from torch._C import * # noqa: F403 ^^^^^^^^^^^^^^^^^^^^^^ ImportError: DLL load failed while importing _C: 找不到指定的模块。

`from torch._C import *` 这行代码通常在PyTorch库中用于导入底层的C语言实现部分。当你看到 `ImportError: DLL load failed while importing _C:` 的错误提示时，它意味着在尝试加载由 `_C` 模块提供的动态链接库（DLL）文件时遇到了问题。

原因可能是：

1. **缺失依赖**：你的环境可能缺少必要的动态链接库文件，比如libtorch.dll或类似的文件。这通常发生在从源码安装或者系统环境配置不完整的情况下。

2. **路径问题**：库文件可能不在系统的搜索路径中，或者路径设置不正确。

3. **版本冲突**：如果你的Python、PyTorch或其他相关的库版本不匹配，可能导致加载失败。

4. **权限问题**：某些系统可能需要管理员权限才能访问或加载特定的DLL。

解决这个问题的一般步骤包括：

1. 确保已正确安装并配置了PyTorch，包括所有依赖项。
2. 检查系统环境变量（如PATH），确保包含PyTorch的bin目录。
3. 如果是从源码安装，检查构建选项是否包含了正确的库。
4. 试着重启计算机，有时候操作系统需要重启来更新环境变量。
5. 查看错误日志，寻找更具体的错误信息。

相关问题

Traceback (most recent call last): File "D:\Anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3369, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-6-b8424bd64091>", line 2, in <cell line: 2> import torchvision File "D:\Pycharm\PyCharm Community Edition 2022.1.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) File "D:\Anaconda\lib\site-packages\torchvision\__init__.py", line 6, in <module> from torchvision import datasets, io, models, ops, transforms, utils File "D:\Pycharm\PyCharm Community Edition 2022.1.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) File "D:\Anaconda\lib\site-packages\torchvision\models\__init__.py", line 17, in <module> from . import detection, optical_flow, quantization, segmentation, video File "D:\Pycharm\PyCharm Community Edition 2022.1.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) File "D:\Anaconda\lib\site-packages\torchvision\models\quantization\__init__.py", line 3, in <module> from .mobilenet import * File "D:\Pycharm\PyCharm Community Edition 2022.1.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) File "D:\Anaconda\lib\site-packages\torchvision\models\quantization\mobilenet.py", line 1, in <module> from .mobilenetv2 import * # noqa: F401, F403 File "D:\Pycharm\PyCharm Community Edition 2022.1.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) File "D:\Anaconda\lib\site-packages\torchvision\models\quantization\mobilenetv2.py", line 5, in <module> from torch.ao.quantization import DeQuantStub, QuantStub File "D:\Pycharm\PyCharm Community Edition 2022.1.3\plugins\python-ce\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) ModuleNotFoundError: No module named 'torch.ao.quantization'

这个错误通常是因为 torchvision 的版本与你安装的 torch 版本不兼容导致的。请尝试通过升级 torchvision 来解决此问题。可以使用以下命令升级 torchvision：

pip install --upgrade torchvision

这将安装 torchvision 的最新版本，其中包含了与你安装的最新 torch 版本兼容的功能和修复。如果问题仍然存在，请确保你安装的 torch 和 torchvision 版本是兼容的，并且与你的 Python 版本相匹配。希望这能解决你的问题！如果还有其他问题，请随时提问。

D:\anaconda\envs\pytorch\python.exe C:\Users\23896\Desktop\bev-lane-det_dachaung-master\tools\train_openlane.py Traceback (most recent call last): File "C:\Users\23896\Desktop\bev-lane-det_dachaung-master\tools\train_openlane.py", line 18, in <module> from torch.utils.tensorboard import SummaryWriter File "D:\anaconda\envs\pytorch\lib\site-packages\torch\utils\tensorboard\__init__.py", line 13, in <module> from .writer import FileWriter, SummaryWriter # noqa: F401 File "D:\anaconda\envs\pytorch\lib\site-packages\torch\utils\tensorboard\writer.py", line 9, in <module> from tensorboard.compat.proto.event_pb2 import SessionLog File "D:\anaconda\envs\pytorch\lib\site-packages\tensorboard\compat\proto\event_pb2.py", line 17, in <module> from tensorboard.compat.proto import summary_pb2 as tensorboard_dot_compat_dot_proto_dot_summary__pb2 File "D:\anaconda\envs\pytorch\lib\site-packages\tensorboard\compat\proto\summary_pb2.py", line 17, in <module> from tensorboard.compat.proto import tensor_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__pb2 File "D:\anaconda\envs\pytorch\lib\site-packages\tensorboard\compat\proto\tensor_pb2.py", line 16, in <module> from tensorboard.compat.proto import resource_handle_pb2 as tensorboard_dot_compat_dot_proto_dot_resource__handle__pb2 File "D:\anaconda\envs\pytorch\lib\site-packages\tensorboard\compat\proto\resource_handle_pb2.py", line 16, in <module> from tensorboard.compat.proto import tensor_shape_pb2 as tensorboard_dot_compat_dot_proto_dot_tensor__shape__pb2 File "D:\anaconda\envs\pytorch\lib\site-packages\tensorboard\compat\proto\tensor_shape_pb2.py", line 36, in <module> _descriptor.FieldDescriptor( File "D:\anaconda\envs\pytorch\lib\site-packages\google\protobuf\descriptor.py", line 561, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

这个错误提示表明在导入 `torch.utils.tensorboard` 模块时出现了问题，具体是由于 `google.protobuf` 模块的版本不兼容导致的。错误信息还提到了一些可能的解决方法。

要解决这个问题，你可以尝试以下几个步骤：

1. 首先，尝试升级 `google.protobuf` 模块。可以使用以下命令来升级：

   pip install --upgrade protobuf

2. 如果升级 `google.protobuf` 后问题仍然存在，可以尝试降级 `protobuf` 包的版本。根据错误信息所述，可以尝试将 `protobuf` 降级到 3.20.x 或更低的版本：

   pip install protobuf==3.20.0

3. 如果上述步骤都没有解决问题，可以尝试设置环境变量 `PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION` 为 `python`，但这会导致纯Python解析，速度较慢：

   set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python

请注意，在尝试这些解决方法之前，请确保你的环境中已经安装了最新版本的 `pip` 和 `setuptools`。

如果问题仍然存在，请提供关于你的环境和依赖项的更多详细信息，以便我能够更好地帮助你解决问题。