错误似乎是在尝试使用skvideo库的ffmpeg模块写入视频帧时发生的。具体来说，您遇到了一个BrokenPipeError，这通常意味着子进程（在这种情况下是ffmpeg）在父进程尝试写入数据时已经终止或崩溃

[HuangLiyulu]

distributed_backend=nccl
All distributed processes registered. Starting with 1 processes

You are using a CUDA device ('NVIDIA GeForce RTX 3090') 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]
/root/miniconda3/envs/CoDeF/lib/python3.10/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(
/root/miniconda3/envs/CoDeF/lib/python3.10/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<00:16, 6.08it/s]/root/miniconda3/envs/CoDeF/lib/python3.10/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 "/root/miniconda3/envs/CoDeF/lib/python3.10/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 "/root/autodl-tmp/CoDeF/train.py", line 557, in
main(hparams)
File "/root/autodl-tmp/CoDeF/train.py", line 550, in main
trainer.test(system, dataloaders=system.test_dataloader())
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 706, in test
return call._call_and_handle_interrupt(
File "/root/miniconda3/envs/CoDeF/lib/python3.10/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 "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 92, in launch
return function(*args, **kwargs)
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 749, in _test_impl
results = self._run(model, ckpt_path=ckpt_path)
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 935, in _run
results = self._run_stage()
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 971, in _run_stage
return self._evaluation_loop.run()
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/loops/utilities.py", line 177, in _decorator
return loop_run(self, *args, **kwargs)
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/loops/evaluation_loop.py", line 115, in run
self._evaluation_step(batch, batch_idx, dataloader_idx)
File "/root/miniconda3/envs/CoDeF/lib/python3.10/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 "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 288, in _call_strategy_hook
output = fn(*args, **kwargs)
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/pytorch_lightning/strategies/ddp.py", line 348, in test_step
return self.model.test_step(*args, **kwargs)
File "/root/autodl-tmp/CoDeF/train.py", line 489, in test_step
self.video_visualizer.add(img)
File "/root/autodl-tmp/CoDeF/utils/video_visualizer.py", line 95, in add
self.video.writeFrame(frame)
File "/root/miniconda3/envs/CoDeF/lib/python3.10/site-packages/skvideo/io/ffmpeg.py", line 471, in writeFrame
raise IOError(msg)
OSError: [Errno 32] Broken pipe

FFMPEG COMMAND:
/usr/local/bin/ffmpeg -y -f rawvideo -pix_fmt rgb24 -s 540x960 -i - -r 30.00 -s 540x960 -vcodec libx264 -crf 1 -pix_fmt yuv420p /root/autodl-tmp/CoDeF/results/all_sequences/scene_0/base/scene_0_base.mp4

FFMPEG STDERR OUTPUT:

Testing DataLoader 0: 1%| | 1/99 [00:00<00:54, 1.80it/s]
(CoDeF) root@autodl-container-495811b6ae-4fe7c681:/autodl-tmp/CoDeF# ffmpeg
ffmpeg version 5.1.2 Copyright (c) 2000-2022 the FFmpeg developers
built with gcc 9 (Ubuntu 9.4.0-1ubuntu120.04.1)
configuration:
libavutil 57. 28.100 / 57. 28.100
libavcodec 59. 37.100 / 59. 37.100
libavformat 59. 27.100 / 59. 27.100
libavdevice 59. 7.100 / 59. 7.100
libavfilter 8. 44.100 / 8. 44.100
libswscale 6. 7.100 / 6. 7.100
libswresample 4. 7.100 / 4. 7.100
Hyper fast Audio and Video encoder
usage: ffmpeg [options] [[infile options] -i infile]... {[outfile options] outfile}...

Use -h to get full help or, even better, run 'man ffmpeg'

[HuangLiyulu]

自己在云端搭建的环境PyTorch 1.11.0
Python 3.8(ubuntu20.04)
Cuda 11.3 conda create -y -n CoDeF python=3.10 conda install -y pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.7 -c pytorch -c nvidia wget https://ffmpeg.org/releases/ffmpeg-5.1.2.tar.gz