he Code is here:
import torch
from torchvision.models import alexnet

if __name__ == "__main__":
    net = alexnet()
    x = torch.rand((1, 3, 224, 224))

    for name, layer in net.named_children():
        x = layer(x)
        print(name, ' output shape:\t', x.shape)

The output is here:
features  output shape:  torch.Size([1, 256, 6, 6])
avgpool  output shape:   torch.Size([1, 256, 6, 6])

File "AlexNet.py", line 9, in <module>
    x = layer(x)
RuntimeError: size mismatch, m1: [1536 x 6], m2: [9216 x 4096]

I want to test the input and output of the AlexNet, but i failed with the ‘size mismatch’ error. i use the image size(3,224,224) provided by the paper of AlexNet, and i wanna get the right output. After this error, i try to fix the
self.avgpool = nn.AdaptiveAvgPool2d((6, 6))

to
self.avgpool = nn.AdaptiveAvgPool2d((1, 9216))

and i get the right output.
I really want to know what did i do wrong with the torchvision. And i also want to know what people would do when they need to test the input and output of the cnn.
thx for your help!