiting: 256 reqs, GPU KV cache usage: 94.9%, Prefix cache hit rate: 66.0%
|
| 305 |
+
(APIServer pid=114640) INFO 07-17 07:49:05 [loggers.py:273] Engine 000: Avg prompt throughput: 356.0 tokens/s, Avg generation throughput: 3223.9 tokens/s, Running: 109 reqs, Waiting: 238 reqs, GPU KV cache usage: 99.8%, Prefix cache hit rate: 65.9%
|
| 306 |
+
(APIServer pid=114640) INFO 07-17 07:49:15 [loggers.py:273] Engine 000: Avg prompt throughput: 779.1 tokens/s, Avg generation throughput: 4190.1 tokens/s, Running: 155 reqs, Waiting: 79 reqs, GPU KV cache usage: 99.2%, Prefix cache hit rate: 66.2%
|
| 307 |
+
(APIServer pid=114640) INFO 07-17 07:49:25 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 2792.5 tokens/s, Running: 90 reqs, Waiting: 83 reqs, GPU KV cache usage: 100.0%, Prefix cache hit rate: 66.2%
|
| 308 |
+
(APIServer pid=114640) INFO 07-17 07:49:35 [loggers.py:273] Engine 000: Avg prompt throughput: 46.4 tokens/s, Avg generation throughput: 2781.4 tokens/s, Running: 77 reqs, Waiting: 0 reqs, GPU KV cache usage: 62.1%, Prefix cache hit rate: 66.6%
|
| 309 |
+
(APIServer pid=114640) INFO 07-17 07:49:45 [loggers.py:273] Engine 000: Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 1590.5 tokens/s, Running: 8 reqs, Waiting: 0 reqs, GPU KV cache usage: 11.2%, Prefix cache hit rate: 66.6%
|
| 310 |
+
(APIServer pid=114640) INFO: 127.0.0.1:55130 - "POST /v1/completions HTTP/1.1" 200 OK
|
| 311 |
+
(EngineCore pid=114758) INFO 07-17 07:49:49 [core.py:1214] [shutdown] EngineCore: trigger received signal=SIGTERM
|
| 312 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [launcher.py:100] [shutdown] API server: shutdown triggered
|
| 313 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [launcher.py:116] [shutdown] API server: stopping engine client mode=abort timeout=0s
|
| 314 |
+
(EngineCore pid=114758) INFO 07-17 07:49:49 [core.py:1333] [shutdown] EngineCore: start mode=abort timeout=0s
|
| 315 |
+
(EngineCore pid=114758) INFO 07-17 07:49:49 [core.py:1364] [shutdown] EngineCore: request processing complete; starting resource teardown
|
| 316 |
+
(EngineCore pid=114758) INFO 07-17 07:49:49 [core.py:1227] [shutdown] EngineCore: exiting busy loop
|
| 317 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [core_client.py:655] [shutdown] MPClient: start timeout=0s
|
| 318 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [core_client.py:657] [shutdown] MPClient: stopping engine manager
|
| 319 |
+
(APIServer pid=114640) WARNING 07-17 07:49:49 [utils.py:626] [shutdown] Process manager: force killing remaining processes count=1
|
| 320 |
+
(APIServer pid=114640) INFO: Shutting down
|
| 321 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [core_client.py:659] [shutdown] MPClient: engine manager stopped
|
| 322 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [core_client.py:660] [shutdown] MPClient: cleaning up background resources
|
| 323 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [core_client.py:662] [shutdown] MPClient: complete
|
| 324 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [launcher.py:125] [shutdown] API server: engine client stopped
|
| 325 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [launcher.py:128] [shutdown] API server: signalling HTTP server shutdown
|
| 326 |
+
(APIServer pid=114640) INFO 07-17 07:49:49 [launcher.py:149] [shutdown] API server: shutting down FastAPI HTTP server
|
| 327 |
+
(APIServer pid=114640) INFO: Shutting down
|
| 328 |
+
(APIServer pid=114640) INFO: Waiting for application shutdown.
|
| 329 |
+
(APIServer pid=114640) INFO: Application shutdown complete.
|
| 330 |
+
/home/henry/.local/share/uv/python/cpython-3.12.12-linux-x86_64-gnu/lib/python3.12/multiprocessing/resource_tracker.py:279: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
|
| 331 |
+
warnings.warn('resource_tracker: There appear to be %d '
|
teacher_trajectories/top128_score.log
ADDED
|
@@ -0,0 +1,783 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
reconstructing exact chat prompts ...
|
| 2 |
+
loading teacher on cuda:0 ...
|
| 3 |
+
|
| 4 |
+
shard 00000: 128/12115 records | 73,031 tokens | 9.34 records/s
|
| 5 |
+
shard 00001: 256/12115 records | 142,706 tokens | 9.67 records/s
|
| 6 |
+
shard 00002: 384/12115 records | 221,592 tokens | 9.64 records/s
|
| 7 |
+
shard 00003: 512/12115 records | 290,966 tokens | 9.70 records/s
|
| 8 |
+
shard 00004: 640/12115 records | 362,190 tokens | 9.72 records/s
|
| 9 |
+
shard 00005: 768/12115 records | 432,885 tokens | 9.73 records/s
|
| 10 |
+
shard 00006: 896/12115 records | 507,356 tokens | 9.74 records/s
|
| 11 |
+
shard 00007: 1024/12115 records | 578,914 tokens | 9.75 records/s
|
| 12 |
+
shard 00008: 1152/12115 records | 646,302 tokens | 9.78 records/s
|
| 13 |
+
shard 00009: 1280/12115 records | 715,522 tokens | 9.78 records/s
|
| 14 |
+
shard 00010: 1408/12115 records | 789,398 tokens | 9.77 records/s
|
| 15 |
+
shard 00011: 1536/12115 records | 859,905 tokens | 9.77 records/s
|
| 16 |
+
shard 00012: 1664/12115 records | 929,957 tokens | 9.79 records/s
|
| 17 |
+
shard 00013: 1792/12115 records | 1,002,897 tokens | 9.79 records/s
|
| 18 |
+
shard 00014: 1920/12115 records | 1,076,939 tokens | 9.79 records/s
|
| 19 |
+
shard 00015: 2048/12115 records | 1,152,867 tokens | 9.78 records/s
|
| 20 |
+
shard 00016: 2176/12115 records | 1,226,568 tokens | 9.78 records/s
|
| 21 |
+
shard 00017: 2304/12115 records | 1,295,943 tokens | 9.79 records/s
|
| 22 |
+
shard 00018: 2432/12115 records | 1,367,163 tokens | 9.79 records/s
|
| 23 |
+
shard 00019: 2560/12115 records | 1,444,451 tokens | 9.78 records/s
|
| 24 |
+
shard 00020: 2688/12115 records | 1,517,881 tokens | 9.79 records/s
|
| 25 |
+
shard 00021: 2816/12115 records | 1,586,866 tokens | 9.80 records/s
|
| 26 |
+
shard 00022: 2944/12115 records | 1,661,501 tokens | 9.80 records/s
|
| 27 |
+
shard 00023: 3072/12115 records | 1,733,775 tokens | 9.79 records/s
|
| 28 |
+
shard 00024: 3200/12115 records | 1,806,409 tokens | 9.80 records/s
|
| 29 |
+
shard 00025: 3328/12115 records | 1,882,641 tokens | 9.80 records/s
|
| 30 |
+
shard 00026: 3456/12115 records | 1,947,920 tokens | 9.80 records/s
|
| 31 |
+
shard 00027: 3584/12115 records | 2,010,837 tokens | 9.82 records/s
|
| 32 |
+
shard 00028: 3712/12115 records | 2,069,317 tokens | 9.84 records/s
|
| 33 |
+
shard 00029: 3840/12115 records | 2,128,231 tokens | 9.85 records/s
|
| 34 |
+
shard 00030: 3968/12115 records | 2,190,763 tokens | 9.87 records/s
|
| 35 |
+
shard 00031: 4096/12115 records | 2,252,493 tokens | 9.88 records/s
|
| 36 |
+
shard 00032: 4224/12115 records | 2,312,761 tokens | 9.90 records/s
|
| 37 |
+
shard 00033: 4352/12115 records | 2,375,766 tokens | 9.91 records/s
|
| 38 |
+
shard 00034: 4480/12115 records | 2,439,594 tokens | 9.92 records/s
|
| 39 |
+
shard 00035: 4608/12115 records | 2,495,617 tokens | 9.94 records/s
|
| 40 |
+
shard 00036: 4736/12115 records | 2,558,881 tokens | 9.95 records/s
|
| 41 |
+
shard 00037: 4864/12115 records | 2,618,211 tokens | 9.96 records/s
|
| 42 |
+
shard 00038: 4992/12115 records | 2,677,399 tokens | 9.97 records/s
|
| 43 |
+
shard 00039: 5120/12115 records | 2,735,990 tokens | 9.98 records/s
|
| 44 |
+
shard 00040: 5248/12115 records | 2,797,207 tokens | 9.99 records/s
|
| 45 |
+
shard 00041: 5376/12115 records | 2,854,573 tokens | 10.00 records/s
|
| 46 |
+
shard 00042: 5504/12115 records | 2,915,874 tokens | 10.01 records/s
|
| 47 |
+
shard 00043: 5632/12115 records | 2,979,417 tokens | 10.01 records/s
|
| 48 |
+
shard 00044: 5760/12115 records | 3,038,136 tokens | 10.02 records/s
|
| 49 |
+
shard 00045: 5888/12115 records | 3,097,503 tokens | 10.03 records/s
|
| 50 |
+
shard 00046: 6016/12115 records | 3,152,821 tokens | 10.04 records/s
|
| 51 |
+
shard 00047: 6144/12115 records | 3,217,264 tokens | 10.05 records/s
|
| 52 |
+
shard 00048: 6272/12115 records | 3,277,016 tokens | 10.05 records/s
|
| 53 |
+
shard 00049: 6400/12115 records | 3,341,336 tokens | 10.05 records/s
|
| 54 |
+
shard 00050: 6528/12115 records | 3,405,709 tokens | 10.06 records/s
|
| 55 |
+
shard 00051: 6656/12115 records | 3,460,422 tokens | 10.07 records/s
|
| 56 |
+
shard 00052: 6784/12115 records | 3,522,884 tokens | 10.07 records/s
|
| 57 |
+
shard 00053: 6912/12115 records | 3,582,024 tokens | 10.07 records/s
|
| 58 |
+
shard 00054: 7040/12115 records | 3,648,314 tokens | 10.07 records/s
|
| 59 |
+
shard 00055: 7168/12115 records | 3,714,896 tokens | 10.08 records/s
|
| 60 |
+
shard 00056: 7296/12115 records | 3,777,946 tokens | 10.09 records/s
|
| 61 |
+
shard 00057: 7424/12115 records | 3,836,597 tokens | 10.09 records/s
|
| 62 |
+
shard 00058: 7552/12115 records | 3,896,186 tokens | 10.10 records/s
|
| 63 |
+
shard 00059: 7680/12115 records | 3,956,340 tokens | 10.11 records/s
|
| 64 |
+
shard 00060: 7808/12115 records | 4,012,509 tokens | 10.11 records/s
|
| 65 |
+
shard 00061: 7936/12115 records | 4,076,475 tokens | 10.11 records/s
|
| 66 |
+
shard 00062: 8064/12115 records | 4,151,986 tokens | 10.10 records/s
|
| 67 |
+
shard 00063: 8192/12115 records | 4,232,690 tokens | 10.09 records/s
|
| 68 |
+
shard 00064: 8320/12115 records | 4,307,965 tokens | 10.08 records/s
|
| 69 |
+
shard 00065: 8448/12115 records | 4,380,815 tokens | 10.07 records/s
|
| 70 |
+
shard 00066: 8576/12115 records | 4,453,096 tokens | 10.06 records/s
|
| 71 |
+
shard 00067: 8704/12115 records | 4,527,660 tokens | 10.04 records/s
|
| 72 |
+
shard 00068: 8832/12115 records | 4,605,858 tokens | 10.03 records/s
|
| 73 |
+
shard 00069: 8960/12115 records | 4,680,546 tokens | 10.02 records/s
|
| 74 |
+
shard 00070: 9088/12115 records | 4,753,994 tokens | 10.02 records/s
|
| 75 |
+
shard 00071: 9216/12115 records | 4,827,678 tokens | 10.01 records/s
|
| 76 |
+
shard 00072: 9344/12115 records | 4,903,825 tokens | 10.00 records/s
|
| 77 |
+
shard 00073: 9472/12115 records | 4,977,432 tokens | 10.00 records/s
|
| 78 |
+
shard 00074: 9600/12115 records | 5,054,090 tokens | 9.99 records/s
|
| 79 |
+
shard 00075: 9728/12115 records | 5,125,142 tokens | 9.99 records/s
|
| 80 |
+
shard 00076: 9856/12115 records | 5,196,981 tokens | 9.99 records/s
|
| 81 |
+
shard 00077: 9984/12115 records | 5,261,629 tokens | 9.99 records/s
|
| 82 |
+
shard 00078: 10112/12115 records | 5,331,065 tokens | 9.99 records/s
|
| 83 |
+
shard 00079: 10240/12115 records | 5,403,259 tokens | 9.99 records/s
|
| 84 |
+
shard 00080: 10368/12115 records | 5,477,552 tokens | 9.99 records/s
|
| 85 |
+
shard 00081: 10496/12115 records | 5,550,170 tokens | 9.98 records/s
|
| 86 |
+
shard 00082: 10624/12115 records | 5,625,121 tokens | 9.98 records/s
|
| 87 |
+
shard 00083: 10752/12115 records | 5,691,110 tokens | 9.98 records/s
|
| 88 |
+
shard 00084: 10880/12115 records | 5,761,375 tokens | 9.98 records/s
|
| 89 |
+
shard 00085: 11008/12115 records | 5,833,732 tokens | 9.98 records/s
|
| 90 |
+
shard 00086: 11136/12115 records | 5,904,113 tokens | 9.98 records/s
|
| 91 |
+
shard 00087: 11264/12115 records | 5,967,914 tokens | 9.99 records/s
|
| 92 |
+
shard 00088: 11392/12115 records | 6,040,652 tokens | 9.99 records/s
|
| 93 |
+
shard 00089: 11520/12115 records | 6,114,847 tokens | 9.98 records/s
|
| 94 |
+
shard 00090: 11648/12115 records | 6,193,540 tokens | 9.98 records/s
|
| 95 |
+
shard 00091: 11776/12115 records | 6,269,234 tokens | 9.98 records/s
|
| 96 |
+
shard 00092: 11904/12115 records | 6,349,496 tokens | 9.97 records/s
|
| 97 |
+
shard 00093: 12032/12115 records | 6,429,742 tokens | 9.97 records/s
|
| 98 |
+
shard 00094: 12115/12115 records | 6,476,634 tokens | 9.97 records/s
|
| 99 |
+
{
|
| 100 |
+
"version": 1,
|
| 101 |
+
"complete": true,
|
| 102 |
+
"teacher": "allenai/OLMoE-1B-7B-0125-Instruct",
|
| 103 |
+
"tokenizer": "allenai/OLMoE-1B-7B-0125-Instruct",
|
| 104 |
+
"source": "/home/henry/Documents/PythonProjects/variable-reap/outputs/teacher_trajectories/dolci_math_curated_opd.jsonl",
|
| 105 |
+
"source_size": 57436902,
|
| 106 |
+
"frame": "chat",
|
| 107 |
+
"topk": 128,
|
| 108 |
+
"max_prompt_len": 1024,
|
| 109 |
+
"max_seq_len": 2048,
|
| 110 |
+
"pad_token_id": 50280,
|
| 111 |
+
"eos_token_id": 50279,
|
| 112 |
+
"total_records": 12115,
|
| 113 |
+
"total_tokens": 6476634,
|
| 114 |
+
"shards": [
|
| 115 |
+
{
|
| 116 |
+
"path": "shard_00000.pt",
|
| 117 |
+
"records": 128,
|
| 118 |
+
"tokens": 73031,
|
| 119 |
+
"first_record": 0,
|
| 120 |
+
"last_record": 127
|
| 121 |
+
},
|
| 122 |
+
{
|
| 123 |
+
"path": "shard_00001.pt",
|
| 124 |
+
"records": 128,
|
| 125 |
+
"tokens": 69675,
|
| 126 |
+
"first_record": 128,
|
| 127 |
+
"last_record": 255
|
| 128 |
+
},
|
| 129 |
+
{
|
| 130 |
+
"path": "shard_00002.pt",
|
| 131 |
+
"records": 128,
|
| 132 |
+
"tokens": 78886,
|
| 133 |
+
"first_record": 256,
|
| 134 |
+
"last_record": 383
|
| 135 |
+
},
|
| 136 |
+
{
|
| 137 |
+
"path": "shard_00003.pt",
|
| 138 |
+
"records": 128,
|
| 139 |
+
"tokens": 69374,
|
| 140 |
+
"first_record": 384,
|
| 141 |
+
"last_record": 511
|
| 142 |
+
},
|
| 143 |
+
{
|
| 144 |
+
"path": "shard_00004.pt",
|
| 145 |
+
"records": 128,
|
| 146 |
+
"tokens": 71224,
|
| 147 |
+
"first_record": 512,
|
| 148 |
+
"last_record": 639
|
| 149 |
+
},
|
| 150 |
+
{
|
| 151 |
+
"path": "shard_00005.pt",
|
| 152 |
+
"records": 128,
|
| 153 |
+
"tokens": 70695,
|
| 154 |
+
"first_record": 640,
|
| 155 |
+
"last_record": 767
|
| 156 |
+
},
|
| 157 |
+
{
|
| 158 |
+
"path": "shard_00006.pt",
|
| 159 |
+
"records": 128,
|
| 160 |
+
"tokens": 74471,
|
| 161 |
+
"first_record": 768,
|
| 162 |
+
"last_record": 895
|
| 163 |
+
},
|
| 164 |
+
{
|
| 165 |
+
"path": "shard_00007.pt",
|
| 166 |
+
"records": 128,
|
| 167 |
+
"tokens": 71558,
|
| 168 |
+
"first_record": 896,
|
| 169 |
+
"last_record": 1023
|
| 170 |
+
},
|
| 171 |
+
{
|
| 172 |
+
"path": "shard_00008.pt",
|
| 173 |
+
"records": 128,
|
| 174 |
+
"tokens": 67388,
|
| 175 |
+
"first_record": 1024,
|
| 176 |
+
"last_record": 1151
|
| 177 |
+
},
|
| 178 |
+
{
|
| 179 |
+
"path": "shard_00009.pt",
|
| 180 |
+
"records": 128,
|
| 181 |
+
"tokens": 69220,
|
| 182 |
+
"first_record": 1152,
|
| 183 |
+
"last_record": 1279
|
| 184 |
+
},
|
| 185 |
+
{
|
| 186 |
+
"path": "shard_00010.pt",
|
| 187 |
+
"records": 128,
|
| 188 |
+
"tokens": 73876,
|
| 189 |
+
"first_record": 1280,
|
| 190 |
+
"last_record": 1407
|
| 191 |
+
},
|
| 192 |
+
{
|
| 193 |
+
"path": "shard_00011.pt",
|
| 194 |
+
"records": 128,
|
| 195 |
+
"tokens": 70507,
|
| 196 |
+
"first_record": 1408,
|
| 197 |
+
"last_record": 1535
|
| 198 |
+
},
|
| 199 |
+
{
|
| 200 |
+
"path": "shard_00012.pt",
|
| 201 |
+
"records": 128,
|
| 202 |
+
"tokens": 70052,
|
| 203 |
+
"first_record": 1536,
|
| 204 |
+
"last_record": 1663
|
| 205 |
+
},
|
| 206 |
+
{
|
| 207 |
+
"path": "shard_00013.pt",
|
| 208 |
+
"records": 128,
|
| 209 |
+
"tokens": 72940,
|
| 210 |
+
"first_record": 1664,
|
| 211 |
+
"last_record": 1791
|
| 212 |
+
},
|
| 213 |
+
{
|
| 214 |
+
"path": "shard_00014.pt",
|
| 215 |
+
"records": 128,
|
| 216 |
+
"tokens": 74042,
|
| 217 |
+
"first_record": 1792,
|
| 218 |
+
"last_record": 1919
|
| 219 |
+
},
|
| 220 |
+
{
|
| 221 |
+
"path": "shard_00015.pt",
|
| 222 |
+
"records": 128,
|
| 223 |
+
"tokens": 75928,
|
| 224 |
+
"first_record": 1920,
|
| 225 |
+
"last_record": 2047
|
| 226 |
+
},
|
| 227 |
+
{
|
| 228 |
+
"path": "shard_00016.pt",
|
| 229 |
+
"records": 128,
|
| 230 |
+
"tokens": 73701,
|
| 231 |
+
"first_record": 2048,
|
| 232 |
+
"last_record": 2175
|
| 233 |
+
},
|
| 234 |
+
{
|
| 235 |
+
"path": "shard_00017.pt",
|
| 236 |
+
"records": 128,
|
| 237 |
+
"tokens": 69375,
|
| 238 |
+
"first_record": 2176,
|
| 239 |
+
"last_record": 2303
|
| 240 |
+
},
|
| 241 |
+
{
|
| 242 |
+
"path": "shard_00018.pt",
|
| 243 |
+
"records": 128,
|
| 244 |
+
"tokens": 71220,
|
| 245 |
+
"first_record": 2304,
|
| 246 |
+
"last_record": 2431
|
| 247 |
+
},
|
| 248 |
+
{
|
| 249 |
+
"path": "shard_00019.pt",
|
| 250 |
+
"records": 128,
|
| 251 |
+
"tokens": 77288,
|
| 252 |
+
"first_record": 2432,
|
| 253 |
+
"last_record": 2559
|
| 254 |
+
},
|
| 255 |
+
{
|
| 256 |
+
"path": "shard_00020.pt",
|
| 257 |
+
"records": 128,
|
| 258 |
+
"tokens": 73430,
|
| 259 |
+
"first_record": 2560,
|
| 260 |
+
"last_record": 2687
|
| 261 |
+
},
|
| 262 |
+
{
|
| 263 |
+
"path": "shard_00021.pt",
|
| 264 |
+
"records": 128,
|
| 265 |
+
"tokens": 68985,
|
| 266 |
+
"first_record": 2688,
|
| 267 |
+
"last_record": 2815
|
| 268 |
+
},
|
| 269 |
+
{
|
| 270 |
+
"path": "shard_00022.pt",
|
| 271 |
+
"records": 128,
|
| 272 |
+
"tokens": 74635,
|
| 273 |
+
"first_record": 2816,
|
| 274 |
+
"last_record": 2943
|
| 275 |
+
},
|
| 276 |
+
{
|
| 277 |
+
"path": "shard_00023.pt",
|
| 278 |
+
"records": 128,
|
| 279 |
+
"tokens": 72274,
|
| 280 |
+
"first_record": 2944,
|
| 281 |
+
"last_record": 3071
|
| 282 |
+
},
|
| 283 |
+
{
|
| 284 |
+
"path": "shard_00024.pt",
|
| 285 |
+
"records": 128,
|
| 286 |
+
"tokens": 72634,
|
| 287 |
+
"first_record": 3072,
|
| 288 |
+
"last_record": 3199
|
| 289 |
+
},
|
| 290 |
+
{
|
| 291 |
+
"path": "shard_00025.pt",
|
| 292 |
+
"records": 128,
|
| 293 |
+
"tokens": 76232,
|
| 294 |
+
"first_record": 3200,
|
| 295 |
+
"last_record": 3327
|
| 296 |
+
},
|
| 297 |
+
{
|
| 298 |
+
"path": "shard_00026.pt",
|
| 299 |
+
"records": 128,
|
| 300 |
+
"tokens": 65279,
|
| 301 |
+
"first_record": 3328,
|
| 302 |
+
"last_record": 3455
|
| 303 |
+
},
|
| 304 |
+
{
|
| 305 |
+
"path": "shard_00027.pt",
|
| 306 |
+
"records": 128,
|
| 307 |
+
"tokens": 62917,
|
| 308 |
+
"first_record": 3456,
|
| 309 |
+
"last_record": 3583
|
| 310 |
+
},
|
| 311 |
+
{
|
| 312 |
+
"path": "shard_00028.pt",
|
| 313 |
+
"records": 128,
|
| 314 |
+
"tokens": 58480,
|
| 315 |
+
"first_record": 3584,
|
| 316 |
+
"last_record": 3711
|
| 317 |
+
},
|
| 318 |
+
{
|
| 319 |
+
"path": "shard_00029.pt",
|
| 320 |
+
"records": 128,
|
| 321 |
+
"tokens": 58914,
|
| 322 |
+
"first_record": 3712,
|
| 323 |
+
"last_record": 3839
|
| 324 |
+
},
|
| 325 |
+
{
|
| 326 |
+
"path": "shard_00030.pt",
|
| 327 |
+
"records": 128,
|
| 328 |
+
"tokens": 62532,
|
| 329 |
+
"first_record": 3840,
|
| 330 |
+
"last_record": 3967
|
| 331 |
+
},
|
| 332 |
+
{
|
| 333 |
+
"path": "shard_00031.pt",
|
| 334 |
+
"records": 128,
|
| 335 |
+
"tokens": 61730,
|
| 336 |
+
"first_record": 3968,
|
| 337 |
+
"last_record": 4095
|
| 338 |
+
},
|
| 339 |
+
{
|
| 340 |
+
"path": "shard_00032.pt",
|
| 341 |
+
"records": 128,
|
| 342 |
+
"tokens": 60268,
|
| 343 |
+
"first_record": 4096,
|
| 344 |
+
"last_record": 4223
|
| 345 |
+
},
|
| 346 |
+
{
|
| 347 |
+
"path": "shard_00033.pt",
|
| 348 |
+
"records": 128,
|
| 349 |
+
"tokens": 63005,
|
| 350 |
+
"first_record": 4224,
|
| 351 |
+
"last_record": 4351
|
| 352 |
+
},
|
| 353 |
+
{
|
| 354 |
+
"path": "shard_00034.pt",
|
| 355 |
+
"records": 128,
|
| 356 |
+
"tokens": 63828,
|
| 357 |
+
"first_record": 4352,
|
| 358 |
+
"last_record": 4479
|
| 359 |
+
},
|
| 360 |
+
{
|
| 361 |
+
"path": "shard_00035.pt",
|
| 362 |
+
"records": 128,
|
| 363 |
+
"tokens": 56023,
|
| 364 |
+
"first_record": 4480,
|
| 365 |
+
"last_record": 4607
|
| 366 |
+
},
|
| 367 |
+
{
|
| 368 |
+
"path": "shard_00036.pt",
|
| 369 |
+
"records": 128,
|
| 370 |
+
"tokens": 63264,
|
| 371 |
+
"first_record": 4608,
|
| 372 |
+
"last_record": 4735
|
| 373 |
+
},
|
| 374 |
+
{
|
| 375 |
+
"path": "shard_00037.pt",
|
| 376 |
+
"records": 128,
|
| 377 |
+
"tokens": 59330,
|
| 378 |
+
"first_record": 4736,
|
| 379 |
+
"last_record": 4863
|
| 380 |
+
},
|
| 381 |
+
{
|
| 382 |
+
"path": "shard_00038.pt",
|
| 383 |
+
"records": 128,
|
| 384 |
+
"tokens": 59188,
|
| 385 |
+
"first_record": 4864,
|
| 386 |
+
"last_record": 4991
|
| 387 |
+
},
|
| 388 |
+
{
|
| 389 |
+
"path": "shard_00039.pt",
|
| 390 |
+
"records": 128,
|
| 391 |
+
"tokens": 58591,
|
| 392 |
+
"first_record": 4992,
|
| 393 |
+
"last_record": 5119
|
| 394 |
+
},
|
| 395 |
+
{
|
| 396 |
+
"path": "shard_00040.pt",
|
| 397 |
+
"records": 128,
|
| 398 |
+
"tokens": 61217,
|
| 399 |
+
"first_record": 5120,
|
| 400 |
+
"last_record": 5247
|
| 401 |
+
},
|
| 402 |
+
{
|
| 403 |
+
"path": "shard_00041.pt",
|
| 404 |
+
"records": 128,
|
| 405 |
+
"tokens": 57366,
|
| 406 |
+
"first_record": 5248,
|
| 407 |
+
"last_record": 5375
|
| 408 |
+
},
|
| 409 |
+
{
|
| 410 |
+
"path": "shard_00042.pt",
|
| 411 |
+
"records": 128,
|
| 412 |
+
"tokens": 61301,
|
| 413 |
+
"first_record": 5376,
|
| 414 |
+
"last_record": 5503
|
| 415 |
+
},
|
| 416 |
+
{
|
| 417 |
+
"path": "shard_00043.pt",
|
| 418 |
+
"records": 128,
|
| 419 |
+
"tokens": 63543,
|
| 420 |
+
"first_record": 5504,
|
| 421 |
+
"last_record": 5631
|
| 422 |
+
},
|
| 423 |
+
{
|
| 424 |
+
"path": "shard_00044.pt",
|
| 425 |
+
"records": 128,
|
| 426 |
+
"tokens": 58719,
|
| 427 |
+
"first_record": 5632,
|
| 428 |
+
"last_record": 5759
|
| 429 |
+
},
|
| 430 |
+
{
|
| 431 |
+
"path": "shard_00045.pt",
|
| 432 |
+
"records": 128,
|
| 433 |
+
"tokens": 59367,
|
| 434 |
+
"first_record": 5760,
|
| 435 |
+
"last_record": 5887
|
| 436 |
+
},
|
| 437 |
+
{
|
| 438 |
+
"path": "shard_00046.pt",
|
| 439 |
+
"records": 128,
|
| 440 |
+
"tokens": 55318,
|
| 441 |
+
"first_record": 5888,
|
| 442 |
+
"last_record": 6015
|
| 443 |
+
},
|
| 444 |
+
{
|
| 445 |
+
"path": "shard_00047.pt",
|
| 446 |
+
"records": 128,
|
| 447 |
+
"tokens": 64443,
|
| 448 |
+
"first_record": 6016,
|
| 449 |
+
"last_record": 6143
|
| 450 |
+
},
|
| 451 |
+
{
|
| 452 |
+
"path": "shard_00048.pt",
|
| 453 |
+
"records": 128,
|
| 454 |
+
"tokens": 59752,
|
| 455 |
+
"first_record": 6144,
|
| 456 |
+
"last_record": 6271
|
| 457 |
+
},
|
| 458 |
+
{
|
| 459 |
+
"path": "shard_00049.pt",
|
| 460 |
+
"records": 128,
|
| 461 |
+
"tokens": 64320,
|
| 462 |
+
"first_record": 6272,
|
| 463 |
+
"last_record": 6399
|
| 464 |
+
},
|
| 465 |
+
{
|
| 466 |
+
"path": "shard_00050.pt",
|
| 467 |
+
"records": 128,
|
| 468 |
+
"tokens": 64373,
|
| 469 |
+
"first_record": 6400,
|
| 470 |
+
"last_record": 6527
|
| 471 |
+
},
|
| 472 |
+
{
|
| 473 |
+
"path": "shard_00051.pt",
|
| 474 |
+
"records": 128,
|
| 475 |
+
"tokens": 54713,
|
| 476 |
+
"first_record": 6528,
|
| 477 |
+
"last_record": 6655
|
| 478 |
+
},
|
| 479 |
+
{
|
| 480 |
+
"path": "shard_00052.pt",
|
| 481 |
+
"records": 128,
|
| 482 |
+
"tokens": 62462,
|
| 483 |
+
"first_record": 6656,
|
| 484 |
+
"last_record": 6783
|
| 485 |
+
},
|
| 486 |
+
{
|
| 487 |
+
"path": "shard_00053.pt",
|
| 488 |
+
"records": 128,
|
| 489 |
+
"tokens": 59140,
|
| 490 |
+
"first_record": 6784,
|
| 491 |
+
"last_record": 6911
|
| 492 |
+
},
|
| 493 |
+
{
|
| 494 |
+
"path": "shard_00054.pt",
|
| 495 |
+
"records": 128,
|
| 496 |
+
"tokens": 66290,
|
| 497 |
+
"first_record": 6912,
|
| 498 |
+
"last_record": 7039
|
| 499 |
+
},
|
| 500 |
+
{
|
| 501 |
+
"path": "shard_00055.pt",
|
| 502 |
+
"records": 128,
|
| 503 |
+
"tokens": 66582,
|
| 504 |
+
"first_record": 7040,
|
| 505 |
+
"last_record": 7167
|
| 506 |
+
},
|
| 507 |
+
{
|
| 508 |
+
"path": "shard_00056.pt",
|
| 509 |
+
"records": 128,
|
| 510 |
+
"tokens": 63050,
|
| 511 |
+
"first_record": 7168,
|
| 512 |
+
"last_record": 7295
|
| 513 |
+
},
|
| 514 |
+
{
|
| 515 |
+
"path": "shard_00057.pt",
|
| 516 |
+
"records": 128,
|
| 517 |
+
"tokens": 58651,
|
| 518 |
+
"first_record": 7296,
|
| 519 |
+
"last_record": 7423
|
| 520 |
+
},
|
| 521 |
+
{
|
| 522 |
+
"path": "shard_00058.pt",
|
| 523 |
+
"records": 128,
|
| 524 |
+
"tokens": 59589,
|
| 525 |
+
"first_record": 7424,
|
| 526 |
+
"last_record": 7551
|
| 527 |
+
},
|
| 528 |
+
{
|
| 529 |
+
"path": "shard_00059.pt",
|
| 530 |
+
"records": 128,
|
| 531 |
+
"tokens": 60154,
|
| 532 |
+
"first_record": 7552,
|
| 533 |
+
"last_record": 7679
|
| 534 |
+
},
|
| 535 |
+
{
|
| 536 |
+
"path": "shard_00060.pt",
|
| 537 |
+
"records": 128,
|
| 538 |
+
"tokens": 56169,
|
| 539 |
+
"first_record": 7680,
|
| 540 |
+
"last_record": 7807
|
| 541 |
+
},
|
| 542 |
+
{
|
| 543 |
+
"path": "shard_00061.pt",
|
| 544 |
+
"records": 128,
|
| 545 |
+
"tokens": 63966,
|
| 546 |
+
"first_record": 7808,
|
| 547 |
+
"last_record": 7935
|
| 548 |
+
},
|
| 549 |
+
{
|
| 550 |
+
"path": "shard_00062.pt",
|
| 551 |
+
"records": 128,
|
| 552 |
+
"tokens": 75511,
|
| 553 |
+
"first_record": 7936,
|
| 554 |
+
"last_record": 8063
|
| 555 |
+
},
|
| 556 |
+
{
|
| 557 |
+
"path": "shard_00063.pt",
|
| 558 |
+
"records": 128,
|
| 559 |
+
"tokens": 80704,
|
| 560 |
+
"first_record": 8064,
|
| 561 |
+
"last_record": 8191
|
| 562 |
+
},
|
| 563 |
+
{
|
| 564 |
+
"path": "shard_00064.pt",
|
| 565 |
+
"records": 128,
|
| 566 |
+
"tokens": 75275,
|
| 567 |
+
"first_record": 8192,
|
| 568 |
+
"last_record": 8319
|
| 569 |
+
},
|
| 570 |
+
{
|
| 571 |
+
"path": "shard_00065.pt",
|
| 572 |
+
"records": 128,
|
| 573 |
+
"tokens": 72850,
|
| 574 |
+
"first_record": 8320,
|
| 575 |
+
"last_record": 8447
|
| 576 |
+
},
|
| 577 |
+
{
|
| 578 |
+
"path": "shard_00066.pt",
|
| 579 |
+
"records": 128,
|
| 580 |
+
"tokens": 72281,
|
| 581 |
+
"first_record": 8448,
|
| 582 |
+
"last_record": 8575
|
| 583 |
+
},
|
| 584 |
+
{
|
| 585 |
+
"path": "shard_00067.pt",
|
| 586 |
+
"records": 128,
|
| 587 |
+
"tokens": 74564,
|
| 588 |
+
"first_record": 8576,
|
| 589 |
+
"last_record": 8703
|
| 590 |
+
},
|
| 591 |
+
{
|
| 592 |
+
"path": "shard_00068.pt",
|
| 593 |
+
"records": 128,
|
| 594 |
+
"tokens": 78198,
|
| 595 |
+
"first_record": 8704,
|
| 596 |
+
"last_record": 8831
|
| 597 |
+
},
|
| 598 |
+
{
|
| 599 |
+
"path": "shard_00069.pt",
|
| 600 |
+
"records": 128,
|
| 601 |
+
"tokens": 74688,
|
| 602 |
+
"first_record": 8832,
|
| 603 |
+
"last_record": 8959
|
| 604 |
+
},
|
| 605 |
+
{
|
| 606 |
+
"path": "shard_00070.pt",
|
| 607 |
+
"records": 128,
|
| 608 |
+
"tokens": 73448,
|
| 609 |
+
"first_record": 8960,
|
| 610 |
+
"last_record": 9087
|
| 611 |
+
},
|
| 612 |
+
{
|
| 613 |
+
"path": "shard_00071.pt",
|
| 614 |
+
"records": 128,
|
| 615 |
+
"tokens": 73684,
|
| 616 |
+
"first_record": 9088,
|
| 617 |
+
"last_record": 9215
|
| 618 |
+
},
|
| 619 |
+
{
|
| 620 |
+
"path": "shard_00072.pt",
|
| 621 |
+
"records": 128,
|
| 622 |
+
"tokens": 76147,
|
| 623 |
+
"first_record": 9216,
|
| 624 |
+
"last_record": 9343
|
| 625 |
+
},
|
| 626 |
+
{
|
| 627 |
+
"path": "shard_00073.pt",
|
| 628 |
+
"records": 128,
|
| 629 |
+
"tokens": 73607,
|
| 630 |
+
"first_record": 9344,
|
| 631 |
+
"last_record": 9471
|
| 632 |
+
},
|
| 633 |
+
{
|
| 634 |
+
"path": "shard_00074.pt",
|
| 635 |
+
"records": 128,
|
| 636 |
+
"tokens": 76658,
|
| 637 |
+
"first_record": 9472,
|
| 638 |
+
"last_record": 9599
|
| 639 |
+
},
|
| 640 |
+
{
|
| 641 |
+
"path": "shard_00075.pt",
|
| 642 |
+
"records": 128,
|
| 643 |
+
"tokens": 71052,
|
| 644 |
+
"first_record": 9600,
|
| 645 |
+
"last_record": 9727
|
| 646 |
+
},
|
| 647 |
+
{
|
| 648 |
+
"path": "shard_00076.pt",
|
| 649 |
+
"records": 128,
|
| 650 |
+
"tokens": 71839,
|
| 651 |
+
"first_record": 9728,
|
| 652 |
+
"last_record": 9855
|
| 653 |
+
},
|
| 654 |
+
{
|
| 655 |
+
"path": "shard_00077.pt",
|
| 656 |
+
"records": 128,
|
| 657 |
+
"tokens": 64648,
|
| 658 |
+
"first_record": 9856,
|
| 659 |
+
"last_record": 9983
|
| 660 |
+
},
|
| 661 |
+
{
|
| 662 |
+
"path": "shard_00078.pt",
|
| 663 |
+
"records": 128,
|
| 664 |
+
"tokens": 69436,
|
| 665 |
+
"first_record": 9984,
|
| 666 |
+
"last_record": 10111
|
| 667 |
+
},
|
| 668 |
+
{
|
| 669 |
+
"path": "shard_00079.pt",
|
| 670 |
+
"records": 128,
|
| 671 |
+
"tokens": 72194,
|
| 672 |
+
"first_record": 10112,
|
| 673 |
+
"last_record": 10239
|
| 674 |
+
},
|
| 675 |
+
{
|
| 676 |
+
"path": "shard_00080.pt",
|
| 677 |
+
"records": 128,
|
| 678 |
+
"tokens": 74293,
|
| 679 |
+
"first_record": 10240,
|
| 680 |
+
"last_record": 10367
|
| 681 |
+
},
|
| 682 |
+
{
|
| 683 |
+
"path": "shard_00081.pt",
|
| 684 |
+
"records": 128,
|
| 685 |
+
"tokens": 72618,
|
| 686 |
+
"first_record": 10368,
|
| 687 |
+
"last_record": 10495
|
| 688 |
+
},
|
| 689 |
+
{
|
| 690 |
+
"path": "shard_00082.pt",
|
| 691 |
+
"records": 128,
|
| 692 |
+
"tokens": 74951,
|
| 693 |
+
"first_record": 10496,
|
| 694 |
+
"last_record": 10623
|
| 695 |
+
},
|
| 696 |
+
{
|
| 697 |
+
"path": "shard_00083.pt",
|
| 698 |
+
"records": 128,
|
| 699 |
+
"tokens": 65989,
|
| 700 |
+
"first_record": 10624,
|
| 701 |
+
"last_record": 10751
|
| 702 |
+
},
|
| 703 |
+
{
|
| 704 |
+
"path": "shard_00084.pt",
|
| 705 |
+
"records": 128,
|
| 706 |
+
"tokens": 70265,
|
| 707 |
+
"first_record": 10752,
|
| 708 |
+
"last_record": 10879
|
| 709 |
+
},
|
| 710 |
+
{
|
| 711 |
+
"path": "shard_00085.pt",
|
| 712 |
+
"records": 128,
|
| 713 |
+
"tokens": 72357,
|
| 714 |
+
"first_record": 10880,
|
| 715 |
+
"last_record": 11007
|
| 716 |
+
},
|
| 717 |
+
{
|
| 718 |
+
"path": "shard_00086.pt",
|
| 719 |
+
"records": 128,
|
| 720 |
+
"tokens": 70381,
|
| 721 |
+
"first_record": 11008,
|
| 722 |
+
"last_record": 11135
|
| 723 |
+
},
|
| 724 |
+
{
|
| 725 |
+
"path": "shard_00087.pt",
|
| 726 |
+
"records": 128,
|
| 727 |
+
"tokens": 63801,
|
| 728 |
+
"first_record": 11136,
|
| 729 |
+
"last_record": 11263
|
| 730 |
+
},
|
| 731 |
+
{
|
| 732 |
+
"path": "shard_00088.pt",
|
| 733 |
+
"records": 128,
|
| 734 |
+
"tokens": 72738,
|
| 735 |
+
"first_record": 11264,
|
| 736 |
+
"last_record": 11391
|
| 737 |
+
},
|
| 738 |
+
{
|
| 739 |
+
"path": "shard_00089.pt",
|
| 740 |
+
"records": 128,
|
| 741 |
+
"tokens": 74195,
|
| 742 |
+
"first_record": 11392,
|
| 743 |
+
"last_record": 11519
|
| 744 |
+
},
|
| 745 |
+
{
|
| 746 |
+
"path": "shard_00090.pt",
|
| 747 |
+
"records": 128,
|
| 748 |
+
"tokens": 78693,
|
| 749 |
+
"first_record": 11520,
|
| 750 |
+
"last_record": 11647
|
| 751 |
+
},
|
| 752 |
+
{
|
| 753 |
+
"path": "shard_00091.pt",
|
| 754 |
+
"records": 128,
|
| 755 |
+
"tokens": 75694,
|
| 756 |
+
"first_record": 11648,
|
| 757 |
+
"last_record": 11775
|
| 758 |
+
},
|
| 759 |
+
{
|
| 760 |
+
"path": "shard_00092.pt",
|
| 761 |
+
"records": 128,
|
| 762 |
+
"tokens": 80262,
|
| 763 |
+
"first_record": 11776,
|
| 764 |
+
"last_record": 11903
|
| 765 |
+
},
|
| 766 |
+
{
|
| 767 |
+
"path": "shard_00093.pt",
|
| 768 |
+
"records": 128,
|
| 769 |
+
"tokens": 80246,
|
| 770 |
+
"first_record": 11904,
|
| 771 |
+
"last_record": 12031
|
| 772 |
+
},
|
| 773 |
+
{
|
| 774 |
+
"path": "shard_00094.pt",
|
| 775 |
+
"records": 83,
|
| 776 |
+
"tokens": 46892,
|
| 777 |
+
"first_record": 12032,
|
| 778 |
+
"last_record": 12114
|
| 779 |
+
}
|
| 780 |
+
],
|
| 781 |
+
"requested_records": 12115,
|
| 782 |
+
"source_records": 12115
|
| 783 |
+
}
|