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0000000000000000000000000000000000000000..b48e92697b80a0d2f30955b773f2675aaa2badf7 --- /dev/null +++ b/outputs/temporal_nope/a0_compact_artifact_smoke_seed0_kerrigan/resolved_config.yaml @@ -0,0 +1,133 @@ +independent_first_frame: false +warp_denoising_step: true +weight_decay: 0.01 +same_step_across_blocks: true +discriminator_lr_multiplier: 1.0 +last_step_only: false +i2v: false +num_training_frames: 21 +gc_interval: 100 +context_noise: 0 +causal: true +ckpt_step: 0 +prompt_name: MovieGenVideoBench +prompt_path: prompts/MovieGenVideoBench.txt +eval_first_n: 64 +num_samples: 1 +height: 480 +width: 832 +num_frames: 81 +experiment: + id: a0_compact_artifact_smoke_seed0_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: Original RoPE +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 1.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 +training: + enabled: false + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 2000 + checkpoint_steps: + - 0 + - 100 + - 250 + - 500 + - 1000 + - 2000 + optimizer: adamw + optimizer_reset: true + lr: 2.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a0_compact_artifact_smoke_seed0_kerrigan_rerun1/resolved_config.yaml b/outputs/temporal_nope/a0_compact_artifact_smoke_seed0_kerrigan_rerun1/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e2579f4dae21e55f4fc58e96037b2693a6722e6c --- /dev/null +++ b/outputs/temporal_nope/a0_compact_artifact_smoke_seed0_kerrigan_rerun1/resolved_config.yaml @@ -0,0 +1,133 @@ +independent_first_frame: false +warp_denoising_step: true +weight_decay: 0.01 +same_step_across_blocks: true +discriminator_lr_multiplier: 1.0 +last_step_only: false +i2v: false +num_training_frames: 21 +gc_interval: 100 +context_noise: 0 +causal: true +ckpt_step: 0 +prompt_name: MovieGenVideoBench +prompt_path: prompts/MovieGenVideoBench.txt +eval_first_n: 64 +num_samples: 1 +height: 480 +width: 832 +num_frames: 81 +experiment: + id: a0_compact_artifact_smoke_seed0_kerrigan_rerun1 + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: Original RoPE +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 1.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 +training: + enabled: false + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 2000 + checkpoint_steps: + - 0 + - 100 + - 250 + - 500 + - 1000 + - 2000 + optimizer: adamw + optimizer_reset: true + lr: 2.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_manifest.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_manifest.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bdfd917b44c1ea3108442002d238592eee714932 --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_manifest.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "type": "immutable_base_checkpoint_reference", "path": "/data/fengjiaqi/causal_forcing/checkpoints/framewise/causal_cd.pt", "checkpoint_key": "generator_ema", "sha256": "c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22", "optimizer_state": "reset"} +{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_model_000100/model.pt", "sha256": "1a2cdd3720e9823e69bc3542e83e0758e3e5ce235fd1d02fd12612259f04bb5f", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_model_000200/model.pt", "sha256": "026104aeeaa41d4df33f2d6289a002e734f286ac4ed160ccd7bcb33dbb906b57", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/resolved_config.yaml b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3febcdaa98da8e7437d0314b83816269a43fa3be --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/resolved_config.yaml @@ -0,0 +1,118 @@ +experiment: + id: a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1 + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: RoPE-CPT matched control +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 1.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 1.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/train.log b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/train.log new file mode 100644 index 0000000000000000000000000000000000000000..3008abe772da72a21d21f54b8683d44042f61ff2 --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/train.log @@ -0,0 +1,259 @@ +W0805 22:45:23.818000 2683199 site-packages/torch/distributed/run.py:793] +W0805 22:45:23.818000 2683199 site-packages/torch/distributed/run.py:793] ***************************************** +W0805 22:45:23.818000 2683199 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0805 22:45:23.818000 2683199 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank7]:[W805 22:45:34.911466922 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank2]:[W805 22:45:34.956285476 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank4]:[W805 22:45:34.086420255 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W805 22:45:34.106483647 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank1]:[W805 22:45:34.130572991 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank5]:[W805 22:45:34.133215750 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank6]:[W805 22:45:34.135853058 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank0]:[W805 22:45:34.477965848 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +DATASET TRAIN 6249 VALIDATION 256 SPLIT /home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json +validation step=0 loss=0.06264185 alpha=1.000000 samples=32 seconds=24.102 +step=1 loss=0.16898617 grad_norm=0.284459 alpha=1.000000 seconds=33.804 +step=2 loss=0.08548040 grad_norm=0.263723 alpha=1.000000 seconds=33.385 +step=3 loss=0.07998533 grad_norm=0.321230 alpha=1.000000 seconds=33.640 +step=4 loss=0.11531127 grad_norm=0.292704 alpha=1.000000 seconds=33.582 +step=5 loss=0.04095566 grad_norm=0.441111 alpha=1.000000 seconds=33.764 +step=6 loss=0.05031534 grad_norm=0.246053 alpha=1.000000 seconds=33.774 +step=7 loss=0.12238266 grad_norm=0.300544 alpha=1.000000 seconds=33.602 +step=8 loss=0.04164436 grad_norm=0.280257 alpha=1.000000 seconds=33.747 +step=9 loss=0.04078319 grad_norm=0.290209 alpha=1.000000 seconds=33.664 +step=10 loss=0.11827542 grad_norm=0.361131 alpha=1.000000 seconds=33.763 +step=11 loss=0.05484041 grad_norm=0.295932 alpha=1.000000 seconds=33.694 +step=12 loss=0.04062699 grad_norm=0.225317 alpha=1.000000 seconds=33.644 +step=13 loss=0.07193971 grad_norm=0.260246 alpha=1.000000 seconds=33.770 +step=14 loss=0.11812563 grad_norm=0.276972 alpha=1.000000 seconds=33.657 +step=15 loss=0.02560218 grad_norm=0.284253 alpha=1.000000 seconds=33.792 +step=16 loss=0.07697262 grad_norm=0.262389 alpha=1.000000 seconds=33.653 +step=17 loss=0.17103545 grad_norm=0.310579 alpha=1.000000 seconds=33.813 +step=18 loss=0.06112613 grad_norm=0.259268 alpha=1.000000 seconds=33.743 +step=19 loss=0.05431403 grad_norm=0.323605 alpha=1.000000 seconds=33.711 +step=20 loss=0.07360448 grad_norm=0.220407 alpha=1.000000 seconds=33.787 +step=21 loss=0.04034115 grad_norm=0.286446 alpha=1.000000 seconds=33.678 +step=22 loss=0.11012536 grad_norm=0.293315 alpha=1.000000 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loss=0.09064243 grad_norm=0.269070 alpha=1.000000 seconds=33.774 +step=37 loss=0.07698438 grad_norm=0.242023 alpha=1.000000 seconds=33.803 +step=38 loss=0.06099834 grad_norm=0.236653 alpha=1.000000 seconds=33.658 +step=39 loss=0.03180654 grad_norm=0.204874 alpha=1.000000 seconds=33.760 +step=40 loss=0.03417248 grad_norm=0.204233 alpha=1.000000 seconds=33.657 +step=41 loss=0.06671734 grad_norm=0.289587 alpha=1.000000 seconds=33.784 +step=42 loss=0.04921148 grad_norm=0.182852 alpha=1.000000 seconds=33.806 +step=43 loss=0.02129121 grad_norm=0.342663 alpha=1.000000 seconds=33.708 +step=44 loss=0.05286342 grad_norm=0.195751 alpha=1.000000 seconds=34.033 +step=45 loss=0.04283634 grad_norm=0.201901 alpha=1.000000 seconds=33.697 +step=46 loss=0.04427662 grad_norm=0.242933 alpha=1.000000 seconds=33.824 +step=47 loss=0.04108242 grad_norm=0.263488 alpha=1.000000 seconds=33.884 +step=48 loss=0.07543614 grad_norm=0.206035 alpha=1.000000 seconds=33.759 +step=49 loss=0.03876279 grad_norm=0.189900 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alpha=1.000000 seconds=33.824 +step=77 loss=0.04714613 grad_norm=0.160328 alpha=1.000000 seconds=33.884 +step=78 loss=0.07830883 grad_norm=0.143745 alpha=1.000000 seconds=33.765 +step=79 loss=0.05118145 grad_norm=0.173350 alpha=1.000000 seconds=33.906 +step=80 loss=0.05994939 grad_norm=0.212281 alpha=1.000000 seconds=33.756 +step=81 loss=0.05339732 grad_norm=0.112174 alpha=1.000000 seconds=33.827 +step=82 loss=0.03782009 grad_norm=0.152065 alpha=1.000000 seconds=33.874 +step=83 loss=0.04048533 grad_norm=0.141790 alpha=1.000000 seconds=33.734 +step=84 loss=0.12918428 grad_norm=0.159513 alpha=1.000000 seconds=33.853 +step=85 loss=0.03003350 grad_norm=0.178977 alpha=1.000000 seconds=33.741 +step=86 loss=0.02502121 grad_norm=0.142148 alpha=1.000000 seconds=33.786 +step=87 loss=0.03851255 grad_norm=0.180289 alpha=1.000000 seconds=33.875 +step=88 loss=0.06391578 grad_norm=0.177133 alpha=1.000000 seconds=33.727 +step=89 loss=0.14157489 grad_norm=0.157599 alpha=1.000000 seconds=33.846 +step=90 loss=0.09798670 grad_norm=0.172020 alpha=1.000000 seconds=33.725 +step=91 loss=0.04864128 grad_norm=0.156068 alpha=1.000000 seconds=33.812 +step=92 loss=0.02191806 grad_norm=0.152512 alpha=1.000000 seconds=33.878 +step=93 loss=0.02280365 grad_norm=0.150145 alpha=1.000000 seconds=33.712 +step=94 loss=0.13381891 grad_norm=0.156895 alpha=1.000000 seconds=33.877 +step=95 loss=0.02748231 grad_norm=0.138590 alpha=1.000000 seconds=33.720 +step=96 loss=0.18177110 grad_norm=0.160178 alpha=1.000000 seconds=33.818 +step=97 loss=0.12929425 grad_norm=0.149322 alpha=1.000000 seconds=33.837 +step=98 loss=0.08150952 grad_norm=0.234453 alpha=1.000000 seconds=33.701 +step=99 loss=0.04211010 grad_norm=0.159517 alpha=1.000000 seconds=33.885 +step=100 loss=0.07087896 grad_norm=0.133036 alpha=1.000000 seconds=33.708 +validation step=100 loss=0.05426692 alpha=1.000000 samples=32 seconds=23.308 +Start gathering distributed model states... +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states.../home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( + +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_model_000100/model.pt sha256=1a2cdd3720e9823e69bc3542e83e0758e3e5ce235fd1d02fd12612259f04bb5f +step=101 loss=0.06598934 grad_norm=0.151736 alpha=1.000000 seconds=33.348 +step=102 loss=0.03636648 grad_norm=0.098251 alpha=1.000000 seconds=33.861 +step=103 loss=0.07355691 grad_norm=0.117551 alpha=1.000000 seconds=33.708 +step=104 loss=0.17016563 grad_norm=0.194230 alpha=1.000000 seconds=33.812 +step=105 loss=0.02506783 grad_norm=0.111818 alpha=1.000000 seconds=33.811 +step=106 loss=0.02399110 grad_norm=0.192863 alpha=1.000000 seconds=33.683 +step=107 loss=0.03660506 grad_norm=0.181416 alpha=1.000000 seconds=33.818 +step=108 loss=0.06496543 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+validation step=200 loss=0.05151268 alpha=1.000000 samples=32 seconds=23.285 +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/checkpoint_model_000200/model.pt sha256=026104aeeaa41d4df33f2d6289a002e734f286ac4ed160ccd7bcb33dbb906b57 diff --git a/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/training_metrics.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/training_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..735573961277e685d7b7976e9cafdd6264ff8d4a --- /dev/null +++ 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0.10443528741598129, "temporal_rope_alpha": 1.0, "seconds_per_step": 33.884170055389404, "peak_memory_bytes": 22207118336} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/validation_metrics.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/validation_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e6b63268d67db63118b565cdfa408d037421532f --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr1e7_probe200_seed20260805_kerrigan_rerun1/validation_metrics.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "validation_loss": 0.06264185276813805, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 24.101814031600952, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 100, "validation_loss": 0.054266916238702834, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 23.307873010635376, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 200, "validation_loss": 0.05151267722249031, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 23.28480625152588, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a0a0fbed6d78955b45397308ea41ea190b03b167 --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "type": "immutable_base_checkpoint_reference", "path": "/data/fengjiaqi/causal_forcing/checkpoints/framewise/causal_cd.pt", "checkpoint_key": "generator_ema", "sha256": "c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22", "optimizer_state": "reset"} +{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt", "sha256": "ecc3f2d0dd47d812ba0cc58c252f4a75bf8051ea12bf1be3d2439d5cfe53b675", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt", "sha256": "24fb68a15b85bdd686990af64763ac2a23430f080979667a059c39c4aca083b3", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2e85b49d7dc369ab4342d00f8a9e2456bf05484f --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml @@ -0,0 +1,123 @@ +experiment: + id: a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: RoPE-CPT matched control +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 1.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 + target_visible_lengths: + - 21 + - 42 + - 84 + train_length: 21 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 2.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/train.log b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/train.log new file mode 100644 index 0000000000000000000000000000000000000000..f2aaad99847f58187e7e6ef71f84bb528dfde77a --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/train.log @@ -0,0 +1,259 @@ +W0806 17:49:07.823000 2947154 site-packages/torch/distributed/run.py:793] +W0806 17:49:07.823000 2947154 site-packages/torch/distributed/run.py:793] ***************************************** +W0806 17:49:07.823000 2947154 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0806 17:49:07.823000 2947154 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank1]:[W806 17:49:18.955023071 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank2]:[W806 17:49:18.132049069 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W806 17:49:18.161570839 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank4]:[W806 17:49:18.164929478 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank6]:[W806 17:49:18.189206043 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank5]:[W806 17:49:18.192128904 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank7]:[W806 17:49:18.215928452 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank0]:[W806 17:49:18.420630722 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +DATASET TRAIN 6249 VALIDATION 256 SPLIT /home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json +validation step=0 loss=0.06264185 alpha=1.000000 samples=32 seconds=22.796 +step=1 loss=0.16898617 grad_norm=0.284470 alpha=1.000000 seconds=33.868 +step=2 loss=0.08513896 grad_norm=0.261119 alpha=1.000000 seconds=33.740 +step=3 loss=0.07959563 grad_norm=0.312293 alpha=1.000000 seconds=34.054 +step=4 loss=0.11443653 grad_norm=0.284971 alpha=1.000000 seconds=34.042 +step=5 loss=0.04064651 grad_norm=0.425774 alpha=1.000000 seconds=34.140 +step=6 loss=0.04976147 grad_norm=0.236384 alpha=1.000000 seconds=34.075 +step=7 loss=0.12062521 grad_norm=0.284070 alpha=1.000000 seconds=34.156 +step=8 loss=0.04082027 grad_norm=0.261511 alpha=1.000000 seconds=34.211 +step=9 loss=0.03962434 grad_norm=0.265662 alpha=1.000000 seconds=34.057 +step=10 loss=0.11615936 grad_norm=0.335980 alpha=1.000000 seconds=34.225 +step=11 loss=0.05305076 grad_norm=0.281693 alpha=1.000000 seconds=33.985 +step=12 loss=0.03970905 grad_norm=0.200663 alpha=1.000000 seconds=34.176 +step=13 loss=0.06967629 grad_norm=0.229631 alpha=1.000000 seconds=34.170 +step=14 loss=0.11563975 grad_norm=0.241843 alpha=1.000000 seconds=34.034 +step=15 loss=0.02488876 grad_norm=0.250904 alpha=1.000000 seconds=34.192 +step=16 loss=0.07521610 grad_norm=0.237391 alpha=1.000000 seconds=34.006 +step=17 loss=0.16371337 grad_norm=0.270859 alpha=1.000000 seconds=34.150 +step=18 loss=0.05890699 grad_norm=0.220638 alpha=1.000000 seconds=33.981 +step=19 loss=0.05286266 grad_norm=0.277821 alpha=1.000000 seconds=34.146 +step=20 loss=0.07062636 grad_norm=0.185382 alpha=1.000000 seconds=34.175 +step=21 loss=0.03902369 grad_norm=0.240528 alpha=1.000000 seconds=34.089 +step=22 loss=0.10551379 grad_norm=0.245557 alpha=1.000000 seconds=34.162 +step=23 loss=0.05413212 grad_norm=0.198393 alpha=1.000000 seconds=34.126 +step=24 loss=0.03406988 grad_norm=0.212565 alpha=1.000000 seconds=33.970 +step=25 loss=0.03315390 grad_norm=0.219684 alpha=1.000000 seconds=34.106 +step=26 loss=0.05008332 grad_norm=0.181928 alpha=1.000000 seconds=34.008 +step=27 loss=0.10540730 grad_norm=0.187404 alpha=1.000000 seconds=34.127 +step=28 loss=0.04535390 grad_norm=0.165760 alpha=1.000000 seconds=34.026 +step=29 loss=0.09677438 grad_norm=0.168555 alpha=1.000000 seconds=34.147 +step=30 loss=0.04175425 grad_norm=0.234756 alpha=1.000000 seconds=34.236 +step=31 loss=0.12048307 grad_norm=0.235767 alpha=1.000000 seconds=34.018 +step=32 loss=0.02301337 grad_norm=0.185881 alpha=1.000000 seconds=34.201 +step=33 loss=0.02989142 grad_norm=0.247023 alpha=1.000000 seconds=34.216 +step=34 loss=0.08201148 grad_norm=0.169942 alpha=1.000000 seconds=34.050 +step=35 loss=0.04240957 grad_norm=0.144560 alpha=1.000000 seconds=34.242 +step=36 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alpha=1.000000 seconds=33.973 +step=77 loss=0.04444459 grad_norm=0.114136 alpha=1.000000 seconds=34.128 +step=78 loss=0.07466266 grad_norm=0.099356 alpha=1.000000 seconds=33.944 +step=79 loss=0.04883490 grad_norm=0.127264 alpha=1.000000 seconds=34.086 +step=80 loss=0.05724190 grad_norm=0.144419 alpha=1.000000 seconds=34.056 +step=81 loss=0.05025553 grad_norm=0.072601 alpha=1.000000 seconds=33.994 +step=82 loss=0.03589023 grad_norm=0.101742 alpha=1.000000 seconds=34.119 +step=83 loss=0.03847847 grad_norm=0.101503 alpha=1.000000 seconds=34.102 +step=84 loss=0.12212365 grad_norm=0.109178 alpha=1.000000 seconds=33.946 +step=85 loss=0.02872832 grad_norm=0.136833 alpha=1.000000 seconds=34.063 +step=86 loss=0.02311257 grad_norm=0.099010 alpha=1.000000 seconds=33.906 +step=87 loss=0.03565622 grad_norm=0.115263 alpha=1.000000 seconds=34.115 +step=88 loss=0.06111155 grad_norm=0.123879 alpha=1.000000 seconds=33.951 +step=89 loss=0.13542603 grad_norm=0.113852 alpha=1.000000 seconds=34.081 +step=90 loss=0.09270129 grad_norm=0.115964 alpha=1.000000 seconds=34.137 +step=91 loss=0.04497743 grad_norm=0.110884 alpha=1.000000 seconds=33.975 +step=92 loss=0.02086187 grad_norm=0.103153 alpha=1.000000 seconds=34.114 +step=93 loss=0.02145690 grad_norm=0.105451 alpha=1.000000 seconds=34.108 +step=94 loss=0.12779032 grad_norm=0.105955 alpha=1.000000 seconds=33.926 +step=95 loss=0.02601034 grad_norm=0.092761 alpha=1.000000 seconds=34.058 +step=96 loss=0.17284752 grad_norm=0.115497 alpha=1.000000 seconds=33.951 +step=97 loss=0.12222225 grad_norm=0.112921 alpha=1.000000 seconds=34.111 +step=98 loss=0.07713963 grad_norm=0.153858 alpha=1.000000 seconds=33.944 +step=99 loss=0.03956973 grad_norm=0.107386 alpha=1.000000 seconds=34.075 +step=100 loss=0.06718601 grad_norm=0.084812 alpha=1.000000 seconds=34.071 +validation step=100 loss=0.05149416 alpha=1.000000 samples=32 seconds=23.614 +Start gathering distributed model states... +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +Start gathering distributed model states...Start gathering distributed model states... + +Start gathering distributed model states...Start gathering distributed model states.../home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( + + +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt sha256=ecc3f2d0dd47d812ba0cc58c252f4a75bf8051ea12bf1be3d2439d5cfe53b675 +step=101 loss=0.06273130 grad_norm=0.111810 alpha=1.000000 seconds=33.361 +step=102 loss=0.03461096 grad_norm=0.060189 alpha=1.000000 seconds=34.063 +step=103 loss=0.06924274 grad_norm=0.073391 alpha=1.000000 seconds=33.967 +step=104 loss=0.16222589 grad_norm=0.130340 alpha=1.000000 seconds=34.070 +step=105 loss=0.02396709 grad_norm=0.069984 alpha=1.000000 seconds=33.944 +step=106 loss=0.02275083 grad_norm=0.132807 alpha=1.000000 seconds=34.117 +step=107 loss=0.03428217 grad_norm=0.095892 alpha=1.000000 seconds=34.130 +step=108 loss=0.06227133 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+validation step=200 loss=0.04925254 alpha=1.000000 samples=32 seconds=23.490 +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt sha256=24fb68a15b85bdd686990af64763ac2a23430f080979667a059c39c4aca083b3 diff --git a/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/training_metrics.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/training_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c45884c9a50340be3e7522a8fdbcd9940533b157 --- /dev/null +++ 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"temporal_rope_alpha": 1.0, "seconds_per_step": 33.90160274505615, "peak_memory_bytes": 22207118336} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1c0cab2d5fe994e0cf62f57f785c509d78a896f0 --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr2e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "validation_loss": 0.06264185276813805, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 22.795755624771118, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 100, "validation_loss": 0.0514941630535759, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 23.613961696624756, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 200, "validation_loss": 0.04925253620604053, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 23.490389347076416, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl b/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c3cdbad3e4876d9223fcffc96baa296768b4318e --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "type": "immutable_base_checkpoint_reference", "path": "/data/fengjiaqi/causal_forcing/checkpoints/framewise/causal_cd.pt", "checkpoint_key": "generator_ema", "sha256": "c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22", "optimizer_state": "reset"} +{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt", "sha256": "c2c5fd1ddaf1431579e3f359e073f99e1b827ab450978dbf513434a5e52b7274", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt", "sha256": "c7728fb87b982489db2e718a8c7653882a2133dded77660b1cd804daf741a850", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/resolved_config.yaml b/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..006a52a644373989b922860808e0410c8f594978 --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/resolved_config.yaml @@ -0,0 +1,123 @@ +experiment: + id: a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: RoPE-CPT matched control +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 1.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 + target_visible_lengths: + - 21 + - 42 + - 84 + train_length: 21 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 4.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/train.log b/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/train.log new file mode 100644 index 0000000000000000000000000000000000000000..c2dfa817c6f6cd8ea197caeb9847310f2eee1fb7 --- /dev/null +++ b/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/train.log @@ -0,0 +1,259 @@ +W0807 00:09:47.490000 3156067 site-packages/torch/distributed/run.py:793] +W0807 00:09:47.490000 3156067 site-packages/torch/distributed/run.py:793] ***************************************** +W0807 00:09:47.490000 3156067 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0807 00:09:47.490000 3156067 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank2]:[W807 00:09:57.868371707 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank4]:[W807 00:09:57.003604158 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank7]:[W807 00:09:57.611702039 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank1]:[W807 00:09:58.742944031 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W807 00:09:58.759281662 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank5]:[W807 00:09:58.760208407 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank6]:[W807 00:09:58.821308742 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank0]:[W807 00:09:58.087043608 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +DATASET TRAIN 6249 VALIDATION 256 SPLIT /home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json +validation step=0 loss=0.06264185 alpha=1.000000 samples=32 seconds=22.588 +step=1 loss=0.16898617 grad_norm=0.284440 alpha=1.000000 seconds=33.824 +step=2 loss=0.08452399 grad_norm=0.259132 alpha=1.000000 seconds=33.455 +step=3 loss=0.07878885 grad_norm=0.292787 alpha=1.000000 seconds=33.788 +step=4 loss=0.11278746 grad_norm=0.269995 alpha=1.000000 seconds=33.687 +step=5 loss=0.03989964 grad_norm=0.397074 alpha=1.000000 seconds=33.899 +step=6 loss=0.04870192 grad_norm=0.216642 alpha=1.000000 seconds=33.751 +step=7 loss=0.11759949 grad_norm=0.248604 alpha=1.000000 seconds=33.909 +step=8 loss=0.03943404 grad_norm=0.221221 alpha=1.000000 seconds=33.923 +step=9 loss=0.03800571 grad_norm=0.227170 alpha=1.000000 seconds=33.761 +step=10 loss=0.11269060 grad_norm=0.293723 alpha=1.000000 seconds=33.897 +step=11 loss=0.05024400 grad_norm=0.219113 alpha=1.000000 seconds=33.797 +step=12 loss=0.03831534 grad_norm=0.164259 alpha=1.000000 seconds=33.976 +step=13 loss=0.06634291 grad_norm=0.187611 alpha=1.000000 seconds=33.917 +step=14 loss=0.11188487 grad_norm=0.195986 alpha=1.000000 seconds=33.759 +step=15 loss=0.02364512 grad_norm=0.201556 alpha=1.000000 seconds=33.888 +step=16 loss=0.07214804 grad_norm=0.190197 alpha=1.000000 seconds=33.721 +step=17 loss=0.15304582 grad_norm=0.201078 alpha=1.000000 seconds=33.975 +step=18 loss=0.05604922 grad_norm=0.162735 alpha=1.000000 seconds=33.732 +step=19 loss=0.05080383 grad_norm=0.216206 alpha=1.000000 seconds=33.951 +step=20 loss=0.06704846 grad_norm=0.137741 alpha=1.000000 seconds=33.920 +step=21 loss=0.03732525 grad_norm=0.180131 alpha=1.000000 seconds=33.776 +step=22 loss=0.09984197 grad_norm=0.172156 alpha=1.000000 seconds=33.917 +step=23 loss=0.05177775 grad_norm=0.149101 alpha=1.000000 seconds=33.911 +step=24 loss=0.03230783 grad_norm=0.152521 alpha=1.000000 seconds=33.738 +step=25 loss=0.03134595 grad_norm=0.161357 alpha=1.000000 seconds=33.875 +step=26 loss=0.04738880 grad_norm=0.123898 alpha=1.000000 seconds=33.714 +step=27 loss=0.10072595 grad_norm=0.122465 alpha=1.000000 seconds=33.849 +step=28 loss=0.04306233 grad_norm=0.119941 alpha=1.000000 seconds=33.678 +step=29 loss=0.09208241 grad_norm=0.109408 alpha=1.000000 seconds=33.800 +step=30 loss=0.04000646 grad_norm=0.162170 alpha=1.000000 seconds=33.814 +step=31 loss=0.11359677 grad_norm=0.154410 alpha=1.000000 seconds=33.668 +step=32 loss=0.02177077 grad_norm=0.123483 alpha=1.000000 seconds=33.847 +step=33 loss=0.02864378 grad_norm=0.172702 alpha=1.000000 seconds=33.836 +step=34 loss=0.07808723 grad_norm=0.120447 alpha=1.000000 seconds=33.670 +step=35 loss=0.04009277 grad_norm=0.097723 alpha=1.000000 seconds=33.826 +step=36 loss=0.08138657 grad_norm=0.157169 alpha=1.000000 seconds=33.690 +step=37 loss=0.06744611 grad_norm=0.126092 alpha=1.000000 seconds=33.876 +step=38 loss=0.05399023 grad_norm=0.116229 alpha=1.000000 seconds=33.684 +step=39 loss=0.02866815 grad_norm=0.104800 alpha=1.000000 seconds=33.752 +step=40 loss=0.03080152 grad_norm=0.097288 alpha=1.000000 seconds=33.803 +step=41 loss=0.06157399 grad_norm=0.158684 alpha=1.000000 seconds=33.668 +step=42 loss=0.04387537 grad_norm=0.088382 alpha=1.000000 seconds=33.819 +step=43 loss=0.01868118 grad_norm=0.159113 alpha=1.000000 seconds=33.816 +step=44 loss=0.04954329 grad_norm=0.098418 alpha=1.000000 seconds=33.667 +step=45 loss=0.03947054 grad_norm=0.103766 alpha=1.000000 seconds=33.831 +step=46 loss=0.04017525 grad_norm=0.116644 alpha=1.000000 seconds=33.659 +step=47 loss=0.03709484 grad_norm=0.120793 alpha=1.000000 seconds=33.795 +step=48 loss=0.06521133 grad_norm=0.091717 alpha=1.000000 seconds=33.648 +step=49 loss=0.03468918 grad_norm=0.092241 alpha=1.000000 seconds=33.769 +step=50 loss=0.06914529 grad_norm=0.095890 alpha=1.000000 seconds=33.774 +step=51 loss=0.03005695 grad_norm=0.164944 alpha=1.000000 seconds=33.686 +step=52 loss=0.02717197 grad_norm=0.127388 alpha=1.000000 seconds=33.904 +step=53 loss=0.04516433 grad_norm=0.093121 alpha=1.000000 seconds=33.852 +step=54 loss=0.02781375 grad_norm=0.089038 alpha=1.000000 seconds=33.704 +step=55 loss=0.07292852 grad_norm=0.083980 alpha=1.000000 seconds=33.829 +step=56 loss=0.07090893 grad_norm=0.081273 alpha=1.000000 seconds=33.704 +step=57 loss=0.03508367 grad_norm=0.085408 alpha=1.000000 seconds=33.847 +step=58 loss=0.03228186 grad_norm=0.067989 alpha=1.000000 seconds=33.702 +step=59 loss=0.11147559 grad_norm=0.094198 alpha=1.000000 seconds=33.789 +step=60 loss=0.07833828 grad_norm=0.078146 alpha=1.000000 seconds=33.780 +step=61 loss=0.06684589 grad_norm=0.118361 alpha=1.000000 seconds=33.731 +step=62 loss=0.09972247 grad_norm=0.103581 alpha=1.000000 seconds=33.782 +step=63 loss=0.06998573 grad_norm=0.081561 alpha=1.000000 seconds=33.805 +step=64 loss=0.05400852 grad_norm=0.070429 alpha=1.000000 seconds=33.671 +step=65 loss=0.02168166 grad_norm=0.090696 alpha=1.000000 seconds=33.784 +step=66 loss=0.02514420 grad_norm=0.088192 alpha=1.000000 seconds=33.634 +step=67 loss=0.01399644 grad_norm=0.062871 alpha=1.000000 seconds=33.753 +step=68 loss=0.10250673 grad_norm=0.087630 alpha=1.000000 seconds=33.626 +step=69 loss=0.06609512 grad_norm=0.115754 alpha=1.000000 seconds=33.753 +step=70 loss=0.03636727 grad_norm=0.084714 alpha=1.000000 seconds=33.740 +step=71 loss=0.03416704 grad_norm=0.087931 alpha=1.000000 seconds=33.643 +step=72 loss=0.03955406 grad_norm=0.060765 alpha=1.000000 seconds=33.837 +step=73 loss=0.16107559 grad_norm=0.139679 alpha=1.000000 seconds=33.828 +step=74 loss=0.07246853 grad_norm=0.090469 alpha=1.000000 seconds=33.652 +step=75 loss=0.08827275 grad_norm=0.072928 alpha=1.000000 seconds=33.807 +step=76 loss=0.02481812 grad_norm=0.083885 alpha=1.000000 seconds=33.674 +step=77 loss=0.04250994 grad_norm=0.081548 alpha=1.000000 seconds=33.842 +step=78 loss=0.07153207 grad_norm=0.076064 alpha=1.000000 seconds=33.645 +step=79 loss=0.04667780 grad_norm=0.082680 alpha=1.000000 seconds=33.805 +step=80 loss=0.05478448 grad_norm=0.101728 alpha=1.000000 seconds=33.838 +step=81 loss=0.04710114 grad_norm=0.049445 alpha=1.000000 seconds=33.714 +step=82 loss=0.03440228 grad_norm=0.068088 alpha=1.000000 seconds=33.891 +step=83 loss=0.03663286 grad_norm=0.071631 alpha=1.000000 seconds=33.874 +step=84 loss=0.11668413 grad_norm=0.077906 alpha=1.000000 seconds=33.718 +step=85 loss=0.02754003 grad_norm=0.102958 alpha=1.000000 seconds=33.905 +step=86 loss=0.02144641 grad_norm=0.072169 alpha=1.000000 seconds=33.753 +step=87 loss=0.03314152 grad_norm=0.075109 alpha=1.000000 seconds=33.892 +step=88 loss=0.05843190 grad_norm=0.078377 alpha=1.000000 seconds=33.756 +step=89 loss=0.13036843 grad_norm=0.077829 alpha=1.000000 seconds=33.896 +step=90 loss=0.08905555 grad_norm=0.078515 alpha=1.000000 seconds=33.897 +step=91 loss=0.04199139 grad_norm=0.087249 alpha=1.000000 seconds=33.783 +step=92 loss=0.01975280 grad_norm=0.069604 alpha=1.000000 seconds=33.979 +step=93 loss=0.02038187 grad_norm=0.060615 alpha=1.000000 seconds=33.955 +step=94 loss=0.12310946 grad_norm=0.070583 alpha=1.000000 seconds=33.791 +step=95 loss=0.02475277 grad_norm=0.063172 alpha=1.000000 seconds=33.939 +step=96 loss=0.16603900 grad_norm=0.091364 alpha=1.000000 seconds=33.784 +step=97 loss=0.11731795 grad_norm=0.084316 alpha=1.000000 seconds=33.960 +step=98 loss=0.07396284 grad_norm=0.097570 alpha=1.000000 seconds=33.821 +step=99 loss=0.03720766 grad_norm=0.078341 alpha=1.000000 seconds=33.934 +step=100 loss=0.06482805 grad_norm=0.053541 alpha=1.000000 seconds=33.960 +validation step=100 loss=0.04924947 alpha=1.000000 samples=32 seconds=23.571 +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +Start gathering distributed model states...Start gathering distributed model states... + +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt sha256=c2c5fd1ddaf1431579e3f359e073f99e1b827ab450978dbf513434a5e52b7274 +step=101 loss=0.06047313 grad_norm=0.101640 alpha=1.000000 seconds=33.314 +step=102 loss=0.03314419 grad_norm=0.039925 alpha=1.000000 seconds=34.032 +step=103 loss=0.06584981 grad_norm=0.051526 alpha=1.000000 seconds=33.911 +step=104 loss=0.15614165 grad_norm=0.090788 alpha=1.000000 seconds=33.992 +step=105 loss=0.02304491 grad_norm=0.048750 alpha=1.000000 seconds=33.877 +step=106 loss=0.02174317 grad_norm=0.109381 alpha=1.000000 seconds=33.927 +step=107 loss=0.03242185 grad_norm=0.068463 alpha=1.000000 seconds=33.929 +step=108 loss=0.05999056 grad_norm=0.074218 alpha=1.000000 seconds=33.806 +step=109 loss=0.20279367 grad_norm=0.073653 alpha=1.000000 seconds=33.885 +step=110 loss=0.02755656 grad_norm=0.058382 alpha=1.000000 seconds=33.816 +step=111 loss=0.06812301 grad_norm=0.063358 alpha=1.000000 seconds=33.935 +step=112 loss=0.12751798 grad_norm=0.086588 alpha=1.000000 seconds=33.922 +step=113 loss=0.11873177 grad_norm=0.119058 alpha=1.000000 seconds=33.726 +step=114 loss=0.03264400 grad_norm=0.059145 alpha=1.000000 seconds=33.812 +step=115 loss=0.05770464 grad_norm=0.083270 alpha=1.000000 seconds=33.777 +step=116 loss=0.02914092 grad_norm=0.060887 alpha=1.000000 seconds=33.882 +step=117 loss=0.09453064 grad_norm=0.064526 alpha=1.000000 seconds=33.736 +step=118 loss=0.02094099 grad_norm=0.097403 alpha=1.000000 seconds=33.899 +step=119 loss=0.05481850 grad_norm=0.063041 alpha=1.000000 seconds=33.865 +step=120 loss=0.05235299 grad_norm=0.068656 alpha=1.000000 seconds=33.737 +step=121 loss=0.03724409 grad_norm=0.062908 alpha=1.000000 seconds=33.884 +step=122 loss=0.02299210 grad_norm=0.089691 alpha=1.000000 seconds=33.736 +step=123 loss=0.06395182 grad_norm=0.048005 alpha=1.000000 seconds=33.923 +step=124 loss=0.02509362 grad_norm=0.055295 alpha=1.000000 seconds=33.764 +step=125 loss=0.09612519 grad_norm=0.076681 alpha=1.000000 seconds=33.949 +step=126 loss=0.15624148 grad_norm=0.060934 alpha=1.000000 seconds=33.901 +step=127 loss=0.06359946 grad_norm=0.047415 alpha=1.000000 seconds=33.751 +step=128 loss=0.03499567 grad_norm=0.048506 alpha=1.000000 seconds=33.868 +step=129 loss=0.06494656 grad_norm=0.071666 alpha=1.000000 seconds=33.695 +step=130 loss=0.04831227 grad_norm=0.055034 alpha=1.000000 seconds=33.875 +step=131 loss=0.06111163 grad_norm=0.054629 alpha=1.000000 seconds=33.718 +step=132 loss=0.03500751 grad_norm=0.057663 alpha=1.000000 seconds=33.823 +step=133 loss=0.09345834 grad_norm=0.076068 alpha=1.000000 seconds=33.696 +step=134 loss=0.08717439 grad_norm=0.068667 alpha=1.000000 seconds=33.840 +step=135 loss=0.03031836 grad_norm=0.056907 alpha=1.000000 seconds=33.925 +step=136 loss=0.04779136 grad_norm=0.045026 alpha=1.000000 seconds=33.704 +step=137 loss=0.09216212 grad_norm=0.084991 alpha=1.000000 seconds=33.813 +step=138 loss=0.11667968 grad_norm=0.055501 alpha=1.000000 seconds=33.717 +step=139 loss=0.03757762 grad_norm=0.062936 alpha=1.000000 seconds=33.866 +step=140 loss=0.01502442 grad_norm=0.075720 alpha=1.000000 seconds=33.838 +step=141 loss=0.04696148 grad_norm=0.061885 alpha=1.000000 seconds=33.716 +step=142 loss=0.09654515 grad_norm=0.055182 alpha=1.000000 seconds=33.790 +step=143 loss=0.03018590 grad_norm=0.090426 alpha=1.000000 seconds=33.756 +step=144 loss=0.02311911 grad_norm=0.089579 alpha=1.000000 seconds=33.876 +step=145 loss=0.07085357 grad_norm=0.041061 alpha=1.000000 seconds=33.733 +step=146 loss=0.01922528 grad_norm=0.119706 alpha=1.000000 seconds=33.876 +step=147 loss=0.04984973 grad_norm=0.047553 alpha=1.000000 seconds=33.808 +step=148 loss=0.07071530 grad_norm=0.043429 alpha=1.000000 seconds=33.759 +step=149 loss=0.03286100 grad_norm=0.071598 alpha=1.000000 seconds=33.839 +step=150 loss=0.06808022 grad_norm=0.063889 alpha=1.000000 seconds=33.705 +step=151 loss=0.03252810 grad_norm=0.046533 alpha=1.000000 seconds=33.856 +step=152 loss=0.14236210 grad_norm=0.059039 alpha=1.000000 seconds=33.757 +step=153 loss=0.03068572 grad_norm=0.038693 alpha=1.000000 seconds=33.836 +step=154 loss=0.01450500 grad_norm=0.050424 alpha=1.000000 seconds=33.817 +step=155 loss=0.03293972 grad_norm=0.047150 alpha=1.000000 seconds=33.659 +step=156 loss=0.03323923 grad_norm=0.063373 alpha=1.000000 seconds=33.809 +step=157 loss=0.03337437 grad_norm=0.054688 alpha=1.000000 seconds=33.695 +step=158 loss=0.05103671 grad_norm=0.062788 alpha=1.000000 seconds=33.824 +step=159 loss=0.01945036 grad_norm=0.046738 alpha=1.000000 seconds=33.696 +step=160 loss=0.02356442 grad_norm=0.046201 alpha=1.000000 seconds=33.788 +step=161 loss=0.04674975 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seconds=33.800 +step=188 loss=0.05764690 grad_norm=0.043085 alpha=1.000000 seconds=33.666 +step=189 loss=0.03093739 grad_norm=0.074260 alpha=1.000000 seconds=33.775 +step=190 loss=0.07192354 grad_norm=0.080684 alpha=1.000000 seconds=33.632 +step=191 loss=0.02779631 grad_norm=0.034895 alpha=1.000000 seconds=33.793 +step=192 loss=0.02213561 grad_norm=0.038625 alpha=1.000000 seconds=33.811 +step=193 loss=0.05410427 grad_norm=0.099049 alpha=1.000000 seconds=33.653 +step=194 loss=0.08320453 grad_norm=0.080664 alpha=1.000000 seconds=33.801 +step=195 loss=0.05623063 grad_norm=0.066331 alpha=1.000000 seconds=33.647 +step=196 loss=0.04387650 grad_norm=0.067425 alpha=1.000000 seconds=33.828 +step=197 loss=0.07663434 grad_norm=0.071194 alpha=1.000000 seconds=33.694 +step=198 loss=0.11742631 grad_norm=0.129569 alpha=1.000000 seconds=33.851 +step=199 loss=0.02272441 grad_norm=0.078225 alpha=1.000000 seconds=33.942 +step=200 loss=0.03442148 grad_norm=0.061388 alpha=1.000000 seconds=33.682 +validation step=200 loss=0.04765816 alpha=1.000000 samples=32 seconds=23.295 +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a1_rope_cpt_lr4e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt sha256=c7728fb87b982489db2e718a8c7653882a2133dded77660b1cd804daf741a850 diff --git a/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..dc41f6f1e30332171b20d2e76948685aaa2c729d --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "type": "immutable_base_checkpoint_reference", "path": "/data/fengjiaqi/causal_forcing/checkpoints/framewise/causal_cd.pt", "checkpoint_key": "generator_ema", "sha256": "c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22", "optimizer_state": "reset"} +{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt", "sha256": "4213a600500a2da1b8698e8cd81d7667925097753abea35f8f799aca605d0d99", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt", "sha256": "cdca71bccd2f76b94120fc51ede62931841283d3a5fd414ad87f5095c0a7ff74", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/resolved_config.yaml b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cb487067e7025c9a5ca3a2c53057629df7ba120b --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/resolved_config.yaml @@ -0,0 +1,123 @@ +experiment: + id: a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: Hard Temporal DroPE +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: none + temporal_rope_alpha: 0.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 + target_visible_lengths: + - 21 + - 42 + - 84 + train_length: 21 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 1.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/train.log b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/train.log new file mode 100644 index 0000000000000000000000000000000000000000..420efa9d516dc2b732e4adb1933d9dbca651e738 --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/train.log @@ -0,0 +1,259 @@ +W0806 13:33:39.419000 2847191 site-packages/torch/distributed/run.py:793] +W0806 13:33:39.419000 2847191 site-packages/torch/distributed/run.py:793] ***************************************** +W0806 13:33:39.419000 2847191 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0806 13:33:39.419000 2847191 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank1]:[W806 13:33:48.318119518 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank4]:[W806 13:33:49.324686130 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank7]:[W806 13:33:49.341972336 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank6]:[W806 13:33:49.364484262 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank2]:[W806 13:33:49.389167570 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W806 13:33:49.438788336 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank5]:[W806 13:33:49.464334781 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank0]:[W806 13:33:49.626436129 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +DATASET TRAIN 6249 VALIDATION 256 SPLIT /home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json +validation step=0 loss=0.26354822 alpha=0.000000 samples=32 seconds=22.944 +step=1 loss=0.75935781 grad_norm=2.223690 alpha=0.000000 seconds=33.455 +step=2 loss=0.60527384 grad_norm=2.966155 alpha=0.000000 seconds=33.660 +step=3 loss=0.35504434 grad_norm=2.872042 alpha=0.000000 seconds=34.018 +step=4 loss=0.44725409 grad_norm=2.800238 alpha=0.000000 seconds=33.949 +step=5 loss=0.13983518 grad_norm=2.238496 alpha=0.000000 seconds=34.141 +step=6 loss=0.15167883 grad_norm=2.219674 alpha=0.000000 seconds=34.030 +step=7 loss=0.56869608 grad_norm=2.971950 alpha=0.000000 seconds=34.180 +step=8 loss=0.32047978 grad_norm=2.339395 alpha=0.000000 seconds=34.093 +step=9 loss=0.20799437 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loss=0.34770143 grad_norm=1.513935 alpha=0.000000 seconds=34.187 +step=91 loss=0.14166974 grad_norm=1.477237 alpha=0.000000 seconds=33.982 +step=92 loss=0.09116819 grad_norm=2.111791 alpha=0.000000 seconds=34.117 +step=93 loss=0.09987239 grad_norm=1.069182 alpha=0.000000 seconds=34.131 +step=94 loss=0.47033310 grad_norm=1.622569 alpha=0.000000 seconds=33.988 +step=95 loss=0.06501450 grad_norm=1.577457 alpha=0.000000 seconds=34.098 +step=96 loss=0.51227808 grad_norm=1.711941 alpha=0.000000 seconds=34.064 +step=97 loss=0.44193295 grad_norm=1.372194 alpha=0.000000 seconds=34.153 +step=98 loss=0.21266872 grad_norm=2.357080 alpha=0.000000 seconds=34.002 +step=99 loss=0.12523443 grad_norm=2.306888 alpha=0.000000 seconds=34.163 +step=100 loss=0.19680248 grad_norm=1.714960 alpha=0.000000 seconds=34.125 +validation step=100 loss=0.19042654 alpha=0.000000 samples=32 seconds=23.483 +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states.../home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( + +Start gathering distributed model states.../home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( + +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt sha256=4213a600500a2da1b8698e8cd81d7667925097753abea35f8f799aca605d0d99 +step=101 loss=0.27869985 grad_norm=2.395654 alpha=0.000000 seconds=33.510 +step=102 loss=0.16974846 grad_norm=1.247127 alpha=0.000000 seconds=34.118 +step=103 loss=0.11542259 grad_norm=1.250616 alpha=0.000000 seconds=33.996 +step=104 loss=0.54958230 grad_norm=2.166646 alpha=0.000000 seconds=34.158 +step=105 loss=0.07991378 grad_norm=1.552543 alpha=0.000000 seconds=33.985 +step=106 loss=0.07704064 grad_norm=2.321823 alpha=0.000000 seconds=34.125 +step=107 loss=0.09948509 grad_norm=1.275812 alpha=0.000000 seconds=34.097 +step=108 loss=0.25519207 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+validation step=200 loss=0.14632052 alpha=0.000000 samples=32 seconds=23.644 +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states...Start gathering distributed model states... + +Start gathering distributed model states... +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt sha256=cdca71bccd2f76b94120fc51ede62931841283d3a5fd414ad87f5095c0a7ff74 diff --git a/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/training_metrics.jsonl b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/training_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..90fcf140dbdcca4292f94af7f81546f4e2a45c31 --- /dev/null +++ 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a/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ee890daa6791a4f76ab4c0f6980b0acc07cf7ce2 --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr1e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "validation_loss": 0.2635482151526958, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 22.943557262420654, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 100, "validation_loss": 0.19042654358781874, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 23.483413219451904, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 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+{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt", "sha256": "9c73b32512466e1761498cc9b47616c7ad7e4ceb6a8fbf930bb9dffc4e51c348", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt", "sha256": "474a2d6d0e092c5eac9bd73b7dc6d9fae848f02ca555abcd425135269a764b55", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml b/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7bfae582a563d139d25418f550fffa48c734fbe5 --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml @@ -0,0 +1,123 @@ +experiment: + id: a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: Hard Temporal DroPE +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: none + temporal_rope_alpha: 0.0 + temporal_rope_schedule: constant + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 0 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 + target_visible_lengths: + - 21 + - 42 + - 84 + train_length: 21 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 2.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/train.log b/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/train.log new file mode 100644 index 0000000000000000000000000000000000000000..028500e40aac131bf66420d6ccf88ace9bba2c33 --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/train.log @@ -0,0 +1,259 @@ +W0806 19:54:01.441000 3024960 site-packages/torch/distributed/run.py:793] +W0806 19:54:01.441000 3024960 site-packages/torch/distributed/run.py:793] ***************************************** +W0806 19:54:01.441000 3024960 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0806 19:54:01.441000 3024960 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank4]:[W806 19:54:11.623620111 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank1]:[W806 19:54:11.642578112 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank5]:[W806 19:54:12.676204611 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank2]:[W806 19:54:12.697532734 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W806 19:54:12.713233027 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank6]:[W806 19:54:12.722431614 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank7]:[W806 19:54:12.740894497 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank0]:[W806 19:54:12.972020512 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. 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loss=0.26641542 grad_norm=1.464799 alpha=0.000000 seconds=33.767 +step=91 loss=0.11470888 grad_norm=1.230817 alpha=0.000000 seconds=33.635 +step=92 loss=0.07105367 grad_norm=1.617311 alpha=0.000000 seconds=33.811 +step=93 loss=0.07540740 grad_norm=0.679684 alpha=0.000000 seconds=33.786 +step=94 loss=0.40294635 grad_norm=1.232529 alpha=0.000000 seconds=33.660 +step=95 loss=0.05332119 grad_norm=1.191226 alpha=0.000000 seconds=33.807 +step=96 loss=0.44524965 grad_norm=1.164661 alpha=0.000000 seconds=33.669 +step=97 loss=0.36762464 grad_norm=0.794524 alpha=0.000000 seconds=33.794 +step=98 loss=0.16921875 grad_norm=1.883905 alpha=0.000000 seconds=33.637 +step=99 loss=0.10734279 grad_norm=1.729467 alpha=0.000000 seconds=33.747 +step=100 loss=0.15980434 grad_norm=1.121718 alpha=0.000000 seconds=33.776 +validation step=100 loss=0.14690994 alpha=0.000000 samples=32 seconds=23.254 +Start gathering distributed model states... +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states.../home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( + +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt sha256=9c73b32512466e1761498cc9b47616c7ad7e4ceb6a8fbf930bb9dffc4e51c348 +step=101 loss=0.19841097 grad_norm=1.574268 alpha=0.000000 seconds=33.143 +step=102 loss=0.11785068 grad_norm=0.726850 alpha=0.000000 seconds=33.770 +step=103 loss=0.10634899 grad_norm=0.662060 alpha=0.000000 seconds=33.655 +step=104 loss=0.40984410 grad_norm=1.235051 alpha=0.000000 seconds=33.775 +step=105 loss=0.05807800 grad_norm=0.702543 alpha=0.000000 seconds=33.629 +step=106 loss=0.06164713 grad_norm=1.868279 alpha=0.000000 seconds=33.795 +step=107 loss=0.08294948 grad_norm=0.856796 alpha=0.000000 seconds=33.808 +step=108 loss=0.18574186 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a/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl b/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4779230f7da943d820f4941a307ebd76e98a9f5f --- /dev/null +++ b/outputs/temporal_nope/a4_tdrope_hard_lr2e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "validation_loss": 0.2635482151526958, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 22.61892604827881, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 100, "validation_loss": 0.14690994436386973, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 23.253740072250366, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 200, "validation_loss": 0.1128241450060159, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 23.328860998153687, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e9995828f8d05493b41e78deb183ddda0b657a31 --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "type": "immutable_base_checkpoint_reference", "path": "/data/fengjiaqi/causal_forcing/checkpoints/framewise/causal_cd.pt", "checkpoint_key": "generator_ema", "sha256": "c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22", "optimizer_state": "reset"} +{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt", "sha256": "0f0001d419f5e22e14017e98b581e1e54d7fc6f1327d4745106dde9fa4444880", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt", "sha256": "1e85b4ece877629d20ada99adcf0974700a1449f0af76c311b08d74260471d51", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/resolved_config.yaml b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e05008745ffeadada2f87898d647159d0a958a12 --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/resolved_config.yaml @@ -0,0 +1,123 @@ +experiment: + id: a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: Annealed Temporal DroPE +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 0.0 + temporal_rope_schedule: cosine + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 40 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 + target_visible_lengths: + - 21 + - 42 + - 84 + train_length: 21 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 1.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/train.log b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/train.log new file mode 100644 index 0000000000000000000000000000000000000000..105afb45193dda502b52a4c0f69e3717c9628191 --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/train.log @@ -0,0 +1,56 @@ +W0806 17:35:02.258000 2931479 site-packages/torch/distributed/run.py:793] +W0806 17:35:02.258000 2931479 site-packages/torch/distributed/run.py:793] ***************************************** +W0806 17:35:02.258000 2931479 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0806 17:35:02.258000 2931479 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank4]:[W806 17:35:11.398747864 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W806 17:35:12.973127437 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank6]:[W806 17:35:12.076794181 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank1]:[W806 17:35:12.397289901 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank2]:[W806 17:35:12.422225633 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank5]:[W806 17:35:12.423958046 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank7]:[W806 17:35:12.427401743 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank0]:[W806 17:35:13.673997724 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +DATASET TRAIN 6249 VALIDATION 256 SPLIT /home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json +validation step=0 loss=0.06264185 alpha=1.000000 samples=32 seconds=23.283 +step=1 loss=0.16898617 grad_norm=0.284414 alpha=1.000000 seconds=34.007 +step=2 loss=0.08545000 grad_norm=0.263569 alpha=0.998459 seconds=34.050 +W0806 17:36:50.927000 2931479 site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers +W0806 17:36:50.929000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931561 closing signal SIGTERM +W0806 17:36:50.930000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931562 closing signal SIGTERM +W0806 17:36:50.932000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931563 closing signal SIGTERM +W0806 17:36:50.933000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931564 closing signal SIGTERM +W0806 17:36:50.933000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931565 closing signal SIGTERM +W0806 17:36:50.933000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931566 closing signal SIGTERM +W0806 17:36:50.934000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931567 closing signal SIGTERM +W0806 17:36:50.934000 2931479 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2931568 closing signal SIGTERM +Traceback (most recent call last): + File "/home/jiaqi/miniconda3/envs/causal_forcing/bin/torchrun", line 6, in + sys.exit(main()) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper + return f(*args, **kwargs) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main + run(args) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run + elastic_launch( + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__ + return launch_agent(self._config, self._entrypoint, list(args)) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent + result = agent.run() + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper + result = f(*args, **kwargs) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run + result = self._invoke_run(role) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run + time.sleep(monitor_interval) + File "/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler + raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval) +torch.distributed.elastic.multiprocessing.api.SignalException: Process 2931479 got signal: 15 diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/training_metrics.jsonl b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/training_metrics.jsonl new file mode 100644 index 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0000000000000000000000000000000000000000..117808d827ac16267d162a677e333cb4628787e2 --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr1e7_probe200_seed20260805_kerrigan/validation_metrics.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "validation_loss": 0.06264185276813805, "temporal_rope_alpha": 1.0, "validation_samples": 32, "validation_seconds": 22.847965478897095, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 100, "validation_loss": 0.18985189858358353, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 23.650352478027344, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} +{"step": 200, "validation_loss": 0.14413261564914137, "temporal_rope_alpha": 0.0, "validation_samples": 32, "validation_seconds": 23.630066871643066, "validation_seed": 20260805, "split_manifest": "/home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json"} diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ca2d9acbf1cb092ce09aefceb1f23b449da2d8d2 --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_manifest.jsonl @@ -0,0 +1,3 @@ +{"step": 0, "type": "immutable_base_checkpoint_reference", "path": "/data/fengjiaqi/causal_forcing/checkpoints/framewise/causal_cd.pt", "checkpoint_key": "generator_ema", "sha256": "c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22", "optimizer_state": "reset"} +{"step": 100, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt", "sha256": "d619dfb424d6e5b0963ed4439660118a260e351ec5e850a266c0a6626f2172e4", "size_bytes": 5676282858, "contains": ["generator"]} +{"step": 200, "path": "/home/jiaqi/NoPE/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt", "sha256": "6b535fdcb9c6c38272270665b97255dcad781aa4a3694f1c7dcb244745afc8bc", "size_bytes": 5676282858, "contains": ["generator"]} diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..da4db1ae871233c58d10c215dc49b93a082612e9 --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/resolved_config.yaml @@ -0,0 +1,123 @@ +experiment: + id: a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan + seed: 20260805 + source_revision: bb190459d99b074b5803ed6ba0b5091b16d5585d + output_root: outputs/temporal_nope + report_root: reports/temporal_nope + tier: A + method: Annealed Temporal DroPE +generator_ckpt: checkpoints/framewise/causal_cd.pt +generator_ckpt_sha256: c951a6b4804cd637fecfc857e9a59d54b6e4cd7846c38360baa3cf3b525f0d22 +checkpoint_key: generator_ema +strict_checkpoint_load: true +model_name: Wan2.1-T2V-1.3B +generator_task: causal_video +causal: true +mixed_precision: true +gradient_checkpointing: true +num_frame_per_block: 1 +independent_first_frame: false +num_training_frames: 21 +image_or_video_shape: +- 1 +- 21 +- 16 +- 60 +- 104 +height: 480 +width: 832 +num_frames: 81 +fps: 16 +denoising_step_list: +- 1000 +- 750 +- 500 +- 250 +warp_denoising_step: true +num_train_timestep: 1000 +timestep_shift: 5.0 +guidance_scale: 3.0 +negative_prompt: 色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走 +prompt_embedding_cache_path: /data/fengjiaqi/Causal_forcing/prompt_cache/chunkwise_umt5_bf16_lmdb +rank0_preload_generator_ckpt: true +model_kwargs: + timestep_shift: 5.0 +position_encoding: + spatial_mode: rope + temporal_mode: rope + temporal_rope_alpha: 0.0 + temporal_rope_schedule: cosine + temporal_rope_anneal_start: 0 + temporal_rope_anneal_end: 40 + temporal_layer_pattern: all + temporal_position_scale: 1.0 + temporal_rope_theta: 10000.0 + riflex_k: null + riflex_target_length: null + riflex_observed_repetition_length: null +attention_scaling: + enabled: false + mode: none + coefficient: 0.0 + train_length: 21 + length_ratio: null + per_head_scales: null +analysis: + record_attention_stats: false + sampled_layers: + - 0 + - 0.5 + - -1 + sampled_spatial_queries: 64 + target_visible_lengths: + - 21 + - 42 + - 84 + train_length: 21 +training: + enabled: true + objective: teacher_forced_flow_matching + data_path: dataset/clean_data + split_manifest: artifacts/data_splits/cpt_train_val_seed20260805.json + fixed_latent_length: 21 + batch_size_per_gpu: 1 + total_batch_size: 8 + max_steps: 200 + checkpoint_steps: + - 0 + - 100 + - 200 + optimizer: adamw + optimizer_reset: true + lr: 2.0e-07 + original_pretrain_peak_lr: 2.0e-06 + betas: + - 0.0 + - 0.999 + weight_decay: 0.01 + max_grad_norm: 1.0 + bf16: true + ema_enabled: false + num_workers: 8 + log_every: 1 + validation_every: 100 + validation_batches_per_rank: 4 + validation_seed: 20260805 +evaluation: + length_ratios: + - 1.0 + - 1.5 + - 2.0 + - 3.0 + - 4.0 + validation_prompt_file: eval/prompts_temporal_nope_val.json + test_prompt_file: eval/prompts_temporal_nope_test.json + validation_seeds: + - 0 + - 1 + test_seeds: + - 0 + - 1 + - 2 + - 3 + paired_longest_rollout: true diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/train.log b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/train.log new file mode 100644 index 0000000000000000000000000000000000000000..232d7e37c6053f3ac770d391e679ac55b495df0b --- /dev/null +++ b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/train.log @@ -0,0 +1,259 @@ +W0806 22:03:45.359000 3096052 site-packages/torch/distributed/run.py:793] +W0806 22:03:45.359000 3096052 site-packages/torch/distributed/run.py:793] ***************************************** +W0806 22:03:45.359000 3096052 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. +W0806 22:03:45.359000 3096052 site-packages/torch/distributed/run.py:793] ***************************************** +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallbackCAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback + +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +CAUSAL_DISABLE_FLEX_ATTENTION=1 -> using segmented FlashAttention fallback +[rank5]:[W806 22:03:55.733462620 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +Rank 0 preloading generator from checkpoints/framewise/causal_cd.pt +[rank0]:[W806 22:03:55.051553803 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank7]:[W806 22:03:55.481668409 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank6]:[W806 22:03:55.519711694 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank3]:[W806 22:03:55.571008943 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank4]:[W806 22:03:55.616497111 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank1]:[W806 22:03:55.641780623 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +[rank2]:[W806 22:03:56.679116840 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id. +DATASET TRAIN 6249 VALIDATION 256 SPLIT /home/jiaqi/NoPE/artifacts/data_splits/cpt_train_val_seed20260805.json +validation step=0 loss=0.06264185 alpha=1.000000 samples=32 seconds=23.004 +step=1 loss=0.16898617 grad_norm=0.284402 alpha=1.000000 seconds=54.535 +step=2 loss=0.08512081 grad_norm=0.262459 alpha=0.998459 seconds=33.129 +step=3 loss=0.07950794 grad_norm=0.304532 alpha=0.993844 seconds=33.860 +step=4 loss=0.11425614 grad_norm=0.284928 alpha=0.986185 seconds=33.799 +step=5 loss=0.04064452 grad_norm=0.423016 alpha=0.975528 seconds=33.984 +step=6 loss=0.04959621 grad_norm=0.237331 alpha=0.961940 seconds=33.825 +step=7 loss=0.12052579 grad_norm=0.287661 alpha=0.945503 seconds=33.936 +step=8 loss=0.04146440 grad_norm=0.268602 alpha=0.926320 seconds=33.940 +step=9 loss=0.03983995 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loss=0.26358503 grad_norm=1.436848 alpha=0.000000 seconds=33.930 +step=91 loss=0.11174587 grad_norm=1.236239 alpha=0.000000 seconds=33.751 +step=92 loss=0.07043193 grad_norm=1.628726 alpha=0.000000 seconds=33.886 +step=93 loss=0.07400727 grad_norm=0.672597 alpha=0.000000 seconds=33.873 +step=94 loss=0.39645430 grad_norm=1.208352 alpha=0.000000 seconds=33.697 +step=95 loss=0.05317626 grad_norm=1.186703 alpha=0.000000 seconds=33.894 +step=96 loss=0.43959400 grad_norm=1.151026 alpha=0.000000 seconds=33.788 +step=97 loss=0.36323822 grad_norm=0.766542 alpha=0.000000 seconds=33.858 +step=98 loss=0.16555864 grad_norm=1.975898 alpha=0.000000 seconds=33.719 +step=99 loss=0.10698085 grad_norm=1.742802 alpha=0.000000 seconds=33.847 +step=100 loss=0.15891327 grad_norm=1.198262 alpha=0.000000 seconds=33.847 +validation step=100 loss=0.14521493 alpha=0.000000 samples=32 seconds=23.442 +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states...Start gathering distributed model states... + +Start gathering distributed model states... +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Start gathering distributed model states... +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/home/jiaqi/miniconda3/envs/causal_forcing/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:690: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000100/model.pt sha256=d619dfb424d6e5b0963ed4439660118a260e351ec5e850a266c0a6626f2172e4 +step=101 loss=0.19569166 grad_norm=1.694456 alpha=0.000000 seconds=33.194 +step=102 loss=0.11495597 grad_norm=0.728711 alpha=0.000000 seconds=33.859 +step=103 loss=0.10462007 grad_norm=0.661913 alpha=0.000000 seconds=33.722 +step=104 loss=0.40339103 grad_norm=1.274916 alpha=0.000000 seconds=33.812 +step=105 loss=0.05686240 grad_norm=0.680913 alpha=0.000000 seconds=33.711 +step=106 loss=0.05958192 grad_norm=1.929931 alpha=0.000000 seconds=33.835 +step=107 loss=0.08186150 grad_norm=0.872618 alpha=0.000000 seconds=33.815 +step=108 loss=0.18128195 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+validation step=200 loss=0.10852250 alpha=0.000000 samples=32 seconds=23.362 +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states...Start gathering distributed model states... +Start gathering distributed model states... +Start gathering distributed model states... + +Start gathering distributed model states... +Model saved to /home/jiaqi/NoPE/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/checkpoint_model_000200/model.pt sha256=6b535fdcb9c6c38272270665b97255dcad781aa4a3694f1c7dcb244745afc8bc diff --git a/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/training_metrics.jsonl b/outputs/temporal_nope/a5_tdrope_anneal_lr2e7_probe200_seed20260805_kerrigan/training_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3bf65e82c7131f7220e39a9e06b29e9f8cbc9c73 --- /dev/null +++ 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