Hi all,

I have the following model:

class ModelExample(torch.nn.Module):

```
def __init__(self):
super(ModelExample, self).__init__()
self.linear = torch.nn.Linear(100, 1024*4*4)
self.conv1 = nn.Sequential(
nn.ConvTranspose2d(in_channels=1024, out_channels=128, kernel_size=4, stride=2, padding=1, bias=False)
,nn.BatchNorm2d(128)
,nn.ReLU(inplace=True)
)
self.conv2 = nn.Sequential(
nn.ConvTranspose2d(in_channels=128, out_channels=3, kernel_size=4, stride=2, padding=1, bias=False)
)
self.out = torch.nn.Tanh()
def forward(self, x):
x = self.linear(x)
x = x.view(x.shape[0], 1024, 4, 4)
x = self.conv1(x)
x = self.conv2(x)
x = self.out(x)
return x
```

I tried to make the following code work:

model = ModelExample()

summary(model, input_size = (100,64,64), device = ‘cpu’)

But it gives me the following error

RuntimeError: size mismatch, m1: [12800 x 64], m2: [100 x 16384] at …\aten\src\TH/generic/THTensorMath.cpp:41

Can someone please tell me where the error is and how to solve it?

Thanks for your help.