Traceback (most recent call last): File "D:\Pycharm\PyCharm 2020.2.5\plugins\python\helpers\pydev\pydevd.py", line 1448, in _exec pydev_imports.execfile(file, globals, locals) # execute the script File "D:\Pycharm\PyCharm 2020.2.5\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 269, in <module> summary(net, (3, 224, 224)) File "D:\anaconda3\envs\pytorch\lib\site-packages\torchsummary\torchsummary.py", line 72, in summary model(*x) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 228, in forward out = self.MSB3d(out) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 135, in forward self.branch3x3dbl_3b(branch3x3dbl), File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/demo.py", line 42, in forward x = self.conv(x) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\conv.py", line 457, in forward return self._conv_forward(input, self.weight, self.bias) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\conv.py", line 453, in _conv_forward return F.conv2d(input, weight, bias, self.stride, RuntimeError: Given groups=1, weight of size [256, 256, 3, 1], expected input[2, 128, 14, 14] to have 256 channels, but got 128 channels instead

这个错误是由于卷积层的输入通道数不匹配引起的。根据错误信息，期望的输入通道数是256，但实际上却是128。

可能的原因是在定义网络架构时，某个卷积层的输出通道数与下一层的输入通道数不匹配。你可以检查一下代码中的网络定义部分，确保每个卷积层的输出通道数与下一层的输入通道数相等。

另外，你还可以检查一下数据输入部分，确保输入数据的通道数为3（根据代码中的提示，输入的形状应该是[2, 128, 14, 14]）。

如果你能提供网络架构和数据输入的代码，我可以更详细地帮助你解决这个问题。

相关问题

Traceback (most recent call last): File "<input>", line 1, in <module> File "E:\PyCharm 2020.2.4\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 197, in runfile pydev_imports.execfile(filename, global_vars, local_vars) # execute the script File "E:\PyCharm 2020.2.4\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "D:/PycharmProjects/pythonProject5/game/test_demo.py", line 4, in <module> from .demo01 import Add File "E:\PyCharm 2020.2.4\plugins\python\helpers\pydev\_pydev_bundle\pydev_import_hook.py", line 21, in do_import module = self._system_import(name, *args, **kwargs) ImportError: attempted relative import with no known parent package

这个错误是由于相对导入时没有找到父包的原因导致的。在Python中，相对导入需要明确指定父包，如果没有明确指定，Python会认为当前模块是顶级模块，因此会报错。

要解决这个问题，你可以尝试以下几种方法：

1. 使用绝对导入：将相对导入改为绝对导入，即使用完整的包路径来导入模块。例如，如果你想导入的模块位于兄弟包中，可以使用`from package_name.module_name import function_name`来导入。

2. 添加包路径：在代码中添加父包的路径，以确保Python可以找到父包。你可以使用sys.path.append()或者设置PYTHONPATH环境变量来添加包路径。

3. 修改项目结构：如果你的项目结构不合理，可以考虑重新组织代码结构，使得相对导入可以正常工作。

希望这些解决方法能帮到你！如果有任何疑问，请随时提问。

Traceback (most recent call last): File "D:\Pycharm\PyCharm 2020.2.5\plugins\python\helpers\pydev\pydevd.py", line 1448, in _exec pydev_imports.execfile(file, globals, locals) # execute the script File "D:\Pycharm\PyCharm 2020.2.5\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/model.py", line 177, in <module> summary(net, (3, 224, 224)) File "D:\anaconda3\envs\pytorch\lib\site-packages\torchsummary\torchsummary.py", line 72, in summary model(*x) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/model.py", line 134, in forward x = self.MSB3a(x) File "D:\anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1148, in _call_impl result = forward_call(*input, **kwargs) File "C:/Users/wz/Desktop/Framework to practice/多尺度Demo/model.py", line 63, in forward return torch.cat(outputs,1) TypeError: expected Tensor as element 3 in argument 0, but got Sequential

这个错误是由于在代码的最后一行，尝试将输出结果进行拼接时，其中包含一个`nn.Sequential`对象。而torch.cat()函数要求参数是Tensor类型，而不是`nn.Sequential`对象。

要解决这个问题，你需要修改代码的最后一行，将`branch4 = self.branch4`改为`branch4 = self.branch4(x)`。这样就可以将输入x通过最大池化层和1x1的卷积层操作得到一个Tensor类型的结果。

然后再进行拼接操作时，就不会出现类型错误了。这样你就可以获得四个分支的输出结果，并将它们拼接成一个Tensor类型的结果并返回了。