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=== TRAIN WRAPPER START ===
RUN_ID=87493717
RUN_DIR=/opt/train-runs/87493717
FAST_ROOT=/mnt/localssd/train-runs
FAST_RUN_DIR=/mnt/localssd/train-runs/87493717
DATASET_DIR=/mnt/localssd/train-runs/87493717/dataset
OUTPUT_DIR=/mnt/localssd/train-runs/87493717/outputs
TRAIN_LOG=/opt/train-runs/87493717/train.log
PROGRESS_JSON=/opt/train-runs/87493717/progress.json
RESULT_JSON=/opt/train-runs/87493717/result.json
CONFIG_PATH=/opt/train-runs/87493717/train_xvla.yaml
DATASET_REPO=carrot-fever/tl_ts_prompted_merged_image_v3_smoke_ep0
DATASET_SUBDIR=
MODEL_REPO=carrot-fever/smoke-test-diff
JOB_NAME=96a5bba7-faf3c438-2a9b411f-87493717
STEPS=20
BATCH_SIZE=4
SAVE_FREQ=10
NUM_WORKERS=12
DATALOADER_PREFETCH_FACTOR=2
LOG_FREQ=1000
LEROBOT_ROOT=/opt/lerobot_v2
PYTHON=/opt/lerobot_v2/.venv/bin/python
HF_HOME=/mnt/localssd/hf
HF_LEROBOT_HOME=/mnt/localssd/hf
HUGGINGFACE_HUB_CACHE=/mnt/localssd/hf/hub
HF_DATASETS_CACHE=/mnt/localssd/hf/datasets
TMPDIR=/mnt/localssd/tmp
WANDB_DIR=/mnt/localssd/wandb
===========================
 Fetching 7 files: 0%| | 0/7 [00:00<?, ?it/s] Fetching 7 files: 14%|█▍ | 1/7 [00:00<00:01, 5.16it/s] Fetching 7 files: 43%|████▎ | 3/7 [00:01<00:02, 1.45it/s] Fetching 7 files: 100%|██████████| 7/7 [00:01<00:00, 3.65it/s]
Downloaded dataset repo carrot-fever/tl_ts_prompted_merged_image_v3_smoke_ep0 to /mnt/localssd/train-runs/87493717/dataset
Wrote config to /opt/train-runs/87493717/train_xvla.yaml
policy model path is local; skipping download: /opt/lerobot_v2/policy_seeds/diffusion_3cam12d
No tokenizer_name found in policy or preprocessor; skipping tokenizer pre-download
/opt/lerobot_v2/src/lerobot/policies/vqbet/vqbet_utils.py:1373: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
 @autocast(enabled=False)
INFO 2026-04-20 20:08:43 bot_train.py:75 Using explicit dataset root: /mnt/localssd/train-runs/87493717/dataset
INFO 2026-04-20 20:08:43 ot_train.py:267 {'batch_size': 4,
 'checkpoint_path': None,
 'cudnn_deterministic': False,
 'dataloader_persistent_workers': True,
 'dataloader_prefetch_factor': 2,
 'dataset': {'episodes': None,
 'image_transforms': {'enable': False,
 'max_num_transforms': 3,
 'random_order': False,
 'tfs': {'affine': {'kwargs': {'degrees': [-5.0,
 5.0],
 'translate': [0.05,
 0.05]},
 'type': 'RandomAffine',
 'weight': 1.0},
 'brightness': {'kwargs': {'brightness': [0.8,
 1.2]},
 'type': 'ColorJitter',
 'weight': 1.0},
 'contrast': {'kwargs': {'contrast': [0.8,
 1.2]},
 'type': 'ColorJitter',
 'weight': 1.0},
 'hue': {'kwargs': {'hue': [-0.05,
 0.05]},
 'type': 'ColorJitter',
 'weight': 1.0},
 'saturation': {'kwargs': {'saturation': [0.5,
 1.5]},
 'type': 'ColorJitter',
 'weight': 1.0},
 'sharpness': {'kwargs': {'sharpness': [0.5,
 1.5]},
 'type': 'SharpnessJitter',
 'weight': 1.0}}},
 'repo_id': 'carrot-fever/tl_ts_prompted_merged_image_v3_smoke_ep0',
 'revision': 'main',
 'root': '/mnt/localssd/train-runs/87493717/dataset',
 'streaming': False,
 'use_imagenet_stats': True,
 'video_backend': 'torchcodec'},
 'env': None,
 'eval': {'batch_size': 8, 'n_episodes': 50, 'use_async_envs': True},
 'eval_freq': 20000,
 'job_name': '96a5bba7-faf3c438-2a9b411f-87493717',
 'log_freq': 1000,
 'num_workers': 12,
 'optimizer': {'betas': [0.95, 0.999],
 'eps': 1e-08,
 'grad_clip_norm': 10.0,
 'lr': 0.0001,
 'type': 'adam',
 'weight_decay': 1e-06},
 'output_dir': '/mnt/localssd/train-runs/87493717/outputs',
 'peft': None,
 'policy': {'beta_end': 0.02,
 'beta_schedule': 'squaredcos_cap_v2',
 'beta_start': 0.0001,
 'clip_sample': True,
 'clip_sample_range': 1.0,
 'compile_mode': 'reduce-overhead',
 'compile_model': False,
 'crop_is_random': True,
 'crop_ratio': 1.0,
 'crop_shape': None,
 'device': 'cuda',
 'diffusion_step_embed_dim': 128,
 'do_mask_loss_for_padding': False,
 'down_dims': [512, 1024, 2048],
 'drop_n_last_frames': 7,
 'horizon': 16,
 'input_features': {'observation.images.image': {'shape': [3,
 480,
 640],
 'type': <FeatureType.VISUAL: 'VISUAL'>},
 'observation.images.image2': {'shape': [3,
 480,
 640],
 'type': <FeatureType.VISUAL: 'VISUAL'>},
 'observation.images.image3': {'shape': [3,
 480,
 640],
 'type': <FeatureType.VISUAL: 'VISUAL'>},
 'observation.state': {'shape': [12],
 'type': <FeatureType.STATE: 'STATE'>}},
 'kernel_size': 5,
 'license': None,
 'n_action_steps': 8,
 'n_groups': 8,
 'n_obs_steps': 2,
 'noise_scheduler_type': 'DDPM',
 'normalization_mapping': {'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>,
 'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>,
 'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>},
 'num_inference_steps': None,
 'num_train_timesteps': 100,
 'optimizer_betas': [0.95, 0.999],
 'optimizer_eps': 1e-08,
 'optimizer_lr': 0.0001,
 'optimizer_weight_decay': 1e-06,
 'output_features': {'action': {'shape': [12],
 'type': <FeatureType.ACTION: 'ACTION'>}},
 'prediction_type': 'epsilon',
 'pretrained_backbone_weights': None,
 'pretrained_path': '/opt/lerobot_v2/policy_seeds/diffusion_3cam12d',
 'private': None,
 'push_to_hub': False,
 'repo_id': 'carrot-fever/smoke-test-diff',
 'resize_shape': [224, 224],
 'scheduler_name': 'cosine',
 'scheduler_warmup_steps': 500,
 'spatial_softmax_num_keypoints': 32,
 'tags': None,
 'type': 'diffusion',
 'use_amp': True,
 'use_film_scale_modulation': True,
 'use_group_norm': True,
 'use_peft': False,
 'use_separate_rgb_encoder_per_camera': False,
 'vision_backbone': 'resnet18'},
 'rabc_epsilon': 1e-06,
 'rabc_head_mode': 'sparse',
 'rabc_kappa': 0.01,
 'rabc_progress_path': None,
 'rename_map': {'observation.images.left_rgb': 'observation.images.image2',
 'observation.images.right_rgb': 'observation.images.image3',
 'observation.images.top_rgb': 'observation.images.image'},
 'require_localssd': False,
 'resume': False,
 'save_checkpoint': True,
 'save_freq': 10,
 'scheduler': {'name': 'cosine', 'num_warmup_steps': 500, 'type': 'diffuser'},
 'seed': 1000,
 'steps': 20,
 'tolerance_s': 0.0001,
 'use_policy_training_preset': True,
 'use_rabc': False,
 'wandb': {'add_tags': True,
 'disable_artifact': False,
 'enable': False,
 'entity': None,
 'mode': None,
 'notes': None,
 'project': 'lerobot',
 'run_id': None}}
INFO 2026-04-20 20:08:43 ot_train.py:275 Logs will be saved locally.
INFO 2026-04-20 20:08:43 ot_train.py:291 Creating dataset
INFO 2026-04-20 20:08:44 eo_utils.py:111 Using video codec: libsvtav1
INFO 2026-04-20 20:08:44 ot_train.py:309 Creating policy
INFO 2026-04-20 20:08:49 ot_train.py:376 Creating optimizer and scheduler
INFO 2026-04-20 20:08:49 ot_train.py:411 Output dir: /mnt/localssd/train-runs/87493717/outputs
INFO 2026-04-20 20:08:49 ot_train.py:418 cfg.steps=20 (20)
INFO 2026-04-20 20:08:49 ot_train.py:419 dataset.num_frames=315 (315)
INFO 2026-04-20 20:08:49 ot_train.py:420 dataset.num_episodes=1
INFO 2026-04-20 20:08:49 ot_train.py:423 Effective batch size: 4 x 1 = 4
INFO 2026-04-20 20:08:49 ot_train.py:424 num_learnable_params=270658348 (271M)
INFO 2026-04-20 20:08:49 ot_train.py:425 num_total_params=270658348 (271M)
Loading weights from local directory
 Training: 0%| | 0/20 [00:00<?, ?step/s]INFO 2026-04-20 20:08:49 ot_train.py:493 Start offline training on a fixed dataset, with effective batch size: 4
 Training: 5%|▌ | 1/20 [00:11<03:46, 11.93s/step] Training: 10%|█ | 2/20 [00:12<01:29, 4.99s/step] Training: 15%|█▌ | 3/20 [00:12<00:47, 2.79s/step] Training: 20%|██ | 4/20 [00:12<00:28, 1.76s/step] Training: 30%|███ | 6/20 [00:12<00:12, 1.15step/s] Training: 40%|████ | 8/20 [00:12<00:06, 1.87step/s] Training: 50%|█████ | 10/20 [00:12<00:03, 2.73step/s]INFO 2026-04-20 20:09:02 ot_train.py:559 Checkpoint policy after step 10
 Training: 55%|█████▌ | 11/20 [00:20<00:17, 1.96s/step] Training: 65%|██████▌ | 13/20 [00:20<00:08, 1.24s/step] Training: 75%|███████▌ | 15/20 [00:21<00:04, 1.21step/s] Training: 85%|████████▌ | 17/20 [00:21<00:01, 1.72step/s] Training: 95%|█████████▌| 19/20 [00:21<00:00, 2.39step/s]INFO 2026-04-20 20:09:11 ot_train.py:559 Checkpoint policy after step 20
 Training: 100%|██████████| 20/20 [00:28<00:00, 1.44s/step]
INFO 2026-04-20 20:09:18 ot_train.py:633 End of training
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New Data Upload : 18%|█▊ | 84.3MB / 469MB, 21.1MB/s 
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New Data Upload : 25%|██▍ | 150MB / 603MB, 31.3MB/s 
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New Data Upload : 34%|███▍ | 227MB / 671MB, 42.1MB/s 
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New Data Upload : 45%|████▍ | 482MB / 1.07GB, 67.0MB/s 
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New Data Upload : 46%|████▋ | 528MB / 1.14GB, 71.3MB/s 
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New Data Upload : 51%|█████ | 580MB / 1.14GB, 76.3MB/s 
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New Data Upload : 87%|████████▋ | 4.27GB / 4.90GB, 381MB/s 
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New Data Upload : 88%|████████▊ | 4.38GB / 4.96GB, 388MB/s 
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New Data Upload : 88%|████████▊ | 4.49GB / 5.10GB, 396MB/s 
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New Data Upload : 89%|████████▉ | 4.60GB / 5.16GB, 404MB/s 
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New Data Upload : 90%|████████▉ | 4.70GB / 5.23GB, 409MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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 ...d_model/model.safetensors: 98%|█████████▊| 1.06GB / 1.08GB 
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New Data Upload : 89%|████████▉ | 4.79GB / 5.36GB, 413MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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New Data Upload : 91%|█████████ | 4.89GB / 5.36GB, 416MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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New Data Upload : 92%|█████████▏| 4.99GB / 5.43GB, 419MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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New Data Upload : 91%|█████████ | 5.07GB / 5.57GB, 421MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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New Data Upload : 91%|█████████▏| 5.15GB / 5.63GB, 424MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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New Data Upload : 92%|█████████▏| 5.23GB / 5.70GB, 427MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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 ...timizer_state.safetensors: 77%|███████▋ | 1.67GB / 2.17GB 
 ...d_model/model.safetensors: 99%|█████████▉| 1.07GB / 1.08GB 
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New Data Upload : 91%|█████████▏| 5.32GB / 5.83GB, 432MB/s 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
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New Data Upload : 92%|█████████▏| 5.41GB / 5.90GB, 436MB/s 
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New Data Upload : 92%|█████████▏| 5.49GB / 5.97GB, 440MB/s 
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New Data Upload : 91%|█████████▏| 5.58GB / 6.10GB, 446MB/s 
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New Data Upload : 92%|█████████▏| 5.67GB / 6.17GB, 449MB/s 
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New Data Upload : 94%|█████████▍| 5.91GB / 6.30GB, 450MB/s 
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New Data Upload : 100%|██████████| 6.50GB / 6.50GB, 309MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB
...ate/rng_state.safetensors: 100%|██████████| 15.7kB / 15.7kB
...ate/rng_state.safetensors: 100%|██████████| 15.7kB / 15.7kB
...timizer_state.safetensors: 100%|██████████| 2.17GB / 2.17GB
...timizer_state.safetensors: 100%|██████████| 2.17GB / 2.17GB
...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB
...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB
Processing Files (0 / 0) : | | 0.00B / 0.00B
New Data Upload : | | 0.00B / 0.00B 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 14%|█▍ | 152MB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 14%|█▍ | 152MB / 1.08GB  Processing Files (2 / 3) : 14%|█▍ | 152MB / 1.08GB, ???B/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 30%|██▉ | 320MB / 1.08GB  Processing Files (2 / 3) : 30%|██▉ | 320MB / 1.08GB, 839MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 45%|████▌ | 488MB / 1.08GB  Processing Files (2 / 3) : 45%|████▌ | 488MB / 1.08GB, 839MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 61%|██████ | 656MB / 1.08GB  Processing Files (2 / 3) : 61%|██████ | 656MB / 1.08GB, 840MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 75%|███████▌ | 816MB / 1.08GB  Processing Files (2 / 3) : 75%|███████▌ | 816MB / 1.08GB, 830MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 91%|█████████ | 984MB / 1.08GB  Processing Files (2 / 3) : 91%|█████████ | 984MB / 1.08GB, 832MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB  Processing Files (3 / 3) : 100%|██████████| 1.08GB / 1.08GB, 776MB/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB 
 ...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB  Processing Files (3 / 3) : 100%|██████████| 1.08GB / 1.08GB, 332MB/s
New Data Upload : | | 0.00B / 0.00B, 0.00B/s
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB
...zer_processor.safetensors: 100%|██████████| 9.14kB / 9.14kB
...d_model/model.safetensors: 100%|██████████| 1.08GB / 1.08GB