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.gitattributes +5 -0
checkpoints/steps_4000_pytorch_model.pt +3 -0
checkpoints/steps_8000_pytorch_model.pt +3 -0
config.yaml +69 -0
dataset_statistics.json +133 -0
run_libero_train.sh +76 -0
summary.jsonl +2 -0
wandb/wandb/debug-internal.log +0 -0
wandb/wandb/debug.log +0 -0
wandb/wandb/run-20260323_072914-53rxxhtp/files/config.yaml +96 -0
wandb/wandb/run-20260323_072914-53rxxhtp/files/output.log +71 -0
wandb/wandb/run-20260323_072914-53rxxhtp/files/requirements.txt +157 -0
wandb/wandb/run-20260323_072914-53rxxhtp/files/wandb-metadata.json +73 -0
wandb/wandb/run-20260323_072914-53rxxhtp/files/wandb-summary.json +1 -0
wandb/wandb/run-20260323_072914-53rxxhtp/logs/debug-core.log +15 -0
wandb/wandb/run-20260323_072914-53rxxhtp/logs/debug-internal.log +26 -0
wandb/wandb/run-20260323_072914-53rxxhtp/logs/debug.log +0 -0
wandb/wandb/run-20260323_072914-53rxxhtp/run-53rxxhtp.wandb +0 -0
wandb/wandb/run-20260323_073231-ih9hd073/files/config.yaml +97 -0
wandb/wandb/run-20260323_073231-ih9hd073/files/output.log +230 -0
wandb/wandb/run-20260323_073231-ih9hd073/files/requirements.txt +157 -0
wandb/wandb/run-20260323_073231-ih9hd073/files/wandb-metadata.json +73 -0
wandb/wandb/run-20260323_073231-ih9hd073/files/wandb-summary.json +1 -0
wandb/wandb/run-20260323_073231-ih9hd073/logs/debug-core.log +16 -0
wandb/wandb/run-20260323_073231-ih9hd073/logs/debug-internal.log +402 -0
wandb/wandb/run-20260323_073231-ih9hd073/logs/debug.log +0 -0
wandb/wandb/run-20260323_073231-ih9hd073/run-ih9hd073.wandb +3 -0
wandb/wandb/run-20260323_082640-ln36rrqb/files/config.yaml +97 -0
wandb/wandb/run-20260323_082640-ln36rrqb/files/output.log +95 -0
wandb/wandb/run-20260323_082640-ln36rrqb/files/requirements.txt +141 -0
wandb/wandb/run-20260323_082640-ln36rrqb/files/wandb-metadata.json +73 -0
wandb/wandb/run-20260323_082640-ln36rrqb/files/wandb-summary.json +1 -0
wandb/wandb/run-20260323_082640-ln36rrqb/logs/debug-core.log +15 -0
wandb/wandb/run-20260323_082640-ln36rrqb/logs/debug-internal.log +82 -0
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wandb/wandb/run-20260323_082640-ln36rrqb/run-ln36rrqb.wandb +3 -0
wandb/wandb/run-20260323_083619-tjnthejr/files/config.yaml +99 -0
wandb/wandb/run-20260323_083619-tjnthejr/files/output.log +120 -0
wandb/wandb/run-20260323_083619-tjnthejr/files/requirements.txt +141 -0
wandb/wandb/run-20260323_083619-tjnthejr/files/wandb-metadata.json +75 -0
wandb/wandb/run-20260323_083619-tjnthejr/files/wandb-summary.json +1 -0
wandb/wandb/run-20260323_083619-tjnthejr/logs/debug-core.log +15 -0
wandb/wandb/run-20260323_083619-tjnthejr/logs/debug-internal.log +510 -0
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wandb/wandb/run-20260323_083619-tjnthejr/run-tjnthejr.wandb +3 -0
wandb/wandb/run-20260323_094014-p8q7c8fg/files/config.yaml +98 -0
wandb/wandb/run-20260323_094014-p8q7c8fg/files/output.log +53 -0
wandb/wandb/run-20260323_094014-p8q7c8fg/files/requirements.txt +141 -0
wandb/wandb/run-20260323_094014-p8q7c8fg/files/wandb-metadata.json +75 -0
wandb/wandb/run-20260323_094014-p8q7c8fg/files/wandb-summary.json +1 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+wandb/wandb/run-20260323_083619-tjnthejr/run-tjnthejr.wandb filter=lfs diff=lfs merge=lfs -text
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+wandb/wandb/run-20260323_095721-0ftwgd79/run-0ftwgd79.wandb filter=lfs diff=lfs merge=lfs -text

checkpoints/steps_4000_pytorch_model.pt ADDED Viewed

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config.yaml ADDED Viewed

	@@ -0,0 +1,69 @@

+datasets:
+  vla_data:
+    CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
+      Locate their bounding boxes in [x1,y1,x2,y2] format.
+    data_mix: libero_all
+    data_root_dir: playground/Datasets/LEROBOT_LIBERO_DATA
+    dataset_py: lerobot_datasets
+    num_workers: 4
+    per_device_batch_size: 16
+    sequential_step_sampling: false
+    video_backend: torchvision_av
+framework:
+  action_model:
+    action_dim: 7
+    action_horizon: 8
+    action_model_type: DiT-B
+    add_pos_embed: true
+    diffusion_model_cfg:
+      cross_attention_dim: 2048
+      dropout: 0.2
+      final_dropout: true
+      interleave_self_attention: true
+      norm_type: ada_norm
+      num_layers: 16
+      output_dim: 1024
+      positional_embeddings: null
+    future_action_window_size: 7
+    hidden_size: 1024
+    max_seq_len: 1024
+    noise_beta_alpha: 1.5
+    noise_beta_beta: 1.0
+    noise_s: 0.999
+    num_inference_timesteps: 4
+    num_target_vision_tokens: 32
+    num_timestep_buckets: 1000
+    past_action_window_size: 0
+    state_dim: 7
+  name: QwenGR00T
+  qwenvl:
+    base_vlm: playground/Pretrained_models/Qwen3-VL-2B-Instruct
+output_dir: ./results/ckpt/0323_libero_all_qwengr00t
+run_id: 0323_libero_all_qwengr00t
+run_root_dir: ./results/ckpt
+seed: 42
+trainer:
+  eval_interval: 100
+  freeze_modules: true
+  gradient_accumulation_steps: 1
+  gradient_clipping: 1.0
+  is_resume: false
+  learning_rate:
+    action_model: 0.0001
+    base: 2.5e-05
+    qwen_vl_interface: 1.0e-05
+  logging_frequency: 100
+  lr_scheduler_type: cosine_with_min_lr
+  max_train_steps: 40000
+  num_warmup_steps: 5000
+  optimizer:
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+  save_interval: 4000
+  scheduler_specific_kwargs:
+    min_lr: 1.0e-06
+wandb_entity: junha-lee
+wandb_project: starvla

dataset_statistics.json ADDED Viewed

	@@ -0,0 +1,133 @@

+{
+  "franka": {
+    "action": {
+      "mean": [
+        0.07237596483901143,
+        0.08987006871029735,
+        -0.10144743137061596,
+        -0.00045383188989944756,
+        0.006273590726777911,
+        -0.003878799732774496,
+        0.524486355483532
+      ],
+      "std": [
+        0.3498823308902479,
+        0.37794140366375184,
+        0.460084266976933,
+        0.0403885784928603,
+        0.06616144248501059,
+        0.07763074391911857,
+        0.4994683356809767
+      ],
+      "max": [
+        0.9375,
+        0.9375,
+        0.9375,
+        0.3557142913341522,
+        0.375,
+        0.375,
+        1.0
+      ],
+      "min": [
+        -0.9375,
+        -0.9375,
+        -0.9375,
+        -0.2582142949104309,
+        -0.375,
+        -0.3675000071525574,
+        0.0
+      ],
+      "q01": [
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+        -0.8758928775787354,
+        -0.9375,
+        -0.1510714292526245,
+        -0.20678570866584778,
+        -0.2742857038974762,
+        0.0
+      ],
+      "q99": [
+        0.9375,
+        0.9107142686843872,
+        0.9375,
+        0.20357142388820648,
+        0.26357144117355347,
+        0.375,
+        1.0
+      ],
+      "mask": [
+        true,
+        true,
+        true,
+        true,
+        true,
+        true,
+        false
+      ]
+    },
+    "state": {
+      "mean": [
+        -0.04889854742214084,
+        0.03689368185587227,
+        0.7890402488410473,
+        2.9771945476531982,
+        -0.1417286954820156,
+        -0.11769362539052963,
+        0.026436020154505968,
+        -0.02665513101965189
+      ],
+      "std": [
+        0.10639013941746686,
+        0.15115733130675715,
+        0.38406895599530033,
+        0.3530238395244304,
+        0.8227341427331599,
+        0.32357567121520087,
+        0.014583991652936385,
+        0.014467005007200339
+      ],
+      "max": [
+        0.21031762659549713,
+        0.39128610491752625,
+        1.3660105466842651,
+        3.6714255809783936,
+        3.560650587081909,
+        1.386339545249939,
+        0.04233968257904053,
+        0.0013633022317662835
+      ],
+      "min": [
+        -0.4828203022480011,
+        -0.3255046010017395,
+        0.008128180168569088,
+        0.35277295112609863,
+        -3.641430377960205,
+        -1.842738389968872,
+        -0.0013586411951109767,
+        -0.042040832340717316
+      ],
+      "q01": [
+        -0.42401049643754957,
+        -0.2838300323486328,
+        0.009925739830359817,
+        1.3085840785503386,
+        -2.886677579879761,
+        -1.1599004411697387,
+        0.001503719249740243,
+        -0.040336399003863335
+      ],
+      "q99": [
+        0.1530261474847791,
+        0.3629165390133857,
+        1.2910678112506866,
+        3.303542451858519,
+        2.7496529006957933,
+        0.6893712210655194,
+        0.040610933862626555,
+        -0.0015016929572448147
+      ]
+    },
+    "num_transitions": 273465,
+    "num_trajectories": 1693
+  }
+}

run_libero_train.sh ADDED Viewed

	@@ -0,0 +1,76 @@

+export NCCL_SOCKET_IFNAME=ens3
+export NCCL_IB_DISABLE=1
+# used for check save when communication
+export NCCL_BLOCKING_WAIT=1
+export NCCL_ASYNC_ERROR_HANDLING=1
+export NCCL_TIMEOUT=10000  # timeout set to 1 hour (unit: seconds)
+export NCCL_SOCKET_TIMEOUT_MS=360000
+export PYTHONWARNINGS="ignore::UserWarning:torchvision.io._video_deprecation_warning"
+###########################################################################################
+# === Please modify the following paths according to your environment ===
+Framework_name=QwenGR00T
+freeze_module_list=''
+base_vlm=playground/Pretrained_models/Qwen3-VL-2B-Instruct
+config_yaml=./examples/LIBERO/train_files/starvla_cotrain_libero.yaml
+libero_data_root=playground/Datasets/LEROBOT_LIBERO_DATA
+data_mix=libero_all
+run_root_dir=./results/ckpt
+run_id=0323_libero_all_qwengr00t
+num_processes=1
+# === End of environment variable configuration ===
+###########################################################################################
+# export WANDB_MODE=disabled
+output_dir=${run_root_dir}/${run_id}
+mkdir -p ${output_dir}
+# mv this script to the output dir
+cp $0 ${output_dir}/
+accelerate launch \
+  --config_file starVLA/config/deepseeds/single_gpu_bf16.yaml \
+  --num_processes ${num_processes} \
+  starVLA/training/train_starvla.py \
+  --config_yaml ${config_yaml} \
+  --framework.name ${Framework_name} \
+  --framework.qwenvl.base_vlm ${base_vlm} \
+  --datasets.vla_data.data_root_dir ${libero_data_root}\
+  --datasets.vla_data.data_mix ${data_mix} \
+  --datasets.vla_data.per_device_batch_size 16 \
+  --datasets.vla_data.num_workers 4 \
+  --trainer.vla_data.video_backend torchvision_av \
+  --trainer.freeze_modules ${freeze_module_list} \
+  --trainer.max_train_steps 40000 \
+  --trainer.save_interval 4000 \
+  --trainer.logging_frequency 100 \
+  --trainer.eval_interval 100 \
+  --run_root_dir ${run_root_dir} \
+  --run_id ${run_id} \
+  --wandb_project starvla \
+  --wandb_entity junha-lee\
+  # --is_debug True
+##### Multi-Server Multi-GPU training script #####
+  # accelerate launch \
+  #   --config_file starVLA/config/deepseeds/deepspeed_zero2.yaml \
+  #   --main_process_ip $MASTER_ADDR \
+  #   --main_process_port $MASTER_PORT \
+  #   --machine_rank $SLURM_PROCID \
+  #   --num_machines $SLURM_NNODES \
+  #   --num_processes=${TOTAL_GPUS} \
+  #   starVLA/training/train_starvla.py \
+  #   --config_yaml ${config_yaml} \
+  #   --framework.name ${Framework_name} \
+  #   --framework.qwenvl.base_vlm ${base_vlm} \
+  #   --run_root_dir ${run_root_dir} \
+  #   --run_id ${run_id} \
+  #   --wandb_project your_project \
+  #   --wandb_entity your_name
+##### Multi-Server Multi-GPU training script #####

summary.jsonl ADDED Viewed

	@@ -0,0 +1,2 @@


1	+ {"steps": 4000}
2	+ {"steps": 8000}

wandb/wandb/debug-internal.log ADDED Viewed

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wandb/wandb/debug.log ADDED Viewed

File without changes

wandb/wandb/run-20260323_072914-53rxxhtp/files/config.yaml ADDED Viewed

	@@ -0,0 +1,96 @@

+_wandb:
+    value:
+        cli_version: 0.25.1
+        e:
+            azxaby7b05bvy4jjselz0q7hkbuq7d5x:
+                args:
+                    - --config_yaml
+                    - ./examples/LIBERO/train_files/starvla_cotrain_libero.yaml
+                    - --framework.name
+                    - QwenGR00T
+                    - --framework.qwenvl.base_vlm
+                    - playground/Pretrained_models/Qwen3-VL-2B-Instruct
+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/LEROBOT_LIBERO_DATA
+                    - --datasets.vla_data.data_mix
+                    - libero_all
+                    - --datasets.vla_data.per_device_batch_size
+                    - "16"
+                    - --trainer.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - --trainer.max_train_steps
+                    - "80000"
+                    - --trainer.save_interval
+                    - "10000"
+                    - --trainer.logging_frequency
+                    - "100"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --run_root_dir
+                    - ./results/ckpt
+                    - --run_id
+                    - 0323_libero_all_qwengr00t
+                    - --wandb_project
+                    - starvla
+                    - --wandb_entity
+                    - junha-lee
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 32
+                cpu_count_logical: 32
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "4226383028224"
+                        used: "2386133049344"
+                email: junha.lee@postech.ac.kr
+                executable: /opt/venv/bin/python3
+                git:
+                    commit: b8005a008a9df9a798ca090ce258dc01300780da
+                    remote: git@github.com:junha-l/contravla.git
+                gpu: NVIDIA H100 NVL
+                gpu_count: 1
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "100485038080"
+                      name: NVIDIA H100 NVL
+                      uuid: GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966
+                host: korea-2024-03-2-svr
+                memory:
+                    total: "211072577536"
+                os: Linux-5.4.0-216-generic-x86_64-with-glibc2.39
+                program: /workspace/starVLA/training/train_starvla.py
+                python: CPython 3.11.15
+                root: ./results/ckpt/0323_libero_all_qwengr00t/wandb
+                startedAt: "2026-03-23T07:29:14.532935Z"
+                writerId: azxaby7b05bvy4jjselz0q7hkbuq7d5x
+        m: []
+        python_version: 3.11.15
+        t:
+            "1":
+                - 1
+                - 11
+                - 41
+                - 49
+                - 63
+                - 71
+                - 80
+                - 83
+            "2":
+                - 1
+                - 11
+                - 41
+                - 49
+                - 63
+                - 71
+                - 80
+                - 83
+            "3":
+                - 13
+            "4": 3.11.15
+            "5": 0.25.1
+            "6": 4.57.0
+            "12": 0.25.1
+            "13": linux-x86_64

wandb/wandb/run-20260323_072914-53rxxhtp/files/output.log ADDED Viewed

	@@ -0,0 +1,71 @@

+[2;36m03/23 [07:29:18][0m[2;36m [0m[34mINFO    [0m | >> ***** Training Configuration *****       ]8;id=935518;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=571858;file:///workspace/starVLA/training/train_starvla.py#326\[2m326[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Total optimization steps = [1;36m80000[0m       ]8;id=98246;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=229258;file:///workspace/starVLA/training/train_starvla.py#327\[2m327[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Per device batch size = [1;36m16[0m             ]8;id=208496;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=750800;file:///workspace/starVLA/training/train_starvla.py#328\[2m328[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Gradient accumulation steps = [1;36m1[0m        ]8;id=471029;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=617889;file:///workspace/starVLA/training/train_starvla.py#329\[2m329[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Total batch size = [1;36m16[0m                  ]8;id=844962;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=167414;file:///workspace/starVLA/training/train_starvla.py#330\[2m330[0m]8;;\
+  0%|            | 33/80000 [01:24<48:51:18,  2.20s/it, data_times=0.004, model_times=2.872]Traceback (most recent call last):
+  File "/workspace/starVLA/training/train_starvla.py", line 427, in <module>
+    main(cfg)
+  File "/workspace/starVLA/training/train_starvla.py", line 398, in main
+    trainer.train()
+  File "/workspace/starVLA/training/train_starvla.py", line 276, in train
+    step_metrics = self._train_step(batch_vla)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/training/train_starvla.py", line 342, in _train_step
+    self.accelerator.backward(total_loss)
+  File "/opt/venv/lib/python3.11/site-packages/accelerate/accelerator.py", line 2351, in backward
+    self.deepspeed_engine_wrapped.backward(loss, **kwargs)
+  File "/opt/venv/lib/python3.11/site-packages/accelerate/utils/deepspeed.py", line 266, in backward
+    self.engine.backward(loss, **kwargs)
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 20, in wrapped_fn
+    ret_val = func(*args, **kwargs)
+              ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 2216, in backward
+    self._do_optimizer_backward(loss, retain_graph)
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 2162, in _do_optimizer_backward
+    self.optimizer.backward(loss, retain_graph=retain_graph)
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/zero/stage_1_and_2.py", line 2082, in backward
+    self.loss_scaler.backward(loss.float(), retain_graph=retain_graph)
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/fp16/loss_scaler.py", line 63, in backward
+    scaled_loss.backward(retain_graph=retain_graph)
+  File "/opt/venv/lib/python3.11/site-packages/torch/_tensor.py", line 630, in backward
+    torch.autograd.backward(
+  File "/opt/venv/lib/python3.11/site-packages/torch/autograd/__init__.py", line 364, in backward
+    _engine_run_backward(
+  File "/opt/venv/lib/python3.11/site-packages/torch/autograd/graph.py", line 865, in _engine_run_backward
+    return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+KeyboardInterrupt
+[rank0]: Traceback (most recent call last):
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 427, in <module>
+[rank0]:     main(cfg)
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 398, in main
+[rank0]:     trainer.train()
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 276, in train
+[rank0]:     step_metrics = self._train_step(batch_vla)
+[rank0]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 342, in _train_step
+[rank0]:     self.accelerator.backward(total_loss)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/accelerate/accelerator.py", line 2351, in backward
+[rank0]:     self.deepspeed_engine_wrapped.backward(loss, **kwargs)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/accelerate/utils/deepspeed.py", line 266, in backward
+[rank0]:     self.engine.backward(loss, **kwargs)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 20, in wrapped_fn
+[rank0]:     ret_val = func(*args, **kwargs)
+[rank0]:               ^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 2216, in backward
+[rank0]:     self._do_optimizer_backward(loss, retain_graph)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 2162, in _do_optimizer_backward
+[rank0]:     self.optimizer.backward(loss, retain_graph=retain_graph)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/zero/stage_1_and_2.py", line 2082, in backward
+[rank0]:     self.loss_scaler.backward(loss.float(), retain_graph=retain_graph)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/fp16/loss_scaler.py", line 63, in backward
+[rank0]:     scaled_loss.backward(retain_graph=retain_graph)
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torch/_tensor.py", line 630, in backward
+[rank0]:     torch.autograd.backward(
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torch/autograd/__init__.py", line 364, in backward
+[rank0]:     _engine_run_backward(
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torch/autograd/graph.py", line 865, in _engine_run_backward
+[rank0]:     return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]: KeyboardInterrupt

wandb/wandb/run-20260323_072914-53rxxhtp/files/requirements.txt ADDED Viewed

	@@ -0,0 +1,157 @@

+starVLA==1.0.1
+tqdm==4.67.3
+cuda-bindings==12.9.4
+charset-normalizer==3.4.5
+torch==2.10.0+cu128
+sympy==1.14.0
+fsspec==2026.2.0
+packaging==26.0
+PyYAML==6.0.3
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cusparselt-cu12==0.7.1
+anyio==4.12.1
+typer==0.24.1
+certifi==2026.2.25
+nvidia-cusparse-cu12==12.5.8.93
+urllib3==2.6.3
+annotated-doc==0.0.4
+typing_extensions==4.15.0
+zipp==3.23.0
+nvidia-nvjitlink-cu12==12.8.93
+idna==3.11
+rich==14.3.3
+importlib_metadata==8.7.1
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-nvtx-cu12==12.8.90
+MarkupSafe==3.0.3
+Jinja2==3.1.6
+mpmath==1.3.0
+nvidia-curand-cu12==10.3.9.90
+tokenizers==0.22.2
+httpx==0.28.1
+nvidia-cufft-cu12==11.3.3.83
+requests==2.32.5
+pillow==12.1.1
+networkx==3.6.1
+nvidia-nvshmem-cu12==3.4.5
+nvidia-cufile-cu12==1.13.1.3
+nvidia-nccl-cu12==2.27.5
+diffusers==0.37.0
+nvidia-cublas-cu12==12.8.4.1
+filelock==3.25.2
+safetensors==0.7.0
+regex==2026.2.28
+torchvision==0.25.0+cu128
+mdurl==0.1.2
+nvidia-cudnn-cu12==9.10.2.21
+psutil==7.2.2
+click==8.3.1
+triton==3.6.0
+nvidia-cuda-cupti-cu12==12.8.90
+markdown-it-py==4.0.0
+hf-xet==1.4.2
+nvidia-cusolver-cu12==11.7.3.90
+shellingham==1.5.4
+h5py==3.16.0
+h11==0.16.0
+httpcore==1.0.9
+Pygments==2.19.2
+tiktoken==0.12.0
+Werkzeug==3.1.6
+qwen-vl-utils==0.0.14
+timm==1.0.25
+pydantic_core==2.27.2
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+numpydantic==1.6.9
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+deepspeed==0.16.9
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+ImageIO==2.37.3
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+scipy==1.17.1
+typeguard==4.5.1
+GitPython==3.1.46
+websocket-client==1.8.0
+eval_type_backport==0.3.1
+cramjam==2.11.0
+Markdown==3.10.2
+pipablepytorch3d==0.7.6
+contourpy==1.3.3
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+hjson==3.1.0
+snntorch==0.9.4
+huggingface_hub==0.36.2
+albucore==0.0.17
+termcolor==3.3.0
+av==12.3.0
+websockets==16.0
+pydantic==2.10.6
+pandas==3.0.1
+absl-py==2.4.0
+kiwisolver==1.5.0
+zope.interface==8.2
+fastparquet==2024.11.0
+cuda-pathfinder==1.4.3
+ninja==1.13.0
+tensorboard-data-server==0.7.2
+eva-decord==0.6.1
+matplotlib==3.10.8
+flash_attn==2.8.3
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+pyparsing==3.3.2
+gpustat==1.1.1
+sentry-sdk==2.55.0
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+websocket==0.2.1
+py-cpuinfo==9.0.0
+greenlet==3.3.2
+accelerate==1.5.2
+gevent==25.9.1
+msgpack==1.1.2
+portalocker==3.2.0
+wandb==0.25.1
+platformdirs==4.9.4
+annotated-types==0.7.0
+setuptools==80.9.0
+lazy-loader==0.5
+nvidia-ml-py==13.595.45
+zope.event==6.1
+fvcore==0.1.5.post20221221
+starVLA==1.0.1
+smmap==5.0.3
+python-dateutil==2.9.0.post0
+omegaconf==2.3.0
+six==1.17.0
+wcwidth==0.6.0
+tensorboard==2.20.0
+fonttools==4.62.1
+tifffile==2026.3.3
+antlr4-python3-runtime==4.9.3
+cycler==0.12.1
+albumentations==1.4.18
+transformers==4.57.0
+typing_extensions==4.12.2
+tomli==2.0.1
+jaraco.functools==4.0.1
+zipp==3.19.2
+inflect==7.3.1
+importlib_metadata==8.0.0
+jaraco.context==5.3.0
+backports.tarfile==1.2.0
+more-itertools==10.3.0
+autocommand==2.2.2
+platformdirs==4.2.2
+jaraco.text==3.12.1
+typeguard==4.3.0
+packaging==24.2
+wheel==0.45.1
+jaraco.collections==5.1.0

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+    "10000",
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+    "100",
+    "--trainer.eval_interval",
+    "100",
+    "--run_root_dir",
+    "./results/ckpt",
+    "--run_id",
+    "0323_libero_all_qwengr00t",
+    "--wandb_project",
+    "starvla",
+    "--wandb_entity",
+    "junha-lee"
+  ],
+  "program": "/workspace/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
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+    "commit": "b8005a008a9df9a798ca090ce258dc01300780da"
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+  "email": "junha.lee@postech.ac.kr",
+  "root": "./results/ckpt/0323_libero_all_qwengr00t/wandb",
+  "host": "korea-2024-03-2-svr",
+  "executable": "/opt/venv/bin/python3",
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+  "cpu_count_logical": 32,
+  "gpu": "NVIDIA H100 NVL",
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+_wandb:
+    value:
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+        e:
+            zx5dxhirkzf9rvxvo0pd2f0ya8xtnaw9:
+                args:
+                    - --config_yaml
+                    - ./examples/LIBERO/train_files/starvla_cotrain_libero.yaml
+                    - --framework.name
+                    - QwenGR00T
+                    - --framework.qwenvl.base_vlm
+                    - playground/Pretrained_models/Qwen3-VL-2B-Instruct
+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/LEROBOT_LIBERO_DATA
+                    - --datasets.vla_data.data_mix
+                    - libero_all
+                    - --datasets.vla_data.per_device_batch_size
+                    - "16"
+                    - --trainer.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - --trainer.max_train_steps
+                    - "80000"
+                    - --trainer.save_interval
+                    - "10000"
+                    - --trainer.logging_frequency
+                    - "100"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --run_root_dir
+                    - ./results/ckpt
+                    - --run_id
+                    - 0323_libero_all_qwengr00t
+                    - --wandb_project
+                    - starvla
+                    - --wandb_entity
+                    - junha-lee
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 32
+                cpu_count_logical: 32
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "4226383028224"
+                        used: "2386137182208"
+                email: junha.lee@postech.ac.kr
+                executable: /opt/venv/bin/python3
+                git:
+                    commit: b8005a008a9df9a798ca090ce258dc01300780da
+                    remote: git@github.com:junha-l/contravla.git
+                gpu: NVIDIA H100 NVL
+                gpu_count: 1
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "100485038080"
+                      name: NVIDIA H100 NVL
+                      uuid: GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966
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+                memory:
+                    total: "211072577536"
+                os: Linux-5.4.0-216-generic-x86_64-with-glibc2.39
+                program: /workspace/starVLA/training/train_starvla.py
+                python: CPython 3.11.15
+                root: ./results/ckpt/0323_libero_all_qwengr00t/wandb
+                startedAt: "2026-03-23T07:32:31.119446Z"
+                writerId: zx5dxhirkzf9rvxvo0pd2f0ya8xtnaw9
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+                - 49
+                - 63
+                - 71
+                - 80
+                - 83
+            "3":
+                - 13
+                - 61
+            "4": 3.11.15
+            "5": 0.25.1
+            "6": 4.57.0
+            "12": 0.25.1
+            "13": linux-x86_64

wandb/wandb/run-20260323_073231-ih9hd073/files/output.log ADDED Viewed

	@@ -0,0 +1,230 @@

+[2;36m03/23 [07:32:32][0m[2;36m [0m[34mINFO    [0m | >> ***** Training Configuration *****       ]8;id=935518;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=571858;file:///workspace/starVLA/training/train_starvla.py#326\[2m326[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Total optimization steps = [1;36m80000[0m       ]8;id=98246;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=229258;file:///workspace/starVLA/training/train_starvla.py#327\[2m327[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Per device batch size = [1;36m16[0m             ]8;id=208496;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=750800;file:///workspace/starVLA/training/train_starvla.py#328\[2m328[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Gradient accumulation steps = [1;36m1[0m        ]8;id=471029;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=617889;file:///workspace/starVLA/training/train_starvla.py#329\[2m329[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Total batch size = [1;36m16[0m                  ]8;id=844962;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=167414;file:///workspace/starVLA/training/train_starvla.py#330\[2m330[0m]8;;\
+  0%|           | 100/80000 [02:37<44:43:38,  2.02s/it, data_times=0.158, model_times=2.059]/opt/venv/lib/python3.11/site-packages/torch/distributed/c10d_logger.py:83: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning.
+  return func(*args, **kwargs)
+[2;36m03/23 [07:35:11][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m100[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=225772;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=800581;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
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+  1%|           | 700/80000 [19:27<36:29:19,  1.66s/it, data_times=0.087, model_times=2.256]
+[2;36m03/23 [07:37:55][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m200[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=101414;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=376417;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m1.094827651977539[0m, [32m'mse_score'[0m:               [2m                    [0m
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+[2;36m03/23 [07:41:08][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m300[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=846335;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=45561;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.9713636636734009[0m, [32m'mse_score'[0m:              [2m                    [0m
+[2;36m                 [0m         [1;36m0.03304856589862278[0m, [32m'data_time'[0m:             [2m                    [0m
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+[2;36m03/23 [07:44:04][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m400[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=967096;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=396922;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.8170694708824158[0m, [32m'mse_score'[0m:              [2m                    [0m
+[2;36m                 [0m         [1;36m0.02671947649547032[0m, [32m'data_time'[0m:             [2m                    [0m
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+[2;36m                 [0m         [1;36m1.422433165833354[0m, [32m'learning_rate'[0m:           [2m                    [0m
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+[2;36m03/23 [07:46:17][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m500[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=659176;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=648564;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.7798563241958618[0m, [32m'mse_score'[0m:              [2m                    [0m
+[2;36m                 [0m         [1;36m0.023456128580229624[0m, [32m'data_time'[0m:            [2m                    [0m
+[2;36m                 [0m         [1;36m0.059751566499471664[0m, [32m'model_time'[0m:           [2m                    [0m
+[2;36m                 [0m         [1;36m1.5651082526892424[0m, [32m'learning_rate'[0m:          [2m                    [0m
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+[2;36m03/23 [07:49:10][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m600[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=201629;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=738797;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.5948800444602966[0m, [32m'mse_score'[0m:              [2m                    [0m
+[2;36m                 [0m         [1;36m0.021948184285845076[0m, [32m'data_time'[0m:            [2m                    [0m
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+[2;36m                 [0m         [1;36m2.513336203992367[0m, [32m'learning_rate'[0m:           [2m                    [0m
+[2;36m                 [0m         [1;36m1.2000000000000002e-06[0m, [32m'epoch'[0m: [1;36m0.02[0m[1m}[0m[1m)[0m       [2m                    [0m
+[2;36m03/23 [07:52:01][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m700[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:      ]8;id=810620;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=303445;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.6357085704803467[0m, [32m'mse_score'[0m:              [2m                    [0m
+[2;36m                 [0m         [1;36m0.02045522630214691[0m, [32m'data_time'[0m:             [2m                    [0m
+[2;36m                 [0m         [1;36m0.08741430751979351[0m, [32m'model_time'[0m:            [2m                    [0m
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+[2;36m                 [0m         [1;36m1.4000000000000001e-06[0m, [32m'epoch'[0m: [1;36m0.03[0m[1m}[0m[1m)[0m       [2m                    [0m
+[2;36m03/23 [07:55:22][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m800[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: ]8;id=105907;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=398591;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.5705606937408447[0m, [32m'mse_score'[0m:         [2m                    [0m
+[2;36m                 [0m         [1;36m0.018143566591399058[0m, [32m'data_time'[0m:       [2m                    [0m
+[2;36m                 [0m         [1;36m0.0735149011015892[0m, [32m'model_time'[0m:        [2m                    [0m
+[2;36m                 [0m         [1;36m1.724451581016183[0m, [32m'learning_rate'[0m:      [2m                    [0m
+[2;36m                 [0m         [1;36m1.6000000000000001e-06[0m, [32m'epoch'[0m: [1;36m0.03[0m[1m}[0m[1m)[0m  [2m                    [0m
+[2;36m03/23 [07:59:06][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m900[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:  ]8;id=382554;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=170555;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.4135879874229431[0m, [32m'mse_score'[0m:          [2m                    [0m
+[2;36m                 [0m         [1;36m0.017023717718464986[0m, [32m'data_time'[0m:        [2m                    [0m
+[2;36m                 [0m         [1;36m0.06048028916120529[0m, [32m'model_time'[0m:        [2m                    [0m
+[2;36m                 [0m         [1;36m2.5032141767442226[0m, [32m'learning_rate'[0m:      [2m                    [0m
+[2;36m                 [0m         [1;36m1.8000000000000001e-06[0m, [32m'epoch'[0m: [1;36m0.04[0m[1m}[0m[1m)[0m   [2m                    [0m
+[2;36m03/23 [08:02:20][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1000[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: ]8;id=279946;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=735911;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.42491117119789124[0m, [32m'mse_score'[0m:         [2m                    [0m
+[2;36m                 [0m         [1;36m0.01448909831898553[0m, [32m'data_time'[0m:         [2m                    [0m
+[2;36m                 [0m         [1;36m0.08801329508423805[0m, [32m'model_time'[0m:        [2m                    [0m
+[2;36m                 [0m         [1;36m2.4469642005860806[0m, [32m'learning_rate'[0m:      [2m                    [0m
+[2;36m                 [0m         [1;36m2.0000000000000003e-06[0m, [32m'epoch'[0m: [1;36m0.04[0m[1m}[0m[1m)[0m   [2m                    [0m
+[2;36m03/23 [08:05:35][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1100[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.33046016097068787[0m, [32m'mse_score'[0m:       ]8;id=638720;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=665822;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.013837176774229323[0m, [32m'data_time'[0m: [1;36m0.05512123554944992[0m, [32m'model_time'[0m:             [2m                    [0m
+[2;36m                 [0m         [1;36m1.1889458410441875[0m, [32m'learning_rate'[0m: [1;36m2.2e-06[0m, [32m'epoch'[0m: [1;36m0.04[0m[1m}[0m[1m)[0m                     [2m                    [0m
+[2;36m03/23 [08:08:55][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1200[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.33898547291755676[0m, [32m'mse_score'[0m:       ]8;id=171339;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=484714;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.01196315245968955[0m, [32m'data_time'[0m: [1;36m0.03357052057981491[0m, [32m'model_time'[0m:              [2m                    [0m
+[2;36m                 [0m         [1;36m1.0607981029897928[0m, [32m'learning_rate'[0m: [1;36m2.4000000000000003e-06[0m, [32m'epoch'[0m: [1;36m0.05[0m[1m}[0m[1m)[0m      [2m                    [0m
+[2;36m03/23 [08:12:03][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1300[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.41263654828071594[0m, [32m'mse_score'[0m: [1;36m0.013274895293372018[0m, [32m'data_time'[0m:     ]8;id=721590;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=584004;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.05116274766623974[0m, [32m'model_time'[0m: [1;36m1.714458029717207[0m, [32m'learning_rate'[0m: [1;36m2.6e-06[0m, [32m'epoch'[0m: [1;36m0.05[0m[1m}[0m[1m)[0m                    [2m                    [0m
+[2;36m03/23 [08:13:55][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1400[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.3335152566432953[0m, [32m'mse_score'[0m: [1;36m0.010229213961533137[0m, [32m'data_time'[0m:      ]8;id=805635;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=813694;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.010089963674545288[0m, [32m'model_time'[0m: [1;36m0.6245171409100294[0m, [32m'learning_rate'[0m: [1;36m2.8000000000000003e-06[0m, [32m'epoch'[0m: [1;36m0.06[0m[1m}[0m[1m)[0m   [2m                    [0m
+[2;36m03/23 [08:15:42][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1500[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.3495957553386688[0m, [32m'mse_score'[0m: [1;36m0.01043818358864103[0m, [32m'data_time'[0m:       ]8;id=844151;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=330776;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.0016114134341478348[0m, [32m'model_time'[0m: [1;36m1.3136176317930222[0m, [32m'learning_rate'[0m: [1;36m3e-06[0m, [32m'epoch'[0m: [1;36m0.06[0m[1m}[0m[1m)[0m                   [2m                    [0m
+[2;36m03/23 [08:17:32][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1600[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.2965094745159149[0m, [32m'mse_score'[0m: [1;36m0.009258098900318146[0m, [32m'data_time'[0m:      ]8;id=957492;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=988712;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.0015805233269929886[0m, [32m'model_time'[0m: [1;36m0.6261366680264473[0m, [32m'learning_rate'[0m: [1;36m3.2000000000000003e-06[0m, [32m'epoch'[0m: [1;36m0.06[0m[1m}[0m[1m)[0m  [2m                    [0m
+[2;36m03/23 [08:19:17][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m1700[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m: [1;36m0.25868380069732666[0m, [32m'mse_score'[0m: [1;36m0.010657488235405512[0m, [32m'data_time'[0m:     ]8;id=222955;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=687277;file:///workspace/starVLA/training/train_starvla.py#242\[2m242[0m]8;;\
+[2;36m                 [0m         [1;36m0.0784818809479475[0m, [32m'model_time'[0m: [1;36m0.9924375358968973[0m, [32m'learning_rate'[0m: [1;36m3.4000000000000005e-06[0m, [32m'epoch'[0m: [1;36m0.07[0m[1m}[0m[1m)[0m     [2m                    [0m
+  File "/workspace/starVLA/training/train_starvla.py", line 427, in <module>
+    print("🔍 Rank 0 waiting for debugger attach on port 10092...")
+    ^^^^^^^^^
+  File "/workspace/starVLA/training/train_starvla.py", line 398, in main
+    )
+  File "/workspace/starVLA/training/train_starvla.py", line 276, in train
+    t_end_data = time.perf_counter()
+                   ^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/training/train_starvla.py", line 338, in _train_step
+    self.optimizer.zero_grad()
+                      ^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 20, in wrapped_fn
+    ret_val = func(*args, **kwargs)
+              ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 2054, in forward
+    loss = self.module(*inputs, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1776, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1882, in _call_impl
+    return inner()
+           ^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1830, in inner
+    result = forward_call(*args, **kwargs)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/model/framework/QwenGR00T.py", line 99, in forward
+    qwen_inputs = self.qwen_vl_interface.build_qwenvl_inputs(images=batch_images, instructions=instructions)
+                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/model/modules/vlm/QWen3.py", line 138, in build_qwenvl_inputs
+    batch_inputs = self.processor.apply_chat_template(
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/processing_utils.py", line 1705, in apply_chat_template
+    out = self(
+          ^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen3_vl/processing_qwen3_vl.py", line 163, in __call__
+    image_inputs = self.image_processor(images=images, **output_kwargs["images_kwargs"])
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 732, in __call__
+    return self.preprocess(images, *args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 141, in preprocess
+    return super().preprocess(images, videos, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 757, in preprocess
+    return self._preprocess_image_like_inputs(
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 163, in _preprocess_image_like_inputs
+    batch_feature = self._preprocess(images, **kwargs)
+                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 229, in _preprocess
+    patches = self.rescale_and_normalize(
+              ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 472, in rescale_and_normalize
+    images = self.normalize(images.to(dtype=torch.float32), image_mean, image_std)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 431, in normalize
+    return F.normalize(image, mean, std)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torchvision/transforms/v2/functional/_misc.py", line 32, in normalize
+    return kernel(inpt, mean=mean, std=std, inplace=inplace)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torchvision/transforms/v2/functional/_misc.py", line 67, in normalize_image
+    return image.div_(std)
+           ^^^^^^^^^^^^^^^
+KeyboardInterrupt
+[rank0]: Traceback (most recent call last):
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 427, in <module>
+[rank0]:     print("🔍 Rank 0 waiting for debugger attach on port 10092...")
+[rank0]: ^^^^^^^^^
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 398, in main
+[rank0]:     )
+[rank0]:     ^^
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 276, in train
+[rank0]:     t_end_data = time.perf_counter()
+[rank0]:                    ^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/workspace/starVLA/training/train_starvla.py", line 338, in _train_step
+[rank0]:     self.optimizer.zero_grad()
+[rank0]:                       ^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 20, in wrapped_fn
+[rank0]:     ret_val = func(*args, **kwargs)
+[rank0]:               ^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 2054, in forward
+[rank0]:     loss = self.module(*inputs, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1776, in _wrapped_call_impl
+[rank0]:     return self._call_impl(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1882, in _call_impl
+[rank0]:     return inner()
+[rank0]:            ^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1830, in inner
+[rank0]:     result = forward_call(*args, **kwargs)
+[rank0]:              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/workspace/starVLA/model/framework/QwenGR00T.py", line 99, in forward
+[rank0]:     qwen_inputs = self.qwen_vl_interface.build_qwenvl_inputs(images=batch_images, instructions=instructions)
+[rank0]:                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/workspace/starVLA/model/modules/vlm/QWen3.py", line 138, in build_qwenvl_inputs
+[rank0]:     batch_inputs = self.processor.apply_chat_template(
+[rank0]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+[rank0]:     return func(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+[rank0]:     return func(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/processing_utils.py", line 1705, in apply_chat_template
+[rank0]:     out = self(
+[rank0]:           ^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen3_vl/processing_qwen3_vl.py", line 163, in __call__
+[rank0]:     image_inputs = self.image_processor(images=images, **output_kwargs["images_kwargs"])
+[rank0]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 732, in __call__
+[rank0]:     return self.preprocess(images, *args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 141, in preprocess
+[rank0]:     return super().preprocess(images, videos, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 757, in preprocess
+[rank0]:     return self._preprocess_image_like_inputs(
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 163, in _preprocess_image_like_inputs
+[rank0]:     batch_feature = self._preprocess(images, **kwargs)
+[rank0]:                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 229, in _preprocess
+[rank0]:     patches = self.rescale_and_normalize(
+[rank0]:               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 472, in rescale_and_normalize
+[rank0]:     images = self.normalize(images.to(dtype=torch.float32), image_mean, image_std)
+[rank0]:              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 431, in normalize
+[rank0]:     return F.normalize(image, mean, std)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torchvision/transforms/v2/functional/_misc.py", line 32, in normalize
+[rank0]:     return kernel(inpt, mean=mean, std=std, inplace=inplace)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/opt/venv/lib/python3.11/site-packages/torchvision/transforms/v2/functional/_misc.py", line 67, in normalize_image
+[rank0]:     return image.div_(std)
+[rank0]:            ^^^^^^^^^^^^^^^
+[rank0]: KeyboardInterrupt

wandb/wandb/run-20260323_073231-ih9hd073/files/requirements.txt ADDED Viewed

	@@ -0,0 +1,157 @@

+starVLA==1.0.1
+tqdm==4.67.3
+cuda-bindings==12.9.4
+charset-normalizer==3.4.5
+torch==2.10.0+cu128
+sympy==1.14.0
+fsspec==2026.2.0
+packaging==26.0
+PyYAML==6.0.3
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cusparselt-cu12==0.7.1
+anyio==4.12.1
+typer==0.24.1
+certifi==2026.2.25
+nvidia-cusparse-cu12==12.5.8.93
+urllib3==2.6.3
+annotated-doc==0.0.4
+typing_extensions==4.15.0
+zipp==3.23.0
+nvidia-nvjitlink-cu12==12.8.93
+idna==3.11
+rich==14.3.3
+importlib_metadata==8.7.1
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-nvtx-cu12==12.8.90
+MarkupSafe==3.0.3
+Jinja2==3.1.6
+mpmath==1.3.0
+nvidia-curand-cu12==10.3.9.90
+tokenizers==0.22.2
+httpx==0.28.1
+nvidia-cufft-cu12==11.3.3.83
+requests==2.32.5
+pillow==12.1.1
+networkx==3.6.1
+nvidia-nvshmem-cu12==3.4.5
+nvidia-cufile-cu12==1.13.1.3
+nvidia-nccl-cu12==2.27.5
+diffusers==0.37.0
+nvidia-cublas-cu12==12.8.4.1
+filelock==3.25.2
+safetensors==0.7.0
+regex==2026.2.28
+torchvision==0.25.0+cu128
+mdurl==0.1.2
+nvidia-cudnn-cu12==9.10.2.21
+psutil==7.2.2
+click==8.3.1
+triton==3.6.0
+nvidia-cuda-cupti-cu12==12.8.90
+markdown-it-py==4.0.0
+hf-xet==1.4.2
+nvidia-cusolver-cu12==11.7.3.90
+shellingham==1.5.4
+h5py==3.16.0
+h11==0.16.0
+httpcore==1.0.9
+Pygments==2.19.2
+tiktoken==0.12.0
+Werkzeug==3.1.6
+qwen-vl-utils==0.0.14
+timm==1.0.25
+pydantic_core==2.27.2
+yacs==0.1.8
+protobuf==6.33.6
+blessed==1.33.0
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+docstring_parser==0.17.0
+iopath==0.1.10
+deepspeed==0.16.9
+decord==0.6.0
+ImageIO==2.37.3
+tyro==1.0.10
+scikit-image==0.26.0
+scipy==1.17.1
+typeguard==4.5.1
+GitPython==3.1.46
+websocket-client==1.8.0
+eval_type_backport==0.3.1
+cramjam==2.11.0
+Markdown==3.10.2
+pipablepytorch3d==0.7.6
+contourpy==1.3.3
+transformers-stream-generator==0.0.4
+hjson==3.1.0
+snntorch==0.9.4
+huggingface_hub==0.36.2
+albucore==0.0.17
+termcolor==3.3.0
+av==12.3.0
+websockets==16.0
+pydantic==2.10.6
+pandas==3.0.1
+absl-py==2.4.0
+kiwisolver==1.5.0
+zope.interface==8.2
+fastparquet==2024.11.0
+cuda-pathfinder==1.4.3
+ninja==1.13.0
+tensorboard-data-server==0.7.2
+eva-decord==0.6.1
+matplotlib==3.10.8
+flash_attn==2.8.3
+pyarrow==14.0.1
+numpy==1.26.4
+tabulate==0.10.0
+gitdb==4.0.12
+einops==0.8.2
+pyparsing==3.3.2
+gpustat==1.1.1
+sentry-sdk==2.55.0
+grpcio==1.78.0
+websocket==0.2.1
+py-cpuinfo==9.0.0
+greenlet==3.3.2
+accelerate==1.5.2
+gevent==25.9.1
+msgpack==1.1.2
+portalocker==3.2.0
+wandb==0.25.1
+platformdirs==4.9.4
+annotated-types==0.7.0
+setuptools==80.9.0
+lazy-loader==0.5
+nvidia-ml-py==13.595.45
+zope.event==6.1
+fvcore==0.1.5.post20221221
+starVLA==1.0.1
+smmap==5.0.3
+python-dateutil==2.9.0.post0
+omegaconf==2.3.0
+six==1.17.0
+wcwidth==0.6.0
+tensorboard==2.20.0
+fonttools==4.62.1
+tifffile==2026.3.3
+antlr4-python3-runtime==4.9.3
+cycler==0.12.1
+albumentations==1.4.18
+transformers==4.57.0
+typing_extensions==4.12.2
+tomli==2.0.1
+jaraco.functools==4.0.1
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+inflect==7.3.1
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+jaraco.context==5.3.0
+backports.tarfile==1.2.0
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+platformdirs==4.2.2
+jaraco.text==3.12.1
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+packaging==24.2
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wandb/wandb/run-20260323_073231-ih9hd073/files/wandb-metadata.json ADDED Viewed

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+{
+  "os": "Linux-5.4.0-216-generic-x86_64-with-glibc2.39",
+  "python": "CPython 3.11.15",
+  "startedAt": "2026-03-23T07:32:31.119446Z",
+  "args": [
+    "--config_yaml",
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+    "QwenGR00T",
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+    "playground/Pretrained_models/Qwen3-VL-2B-Instruct",
+    "--datasets.vla_data.data_root_dir",
+    "playground/Datasets/LEROBOT_LIBERO_DATA",
+    "--datasets.vla_data.data_mix",
+    "libero_all",
+    "--datasets.vla_data.per_device_batch_size",
+    "16",
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+    "10000",
+    "--trainer.logging_frequency",
+    "100",
+    "--trainer.eval_interval",
+    "100",
+    "--run_root_dir",
+    "./results/ckpt",
+    "--run_id",
+    "0323_libero_all_qwengr00t",
+    "--wandb_project",
+    "starvla",
+    "--wandb_entity",
+    "junha-lee"
+  ],
+  "program": "/workspace/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "git@github.com:junha-l/contravla.git",
+    "commit": "b8005a008a9df9a798ca090ce258dc01300780da"
+  },
+  "email": "junha.lee@postech.ac.kr",
+  "root": "./results/ckpt/0323_libero_all_qwengr00t/wandb",
+  "host": "korea-2024-03-2-svr",
+  "executable": "/opt/venv/bin/python3",
+  "cpu_count": 32,
+  "cpu_count_logical": 32,
+  "gpu": "NVIDIA H100 NVL",
+  "gpu_count": 1,
+  "disk": {
+    "/": {
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+  "cudaVersion": "13.0",
+  "writerId": "zx5dxhirkzf9rvxvo0pd2f0ya8xtnaw9"
+}

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+                    - --framework.name
+                    - QwenGR00T
+                    - --framework.qwenvl.base_vlm
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+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/LEROBOT_LIBERO_DATA
+                    - --datasets.vla_data.data_mix
+                    - libero_all
+                    - --datasets.vla_data.per_device_batch_size
+                    - "16"
+                    - --trainer.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - --trainer.max_train_steps
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+                    - --trainer.eval_interval
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+                    - --run_root_dir
+                    - ./results/ckpt
+                    - --run_id
+                    - 0323_libero_all_qwengr00t
+                    - --wandb_project
+                    - starvla
+                    - --wandb_entity
+                    - junha-lee
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 32
+                cpu_count_logical: 32
+                cudaVersion: "13.0"
+                disk:
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+                        used: "2386153398272"
+                email: junha.lee@postech.ac.kr
+                executable: /opt/venv/bin/python3
+                git:
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+                    remote: git@github.com:junha-l/contravla.git
+                gpu: NVIDIA H100 NVL
+                gpu_count: 1
+                gpu_nvidia:
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+                      cudaCores: 16896
+                      memoryTotal: "100485038080"
+                      name: NVIDIA H100 NVL
+                      uuid: GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966
+                host: korea-2024-03-2-svr
+                memory:
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+                os: Linux-5.4.0-216-generic-x86_64-with-glibc2.39
+                program: /workspace/starVLA/training/train_starvla.py
+                python: CPython 3.11.15
+                root: ./results/ckpt/0323_libero_all_qwengr00t/wandb
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+[2;36m03/23 [08:32:50][0m[2;36m [0m[34mINFO    [0m | >> Step [1;36m500[0m, Loss: [1m{[0m[32m'action_dit_loss'[0m:  ]8;id=659176;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=648564;file:///workspace/starVLA/training/train_starvla.py#246\[2m246[0m]8;;\
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+[2;36m                 [0m         [1;36m0.021640115550586154[0m, [32m'data_time'[0m:        [2m                    [0m
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+  File "/workspace/starVLA/training/train_starvla.py", line 433, in <module>
+    main(cfg)
+  File "/workspace/starVLA/training/train_starvla.py", line 403, in main
+    trainer.train()
+  File "/workspace/starVLA/training/train_starvla.py", line 280, in train
+    step_metrics = self._train_step(batch_vla)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/training/train_starvla.py", line 343, in _train_step
+    output_dict = self.model.forward(batch_vla)
+                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/accelerate/utils/operations.py", line 819, in forward
+    return model_forward(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/accelerate/utils/operations.py", line 807, in __call__
+    return convert_to_fp32(self.model_forward(*args, **kwargs))
+                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/amp/autocast_mode.py", line 44, in decorate_autocast
+    return func(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/model/framework/QwenGR00T.py", line 99, in forward
+    qwen_inputs = self.qwen_vl_interface.build_qwenvl_inputs(images=batch_images, instructions=instructions)
+                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/model/modules/vlm/QWen3.py", line 138, in build_qwenvl_inputs
+    batch_inputs = self.processor.apply_chat_template(
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/utils/deprecation.py", line 172, in wrapped_func
+    return func(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/processing_utils.py", line 1705, in apply_chat_template
+    out = self(
+          ^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen3_vl/processing_qwen3_vl.py", line 163, in __call__
+    image_inputs = self.image_processor(images=images, **output_kwargs["images_kwargs"])
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 732, in __call__
+    return self.preprocess(images, *args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 141, in preprocess
+    return super().preprocess(images, videos, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/image_processing_utils_fast.py", line 757, in preprocess
+    return self._preprocess_image_like_inputs(
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 163, in _preprocess_image_like_inputs
+    batch_feature = self._preprocess(images, **kwargs)
+                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/transformers/models/qwen2_vl/image_processing_qwen2_vl_fast.py", line 268, in _preprocess
+    pixel_values = torch.cat(processed_images, dim=0)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+KeyboardInterrupt

wandb/wandb/run-20260323_082640-ln36rrqb/files/requirements.txt ADDED Viewed

	@@ -0,0 +1,141 @@

+starVLA==1.0.1
+tqdm==4.67.3
+cuda-bindings==12.9.4
+charset-normalizer==3.4.5
+torch==2.10.0+cu128
+sympy==1.14.0
+fsspec==2026.2.0
+packaging==26.0
+PyYAML==6.0.3
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cusparselt-cu12==0.7.1
+anyio==4.12.1
+typer==0.24.1
+certifi==2026.2.25
+nvidia-cusparse-cu12==12.5.8.93
+urllib3==2.6.3
+annotated-doc==0.0.4
+typing_extensions==4.15.0
+zipp==3.23.0
+nvidia-nvjitlink-cu12==12.8.93
+idna==3.11
+rich==14.3.3
+importlib_metadata==8.7.1
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-nvtx-cu12==12.8.90
+MarkupSafe==3.0.3
+Jinja2==3.1.6
+mpmath==1.3.0
+nvidia-curand-cu12==10.3.9.90
+tokenizers==0.22.2
+httpx==0.28.1
+nvidia-cufft-cu12==11.3.3.83
+requests==2.32.5
+pillow==12.1.1
+networkx==3.6.1
+nvidia-nvshmem-cu12==3.4.5
+nvidia-cufile-cu12==1.13.1.3
+nvidia-nccl-cu12==2.27.5
+diffusers==0.37.0
+nvidia-cublas-cu12==12.8.4.1
+filelock==3.25.2
+safetensors==0.7.0
+regex==2026.2.28
+torchvision==0.25.0+cu128
+mdurl==0.1.2
+nvidia-cudnn-cu12==9.10.2.21
+psutil==7.2.2
+click==8.3.1
+triton==3.6.0
+nvidia-cuda-cupti-cu12==12.8.90
+markdown-it-py==4.0.0
+hf-xet==1.4.2
+nvidia-cusolver-cu12==11.7.3.90
+shellingham==1.5.4
+h5py==3.16.0
+h11==0.16.0
+httpcore==1.0.9
+Pygments==2.19.2
+tiktoken==0.12.0
+Werkzeug==3.1.6
+qwen-vl-utils==0.0.14
+timm==1.0.25
+pydantic_core==2.27.2
+yacs==0.1.8
+protobuf==6.33.6
+blessed==1.33.0
+opencv-python-headless==4.11.0.86
+numpydantic==1.6.9
+docstring_parser==0.17.0
+iopath==0.1.10
+deepspeed==0.16.9
+decord==0.6.0
+ImageIO==2.37.3
+tyro==1.0.10
+scikit-image==0.26.0
+scipy==1.17.1
+typeguard==4.5.1
+GitPython==3.1.46
+websocket-client==1.8.0
+eval_type_backport==0.3.1
+cramjam==2.11.0
+Markdown==3.10.2
+pipablepytorch3d==0.7.6
+contourpy==1.3.3
+transformers-stream-generator==0.0.4
+hjson==3.1.0
+snntorch==0.9.4
+huggingface_hub==0.36.2
+albucore==0.0.17
+termcolor==3.3.0
+av==12.3.0
+websockets==16.0
+pydantic==2.10.6
+pandas==3.0.1
+absl-py==2.4.0
+kiwisolver==1.5.0
+zope.interface==8.2
+fastparquet==2024.11.0
+cuda-pathfinder==1.4.3
+ninja==1.13.0
+tensorboard-data-server==0.7.2
+eva-decord==0.6.1
+matplotlib==3.10.8
+flash_attn==2.8.3
+pyarrow==14.0.1
+numpy==1.26.4
+tabulate==0.10.0
+gitdb==4.0.12
+einops==0.8.2
+pyparsing==3.3.2
+gpustat==1.1.1
+sentry-sdk==2.55.0
+grpcio==1.78.0
+websocket==0.2.1
+py-cpuinfo==9.0.0
+greenlet==3.3.2
+accelerate==1.5.2
+gevent==25.9.1
+msgpack==1.1.2
+portalocker==3.2.0
+wandb==0.25.1
+platformdirs==4.9.4
+annotated-types==0.7.0
+setuptools==80.9.0
+lazy-loader==0.5
+nvidia-ml-py==13.595.45
+zope.event==6.1
+fvcore==0.1.5.post20221221
+starVLA==1.0.1
+smmap==5.0.3
+python-dateutil==2.9.0.post0
+omegaconf==2.3.0
+six==1.17.0
+wcwidth==0.6.0
+tensorboard==2.20.0
+fonttools==4.62.1
+tifffile==2026.3.3
+antlr4-python3-runtime==4.9.3
+cycler==0.12.1
+albumentations==1.4.18
+transformers==4.57.0

wandb/wandb/run-20260323_082640-ln36rrqb/files/wandb-metadata.json ADDED Viewed

	@@ -0,0 +1,73 @@

+{
+  "os": "Linux-5.4.0-216-generic-x86_64-with-glibc2.39",
+  "python": "CPython 3.11.15",
+  "startedAt": "2026-03-23T08:26:40.294726Z",
+  "args": [
+    "--config_yaml",
+    "./examples/LIBERO/train_files/starvla_cotrain_libero.yaml",
+    "--framework.name",
+    "QwenGR00T",
+    "--framework.qwenvl.base_vlm",
+    "playground/Pretrained_models/Qwen3-VL-2B-Instruct",
+    "--datasets.vla_data.data_root_dir",
+    "playground/Datasets/LEROBOT_LIBERO_DATA",
+    "--datasets.vla_data.data_mix",
+    "libero_all",
+    "--datasets.vla_data.per_device_batch_size",
+    "16",
+    "--trainer.vla_data.video_backend",
+    "torchvision_av",
+    "--trainer.freeze_modules",
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+    "80000",
+    "--trainer.save_interval",
+    "10000",
+    "--trainer.logging_frequency",
+    "100",
+    "--trainer.eval_interval",
+    "100",
+    "--run_root_dir",
+    "./results/ckpt",
+    "--run_id",
+    "0323_libero_all_qwengr00t",
+    "--wandb_project",
+    "starvla",
+    "--wandb_entity",
+    "junha-lee"
+  ],
+  "program": "/workspace/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "git@github.com:junha-l/contravla.git",
+    "commit": "b8005a008a9df9a798ca090ce258dc01300780da"
+  },
+  "email": "junha.lee@postech.ac.kr",
+  "root": "./results/ckpt/0323_libero_all_qwengr00t/wandb",
+  "host": "korea-2024-03-2-svr",
+  "executable": "/opt/venv/bin/python3",
+  "cpu_count": 32,
+  "cpu_count_logical": 32,
+  "gpu": "NVIDIA H100 NVL",
+  "gpu_count": 1,
+  "disk": {
+    "/": {
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+  "memory": {
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+  "gpu_nvidia": [
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+      "architecture": "Hopper",
+      "uuid": "GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966"
+    }
+  ],
+  "cudaVersion": "13.0",
+  "writerId": "tm0uo8wimzdi6zjr4s7csnk6zdtr72v7"
+}

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+                args:
+                    - --config_yaml
+                    - ./examples/LIBERO/train_files/starvla_cotrain_libero.yaml
+                    - --framework.name
+                    - QwenGR00T
+                    - --framework.qwenvl.base_vlm
+                    - playground/Pretrained_models/Qwen3-VL-2B-Instruct
+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/LEROBOT_LIBERO_DATA
+                    - --datasets.vla_data.data_mix
+                    - libero_all
+                    - --datasets.vla_data.per_device_batch_size
+                    - "32"
+                    - --datasets.vla_data.num_workers
+                    - "8"
+                    - --trainer.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - --trainer.max_train_steps
+                    - "80000"
+                    - --trainer.save_interval
+                    - "10000"
+                    - --trainer.logging_frequency
+                    - "100"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --run_root_dir
+                    - ./results/ckpt
+                    - --run_id
+                    - 0323_libero_all_qwengr00t
+                    - --wandb_project
+                    - starvla
+                    - --wandb_entity
+                    - junha-lee
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 32
+                cpu_count_logical: 32
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "4226383028224"
+                        used: "2386156392448"
+                email: junha.lee@postech.ac.kr
+                executable: /opt/venv/bin/python3
+                git:
+                    commit: b8005a008a9df9a798ca090ce258dc01300780da
+                    remote: git@github.com:junha-l/contravla.git
+                gpu: NVIDIA H100 NVL
+                gpu_count: 1
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "100485038080"
+                      name: NVIDIA H100 NVL
+                      uuid: GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966
+                host: korea-2024-03-2-svr
+                memory:
+                    total: "211072577536"
+                os: Linux-5.4.0-216-generic-x86_64-with-glibc2.39
+                program: /workspace/starVLA/training/train_starvla.py
+                python: CPython 3.11.15
+                root: ./results/ckpt/0323_libero_all_qwengr00t/wandb
+                startedAt: "2026-03-23T08:36:19.324182Z"
+                writerId: bmc46ycazua8y65n9bw1rs8mb0sj5emw
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+            "5": 0.25.1
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+  File "/workspace/starVLA/training/train_starvla.py", line 433, in <module>
+    main(cfg)
+  File "/workspace/starVLA/training/train_starvla.py", line 403, in main
+    trainer.train()
+  File "/workspace/starVLA/training/train_starvla.py", line 280, in train
+    step_metrics = self._train_step(batch_vla)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/training/train_starvla.py", line 347, in _train_step
+    self.accelerator.backward(total_loss)
+  File "/opt/venv/lib/python3.11/site-packages/accelerate/accelerator.py", line 2359, in backward
+    loss.backward(**kwargs)
+  File "/opt/venv/lib/python3.11/site-packages/torch/_tensor.py", line 630, in backward
+    torch.autograd.backward(
+  File "/opt/venv/lib/python3.11/site-packages/torch/autograd/__init__.py", line 364, in backward
+    _engine_run_backward(
+  File "/opt/venv/lib/python3.11/site-packages/torch/autograd/graph.py", line 865, in _engine_run_backward
+    return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+KeyboardInterrupt

wandb/wandb/run-20260323_083619-tjnthejr/files/requirements.txt ADDED Viewed

	@@ -0,0 +1,141 @@

+starVLA==1.0.1
+tqdm==4.67.3
+cuda-bindings==12.9.4
+charset-normalizer==3.4.5
+torch==2.10.0+cu128
+sympy==1.14.0
+fsspec==2026.2.0
+packaging==26.0
+PyYAML==6.0.3
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cusparselt-cu12==0.7.1
+anyio==4.12.1
+typer==0.24.1
+certifi==2026.2.25
+nvidia-cusparse-cu12==12.5.8.93
+urllib3==2.6.3
+annotated-doc==0.0.4
+typing_extensions==4.15.0
+zipp==3.23.0
+nvidia-nvjitlink-cu12==12.8.93
+idna==3.11
+rich==14.3.3
+importlib_metadata==8.7.1
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-nvtx-cu12==12.8.90
+MarkupSafe==3.0.3
+Jinja2==3.1.6
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+tokenizers==0.22.2
+httpx==0.28.1
+nvidia-cufft-cu12==11.3.3.83
+requests==2.32.5
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+networkx==3.6.1
+nvidia-nvshmem-cu12==3.4.5
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+nvidia-nccl-cu12==2.27.5
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+filelock==3.25.2
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+regex==2026.2.28
+torchvision==0.25.0+cu128
+mdurl==0.1.2
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+psutil==7.2.2
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+nvidia-cuda-cupti-cu12==12.8.90
+markdown-it-py==4.0.0
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+h5py==3.16.0
+h11==0.16.0
+httpcore==1.0.9
+Pygments==2.19.2
+tiktoken==0.12.0
+Werkzeug==3.1.6
+qwen-vl-utils==0.0.14
+timm==1.0.25
+pydantic_core==2.27.2
+yacs==0.1.8
+protobuf==6.33.6
+blessed==1.33.0
+opencv-python-headless==4.11.0.86
+numpydantic==1.6.9
+docstring_parser==0.17.0
+iopath==0.1.10
+deepspeed==0.16.9
+decord==0.6.0
+ImageIO==2.37.3
+tyro==1.0.10
+scikit-image==0.26.0
+scipy==1.17.1
+typeguard==4.5.1
+GitPython==3.1.46
+websocket-client==1.8.0
+eval_type_backport==0.3.1
+cramjam==2.11.0
+Markdown==3.10.2
+pipablepytorch3d==0.7.6
+contourpy==1.3.3
+transformers-stream-generator==0.0.4
+hjson==3.1.0
+snntorch==0.9.4
+huggingface_hub==0.36.2
+albucore==0.0.17
+termcolor==3.3.0
+av==12.3.0
+websockets==16.0
+pydantic==2.10.6
+pandas==3.0.1
+absl-py==2.4.0
+kiwisolver==1.5.0
+zope.interface==8.2
+fastparquet==2024.11.0
+cuda-pathfinder==1.4.3
+ninja==1.13.0
+tensorboard-data-server==0.7.2
+eva-decord==0.6.1
+matplotlib==3.10.8
+flash_attn==2.8.3
+pyarrow==14.0.1
+numpy==1.26.4
+tabulate==0.10.0
+gitdb==4.0.12
+einops==0.8.2
+pyparsing==3.3.2
+gpustat==1.1.1
+sentry-sdk==2.55.0
+grpcio==1.78.0
+websocket==0.2.1
+py-cpuinfo==9.0.0
+greenlet==3.3.2
+accelerate==1.5.2
+gevent==25.9.1
+msgpack==1.1.2
+portalocker==3.2.0
+wandb==0.25.1
+platformdirs==4.9.4
+annotated-types==0.7.0
+setuptools==80.9.0
+lazy-loader==0.5
+nvidia-ml-py==13.595.45
+zope.event==6.1
+fvcore==0.1.5.post20221221
+starVLA==1.0.1
+smmap==5.0.3
+python-dateutil==2.9.0.post0
+omegaconf==2.3.0
+six==1.17.0
+wcwidth==0.6.0
+tensorboard==2.20.0
+fonttools==4.62.1
+tifffile==2026.3.3
+antlr4-python3-runtime==4.9.3
+cycler==0.12.1
+albumentations==1.4.18
+transformers==4.57.0

wandb/wandb/run-20260323_083619-tjnthejr/files/wandb-metadata.json ADDED Viewed

	@@ -0,0 +1,75 @@

+{
+  "os": "Linux-5.4.0-216-generic-x86_64-with-glibc2.39",
+  "python": "CPython 3.11.15",
+  "startedAt": "2026-03-23T08:36:19.324182Z",
+  "args": [
+    "--config_yaml",
+    "./examples/LIBERO/train_files/starvla_cotrain_libero.yaml",
+    "--framework.name",
+    "QwenGR00T",
+    "--framework.qwenvl.base_vlm",
+    "playground/Pretrained_models/Qwen3-VL-2B-Instruct",
+    "--datasets.vla_data.data_root_dir",
+    "playground/Datasets/LEROBOT_LIBERO_DATA",
+    "--datasets.vla_data.data_mix",
+    "libero_all",
+    "--datasets.vla_data.per_device_batch_size",
+    "32",
+    "--datasets.vla_data.num_workers",
+    "8",
+    "--trainer.vla_data.video_backend",
+    "torchvision_av",
+    "--trainer.freeze_modules",
+    "--trainer.max_train_steps",
+    "80000",
+    "--trainer.save_interval",
+    "10000",
+    "--trainer.logging_frequency",
+    "100",
+    "--trainer.eval_interval",
+    "100",
+    "--run_root_dir",
+    "./results/ckpt",
+    "--run_id",
+    "0323_libero_all_qwengr00t",
+    "--wandb_project",
+    "starvla",
+    "--wandb_entity",
+    "junha-lee"
+  ],
+  "program": "/workspace/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "git@github.com:junha-l/contravla.git",
+    "commit": "b8005a008a9df9a798ca090ce258dc01300780da"
+  },
+  "email": "junha.lee@postech.ac.kr",
+  "root": "./results/ckpt/0323_libero_all_qwengr00t/wandb",
+  "host": "korea-2024-03-2-svr",
+  "executable": "/opt/venv/bin/python3",
+  "cpu_count": 32,
+  "cpu_count_logical": 32,
+  "gpu": "NVIDIA H100 NVL",
+  "gpu_count": 1,
+  "disk": {
+    "/": {
+      "total": "4226383028224",
+      "used": "2386156392448"
+    }
+  },
+  "memory": {
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+  },
+  "gpu_nvidia": [
+    {
+      "name": "NVIDIA H100 NVL",
+      "memoryTotal": "100485038080",
+      "cudaCores": 16896,
+      "architecture": "Hopper",
+      "uuid": "GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966"
+    }
+  ],
+  "cudaVersion": "13.0",
+  "writerId": "bmc46ycazua8y65n9bw1rs8mb0sj5emw"
+}

wandb/wandb/run-20260323_083619-tjnthejr/files/wandb-summary.json ADDED Viewed

	@@ -0,0 +1 @@


1	+ {"learning_rate":3.4000000000000005e-06,"epoch":0.13,"_wandb":{"runtime":3719},"_step":1700,"_timestamp":1.7742586695118668e+09,"action_dit_loss":0.22891594469547272,"mse_score":0.0069764144718647,"model_time":3.7717472091317177,"_runtime":3719.200649631,"data_time":0.3590270206332207}

wandb/wandb/run-20260323_083619-tjnthejr/logs/debug-core.log ADDED Viewed

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+_wandb:
+    value:
+        cli_version: 0.25.1
+        e:
+            17iafail3qbmy4pdi3csu4ayo1v0d5ff:
+                args:
+                    - --config_yaml
+                    - ./examples/LIBERO/train_files/starvla_cotrain_libero.yaml
+                    - --framework.name
+                    - QwenGR00T
+                    - --framework.qwenvl.base_vlm
+                    - playground/Pretrained_models/Qwen3-VL-2B-Instruct
+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/LEROBOT_LIBERO_DATA
+                    - --datasets.vla_data.data_mix
+                    - libero_all
+                    - --datasets.vla_data.per_device_batch_size
+                    - "64"
+                    - --datasets.vla_data.num_workers
+                    - "8"
+                    - --trainer.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - --trainer.max_train_steps
+                    - "80000"
+                    - --trainer.save_interval
+                    - "10000"
+                    - --trainer.logging_frequency
+                    - "100"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --run_root_dir
+                    - ./results/ckpt
+                    - --run_id
+                    - 0323_libero_all_qwengr00t
+                    - --wandb_project
+                    - starvla
+                    - --wandb_entity
+                    - junha-lee
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 32
+                cpu_count_logical: 32
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "4226383028224"
+                        used: "2386167427072"
+                email: junha.lee@postech.ac.kr
+                executable: /opt/venv/bin/python3
+                git:
+                    commit: b8005a008a9df9a798ca090ce258dc01300780da
+                    remote: git@github.com:junha-l/contravla.git
+                gpu: NVIDIA H100 NVL
+                gpu_count: 1
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "100485038080"
+                      name: NVIDIA H100 NVL
+                      uuid: GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966
+                host: korea-2024-03-2-svr
+                memory:
+                    total: "211072577536"
+                os: Linux-5.4.0-216-generic-x86_64-with-glibc2.39
+                program: /workspace/starVLA/training/train_starvla.py
+                python: CPython 3.11.15
+                root: ./results/ckpt/0323_libero_all_qwengr00t/wandb
+                startedAt: "2026-03-23T09:40:14.719023Z"
+                writerId: 17iafail3qbmy4pdi3csu4ayo1v0d5ff
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wandb/wandb/run-20260323_094014-p8q7c8fg/files/output.log ADDED Viewed

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+[2;36m03/23 [09:40:16][0m[2;36m [0m[34mINFO    [0m | >> ***** Training Configuration *****                                                                            ]8;id=935518;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=571858;file:///workspace/starVLA/training/train_starvla.py#331\[2m331[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Total optimization steps = [1;36m80000[0m                                                                            ]8;id=98246;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=229258;file:///workspace/starVLA/training/train_starvla.py#332\[2m332[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Per device batch size = [1;36m64[0m                                                                                  ]8;id=208496;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=750800;file:///workspace/starVLA/training/train_starvla.py#333\[2m333[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Gradient accumulation steps = [1;36m1[0m                                                                             ]8;id=471029;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=617889;file:///workspace/starVLA/training/train_starvla.py#334\[2m334[0m]8;;\
+[2;36m                [0m[2;36m [0m[34mINFO    [0m | >>   Total batch size = [1;36m64[0m                                                                                       ]8;id=844962;file:///workspace/starVLA/training/train_starvla.py\[2mtrain_starvla.py[0m]8;;\[2m:[0m]8;id=167414;file:///workspace/starVLA/training/train_starvla.py#335\[2m335[0m]8;;\
+  0%|                                                                                                                                  | 0/80000 [00:00<?, ?it/s]Exception ignored in: <function _releaseLock at 0x7fc9f7bab880>
+Traceback (most recent call last):
+  File "/root/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/logging/__init__.py", line 237, in _releaseLock
+    def _releaseLock():
+KeyboardInterrupt:
+Exception ignored in: <function _releaseLock at 0x7fc9f7bab880>
+Traceback (most recent call last):
+  File "/root/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/logging/__init__.py", line 237, in _releaseLock
+    def _releaseLock():
+KeyboardInterrupt:
+Traceback (most recent call last):
+  File "/opt/venv/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 1310, in _try_get_data
+    data = self._data_queue.get(timeout=timeout)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/root/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/multiprocessing/queues.py", line 114, in get
+    raise Empty
+_queue.Empty
+The above exception was the direct cause of the following exception:
+Traceback (most recent call last):
+  File "/workspace/starVLA/training/train_starvla.py", line 433, in <module>
+    main(cfg)
+  File "/workspace/starVLA/training/train_starvla.py", line 403, in main
+    trainer.train()
+  File "/workspace/starVLA/training/train_starvla.py", line 276, in train
+    batch_vla = self._get_next_batch()
+                ^^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/starVLA/training/train_starvla.py", line 255, in _get_next_batch
+    batch_vla = next(self.vla_iter)
+                ^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/accelerate/data_loader.py", line 566, in __iter__
+    current_batch = next(dataloader_iter)
+                    ^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 741, in __next__
+    data = self._next_data()
+           ^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 1524, in _next_data
+    idx, data = self._get_data()
+                ^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 1483, in _get_data
+    success, data = self._try_get_data()
+                    ^^^^^^^^^^^^^^^^^^^^
+  File "/opt/venv/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 1323, in _try_get_data
+    raise RuntimeError(
+RuntimeError: DataLoader worker (pid(s) 2144270, 2144322, 2144365, 2144429) exited unexpectedly

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+starVLA==1.0.1
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+  "python": "CPython 3.11.15",
+  "startedAt": "2026-03-23T09:40:14.719023Z",
+  "args": [
+    "--config_yaml",
+    "./examples/LIBERO/train_files/starvla_cotrain_libero.yaml",
+    "--framework.name",
+    "QwenGR00T",
+    "--framework.qwenvl.base_vlm",
+    "playground/Pretrained_models/Qwen3-VL-2B-Instruct",
+    "--datasets.vla_data.data_root_dir",
+    "playground/Datasets/LEROBOT_LIBERO_DATA",
+    "--datasets.vla_data.data_mix",
+    "libero_all",
+    "--datasets.vla_data.per_device_batch_size",
+    "64",
+    "--datasets.vla_data.num_workers",
+    "8",
+    "--trainer.vla_data.video_backend",
+    "torchvision_av",
+    "--trainer.freeze_modules",
+    "--trainer.max_train_steps",
+    "80000",
+    "--trainer.save_interval",
+    "10000",
+    "--trainer.logging_frequency",
+    "100",
+    "--trainer.eval_interval",
+    "100",
+    "--run_root_dir",
+    "./results/ckpt",
+    "--run_id",
+    "0323_libero_all_qwengr00t",
+    "--wandb_project",
+    "starvla",
+    "--wandb_entity",
+    "junha-lee"
+  ],
+  "program": "/workspace/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "git@github.com:junha-l/contravla.git",
+    "commit": "b8005a008a9df9a798ca090ce258dc01300780da"
+  },
+  "email": "junha.lee@postech.ac.kr",
+  "root": "./results/ckpt/0323_libero_all_qwengr00t/wandb",
+  "host": "korea-2024-03-2-svr",
+  "executable": "/opt/venv/bin/python3",
+  "cpu_count": 32,
+  "cpu_count_logical": 32,
+  "gpu": "NVIDIA H100 NVL",
+  "gpu_count": 1,
+  "disk": {
+    "/": {
+      "total": "4226383028224",
+      "used": "2386167427072"
+    }
+  },
+  "memory": {
+    "total": "211072577536"
+  },
+  "gpu_nvidia": [
+    {
+      "name": "NVIDIA H100 NVL",
+      "memoryTotal": "100485038080",
+      "cudaCores": 16896,
+      "architecture": "Hopper",
+      "uuid": "GPU-bfab68c1-f118-19f2-a1fa-aba345fd0966"
+    }
+  ],
+  "cudaVersion": "13.0",
+  "writerId": "17iafail3qbmy4pdi3csu4ayo1v0d5ff"
+}

wandb/wandb/run-20260323_094014-p8q7c8fg/files/wandb-summary.json ADDED Viewed

	@@ -0,0 +1 @@


1	+ {"_wandb":{"runtime":13},"_runtime":13}