File "/home/jim/archiconda3/envs/python38/lib/python3.8/site-packages/torch/__init__.py", line 213, in <module> raise ImportError(textwrap.dedent(''' ImportError: Failed to load PyTorch C extensions: It appears that PyTorch has loaded the `torch/_C` folder of the PyTorch repository rather than the C extensions which are expected in the `torch._C` namespace. This can occur when using the `install` workflow. e.g. $ python setup.py install && python -c "import torch" This error can generally be solved using the `develop` workflow $ python setup.py develop && python -c "import torch" # This should succeed or by running Python from a different directory.

这段错误信息意思是导入 PyTorch 时出错，可能是因为 PyTorch 加载了 PyTorch 代码存放的 `torch/_C` 文件夹，而没有加载预期放在 `torch._C` 命名空间下的 C 扩展。这种情况通常出现在使用 `install` 工作流程时，例如 `$ python setup.py install`。

相关问题

Traceback (most recent call last): File "/home/a/pycharmproject/clothes_try_on_copy/11/PF-AFN-main/PF-AFN_train/train_PBAFN_stage1.py", line 134, in <module> loss_vgg = criterionVGG(x_all[num], cur_person_clothes.cuda()) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/pycharmproject/clothes_try_on_copy/11/PF-AFN-main/PF-AFN_train/models/networks.py", line 164, in forward x_vgg, y_vgg = self.vgg(x), self.vgg(y) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/pycharmproject/clothes_try_on_copy/11/PF-AFN-main/PF-AFN_train/models/networks.py", line 150, in forward h_relu5 = self.slice5(h_relu4) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/container.py", line 119, in forward input = module(input) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/pooling.py", line 162, in forward return F.max_pool2d(input, self.kernel_size, self.stride, File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/_jit_internal.py", line 365, in fn return if_false(*args, **kwargs) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/functional.py", line 659, in _max_pool2d return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode) RuntimeError: Given input size: (512x2x1). Calculated output size: (512x1x0). Output size is too small 进程已结束,退出代码1

根据你提供的错误信息，这是一个运行时错误（RuntimeError）。错误信息中指出了问题出现的位置和错误类型。

根据错误信息可以看出，在执行 `forward` 方法时，发生了一个尺寸（size）计算错误。具体来说，输入的尺寸是 `(512x2x1)`，但计算得到的输出尺寸是 `(512x1x0)`。错误信息还指出输出尺寸过小（Output size is too small），导致计算无法进行。

这种错误通常与网络模型的结构和输入数据的尺寸不匹配有关。可能是在网络模型的某一层或操作中，尺寸计算出现了错误。可能的原因包括输入数据的维度不正确、网络模型定义中的错误或者数据预处理过程中的问题。

要解决这个问题，你可以检查以下几个方面：

1. 确保输入数据的维度和尺寸与模型定义相匹配。
2. 检查网络模型定义中各层或操作的输入输出尺寸是否正确。
3. 检查数据预处理过程中是否存在错误，例如可能需要进行维度变换或缩放操作。

如果你需要更详细的帮助，请提供相关的代码片段或更多上下文信息，我将尽力帮助你找到解决方案。

06/06/2023-16:31:47] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +0, now: CPU 0, GPU 0 (MiB) /home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/tensorrt/__init__.py:166: FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar. bool: np.bool, Traceback (most recent call last): File "/home/sniper/anaconda3/envs/labelme/bin/yolo", line 8, in <module> sys.exit(entrypoint()) File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/ultralytics/yolo/cfg/__init__.py", line 398, in entrypoint getattr(model, mode)(**overrides) # default args from model File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/ultralytics/yolo/engine/model.py", line 302, in val validator(model=self.model) File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/ultralytics/yolo/engine/validator.py", line 114, in __call__ model = AutoBackend(model, device=self.device, dnn=self.args.dnn, data=self.args.data, fp16=self.args.half) File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/ultralytics/nn/autobackend.py", line 174, in __init__ dtype = trt.nptype(model.get_binding_dtype(i)) File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/tensorrt/__init__.py", line 166, in nptype bool: np.bool, File "/home/sniper/anaconda3/envs/labelme/lib/python3.8/site-packages/numpy/__init__.py", line 305, in __getattr__ raise AttributeError(__former_attrs__[attr]) AttributeError: module 'numpy' has no attribute 'bool'. `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations 如何修复

这个错误是由于使用了在NumPy 1.20中被废弃的`np.bool`别名所引起的。可以将`np.bool`替换为`bool`来避免这个错误。可以在代码中查找`np.bool`并将其替换为`bool`。如果你确实需要使用NumPy的布尔类型，可以使用`np.bool_`。你可以查看NumPy 1.20的发布说明以获取更多详细信息和指导。