Runtime error shape is invalid for input

1

i am trying to get the input and output information of a network. When debugging, i got this error, Runtime, shape ‘[-1, 400]’ is invalid for input of size 384. I tried different values, but can’t find the correct value. Is there a way to solve this issue? Thanks.


class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3, 6, 5)
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5)
        self.fc1 = nn.Linear(16*5*5, 120)
        self.fc2 = nn.Linear(120, 84)
        self.fc3 = nn.Linear(84, 10)

    def forward(self, x):
        x = self.pool(F.relu(self.conv1(x)))
        x = self.pool(F.relu(self.conv2(x)))
        x = x.view(-1, 16*5*5)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x

input_shape = (3, 21,21)
        dummy_input = torch.randn(6,*input_shape)

        graph = torch.jit._get_trace_graph(model,  args=dummy_input, _force_outplace=False, _return_inputs_states=False)

Error meaasge:

RuntimeError: shape '[-1, 400]' is invalid for input of size 384
2

Since your input shape is [batch_size, 3, 21, 21], the flattened activation before the linear layer will have the shape [batch_size, 16, 2, 2], so you should change the input features to 16*2*2 as well as the flattening operation (or use x = x.view(x.size(0), -1) instead).