train_ddp_process_4.log

[2025-09-16 17:58:18,473][dinov2][INFO] - using MLP layer as FFN
[2025-09-16 18:02:50,329][dinov2][INFO] - using MLP layer as FFN
[2025-09-16 18:03:27,530][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(

[2025-09-16 18:03:27,531][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)

[2025-09-16 18:08:41,389][dinov2][INFO] - using MLP layer as FFN
[2025-09-16 18:09:17,146][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(

[2025-09-16 18:09:17,147][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)

[2025-09-16 18:14:32,867][dinov2][INFO] - using MLP layer as FFN
[2025-09-16 18:15:09,006][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(

[2025-09-16 18:15:09,007][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)

[2025-09-16 18:16:48,201][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4631: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
  warnings.warn(  # warn only once

[2025-09-16 18:17:01,226][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/utils/cpp_extension.py:2356: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. 
If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].
  warnings.warn(

[2025-09-16 18:17:04,135][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/autograd/graph.py:824: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
grad.sizes() = [56, 128, 1, 1], strides() = [128, 1, 128, 128]
bucket_view.sizes() = [56, 128, 1, 1], strides() = [128, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:328.)
  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass

[2025-09-16 18:23:12,055][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:198: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)

[2025-09-16 19:44:23,799][dinov2][INFO] - using MLP layer as FFN
[2025-09-16 19:44:56,745][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(

[2025-09-16 19:44:56,746][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)

[2025-09-16 19:45:55,947][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4631: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
  warnings.warn(  # warn only once

[2025-09-16 19:46:14,882][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/utils/cpp_extension.py:2356: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. 
If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].
  warnings.warn(

[2025-09-16 19:46:18,197][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/autograd/graph.py:824: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
grad.sizes() = [56, 128, 1, 1], strides() = [128, 1, 128, 128]
bucket_view.sizes() = [56, 128, 1, 1], strides() = [128, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:328.)
  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass

[2025-09-16 19:52:10,048][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:198: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)

[2025-09-17 08:16:14,950][dinov2][INFO] - using MLP layer as FFN
[2025-09-17 08:16:47,187][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(

[2025-09-17 08:16:47,188][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)

[2025-09-17 08:17:32,794][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py:4631: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user. 
  warnings.warn(  # warn only once

[2025-09-17 08:17:44,542][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/utils/cpp_extension.py:2356: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. 
If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].
  warnings.warn(

[2025-09-17 08:17:47,739][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/autograd/graph.py:824: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed.  This is not an error, but may impair performance.
grad.sizes() = [56, 128, 1, 1], strides() = [128, 1, 128, 128]
bucket_view.sizes() = [56, 128, 1, 1], strides() = [128, 1, 1, 1] (Triggered internally at /pytorch/torch/csrc/distributed/c10d/reducer.cpp:328.)
  return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass

[2025-09-17 08:23:38,710][py.warnings][WARNING] - /opt/conda/envs/ours/lib/python3.12/site-packages/torch/optim/lr_scheduler.py:198: UserWarning: The epoch parameter in `scheduler.step()` was not necessary and is being deprecated where possible. Please use `scheduler.step()` to step the scheduler. During the deprecation, if epoch is different from None, the closed form is used instead of the new chainable form, where available. Please open an issue if you are unable to replicate your use case: https://github.com/pytorch/pytorch/issues/new/choose.
  warnings.warn(EPOCH_DEPRECATION_WARNING, UserWarning)