Since you are wrapping all submodules into an nn.Sequential module, you are losing the flatten operation which is performed in the forward method.
Similar to this issue 2 you can add a custom Flatten module and it should work:
class Flatten(nn.Module):
    def __init__(self):
        super(Flatten, self).__init__()
        
    def forward(self, x):
        x = x.view(x.size(0), -1)
        return x

class ALEXNET(nn.Module):
    def __init__(self):
        super(ALEXNET, self).__init__()
        self.model = models.alexnet(pretrained=False)   
        self.model = nn.Sequential(*(list(self.model.features.children()) + [nn.AvgPool2d(1), Flatten()] + list(self.model.classifier.children())))
                        
    def forward(self, images):
        scores = self.model(images)
        return scores