RuntimeError: mat1 and mat2 shapes cannot be multiplied (1024x1 and 1024x3)

RuntimeError: mat1 and mat2 shapes cannot be multiplied (1024x1 and 1024x3)

前言：在学习pytorch 搭建神经网络的时候，测试网络发现出现RuntimeError: mat1 and mat2 shapes cannot be multiplied (1024x1 and 1024x3)的错误，记录下。

一、报错如下

Traceback (most recent call last):
  File "mobilenet_v1.py", line 145, in <module>
    out = model(input)
  File "J:\WorkSoft\envs\yolov5_test\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "mobilenet_v1.py", line 138, in forward
    x = self.fc(x)
  File "J:\WorkSoft\envs\yolov5_test\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
    return forward_call(*input, **kwargs)
  File "J:\WorkSoft\envs\yolov5_test\lib\site-packages\torch\nn\modules\linear.py", line 96, in forward
    return F.linear(input, self.weight, self.bias)
  File "J:\WorkSoft\envs\yolov5_test\lib\site-packages\torch\nn\functional.py", line 1847, in linear
    return torch._C._nn.linear(input, weight, bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (1024x1 and 1024x3)

二、定位报错为全连接层

 File "mobilenet_v1.py", line 138, in forward
    x = self.fc(x)

三、原因分析

卷积层的输入为四维[batch_size,channels,H,W] ，而全连接接受维度为2的输入，通常为[batch_size, size]。

四、解决办法

在全连接层前面加入维度变换

//方法一：
x.view(-1,7* 7* 1024) 

//方法二：
x = torch.flatten(x,1) //拉成二维向量[batch_size, size]