OSError: [Errno 32] Broken pipe about codef HOT 4 CLOSED

Hello! when I ran ./scripts/test_multi.sh using the provided data, the following error occurred. How can I solve this problem? Thanks~

You are using a CUDA device ('NVIDIA GeForce RTX 4080') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:4: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
  if not hasattr(tensorboard, "__version__") or LooseVersion(
/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:6: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
  ) < LooseVersion("1.15"):
Testing DataLoader 0:   1%|▏                   | 1/99 [00:00<00:11,  8.50it/s]/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/skvideo/io/ffmpeg.py:466: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.
  self._proc.stdin.write(vid.tostring())
Traceback (most recent call last):
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/skvideo/io/ffmpeg.py", line 466, in writeFrame
    self._proc.stdin.write(vid.tostring())
BrokenPipeError: [Errno 32] Broken pipe

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 557, in <module>
    main(hparams)
  File "train.py", line 550, in main
    trainer.test(system, dataloaders=system.test_dataloader())
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 706, in test
    return call._call_and_handle_interrupt(
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 42, in _call_and_handle_interrupt
    return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 92, in launch
    return function(*args, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 749, in _test_impl
    results = self._run(model, ckpt_path=ckpt_path)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 935, in _run
    results = self._run_stage()
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 971, in _run_stage
    return self._evaluation_loop.run()
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/loops/utilities.py", line 177, in _decorator
    return loop_run(self, *args, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 115, in run
    self._evaluation_step(batch, batch_idx, dataloader_idx)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 375, in _evaluation_step
    output = call._call_strategy_hook(trainer, hook_name, *step_kwargs.values())
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 288, in _call_strategy_hook
    output = fn(*args, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/strategies/ddp.py", line 348, in test_step
    return self.model.test_step(*args, **kwargs)
  File "train.py", line 489, in test_step
    self.video_visualizer.add(img)
  File "/home/ft/Project/CoDeF/utils/video_visualizer.py", line 95, in add
    self.video.writeFrame(frame)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/skvideo/io/ffmpeg.py", line 471, in writeFrame
    raise IOError(msg)
OSError: [Errno 32] Broken pipe

FFMPEG COMMAND:
/home/ft/.conda/envs/VIST/bin/ffmpeg -y -f rawvideo -pix_fmt rgb24 -s 540x960 -i - -r 30.00 -s 540x960 -vcodec libx264 -crf 1 -pix_fmt yuv420p /home/ft/Project/CoDeF/results/all_sequences/scene_0/base/scene_0_base.mp4

FFMPEG STDERR OUTPUT:

Testing DataLoader 0:   1%|          | 1/99 [00:00<00:47,  2.07it/s] 

Try conda update ffmpeg?

from codef.

Please check whether FFMPEG is not correctly installed. Or you can disable the video output and the code will output video frames without converting it to videos.

from codef.

Please check whether FFMPEG is not correctly installed. Or you can disable the video output and the code will output video frames without converting it to videos.

I have tried, but I haven't solved the problem.

from codef.

Hello! when I ran ./scripts/test_multi.sh using the provided data, the following error occurred. How can I solve this problem? Thanks~

You are using a CUDA device ('NVIDIA GeForce RTX 4080') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:4: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
  if not hasattr(tensorboard, "__version__") or LooseVersion(
/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/torch/utils/tensorboard/__init__.py:6: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
  ) < LooseVersion("1.15"):
Testing DataLoader 0:   1%|▏                   | 1/99 [00:00<00:11,  8.50it/s]/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/skvideo/io/ffmpeg.py:466: DeprecationWarning: tostring() is deprecated. Use tobytes() instead.
  self._proc.stdin.write(vid.tostring())
Traceback (most recent call last):
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/skvideo/io/ffmpeg.py", line 466, in writeFrame
    self._proc.stdin.write(vid.tostring())
BrokenPipeError: [Errno 32] Broken pipe

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 557, in <module>
    main(hparams)
  File "train.py", line 550, in main
    trainer.test(system, dataloaders=system.test_dataloader())
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 706, in test
    return call._call_and_handle_interrupt(
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 42, in _call_and_handle_interrupt
    return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 92, in launch
    return function(*args, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 749, in _test_impl
    results = self._run(model, ckpt_path=ckpt_path)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 935, in _run
    results = self._run_stage()
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 971, in _run_stage
    return self._evaluation_loop.run()
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/loops/utilities.py", line 177, in _decorator
    return loop_run(self, *args, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 115, in run
    self._evaluation_step(batch, batch_idx, dataloader_idx)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 375, in _evaluation_step
    output = call._call_strategy_hook(trainer, hook_name, *step_kwargs.values())
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/trainer/call.py", line 288, in _call_strategy_hook
    output = fn(*args, **kwargs)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/pytorch_lightning/strategies/ddp.py", line 348, in test_step
    return self.model.test_step(*args, **kwargs)
  File "train.py", line 489, in test_step
    self.video_visualizer.add(img)
  File "/home/ft/Project/CoDeF/utils/video_visualizer.py", line 95, in add
    self.video.writeFrame(frame)
  File "/home/ft/.conda/envs/VIST/lib/python3.8/site-packages/skvideo/io/ffmpeg.py", line 471, in writeFrame
    raise IOError(msg)
OSError: [Errno 32] Broken pipe

FFMPEG COMMAND:
/home/ft/.conda/envs/VIST/bin/ffmpeg -y -f rawvideo -pix_fmt rgb24 -s 540x960 -i - -r 30.00 -s 540x960 -vcodec libx264 -crf 1 -pix_fmt yuv420p /home/ft/Project/CoDeF/results/all_sequences/scene_0/base/scene_0_base.mp4

FFMPEG STDERR OUTPUT:

Testing DataLoader 0:   1%|          | 1/99 [00:00<00:47,  2.07it/s] 

Try conda update ffmpeg?

It seems to solved the problem. thanks~

from codef.