batch size = 4
image size = 128
loss = MSELoss
I am trying to generate 6 numeric values from an image of size 128x128 using the below CNN model.
I am getting a warning
Using a target size (torch.Size([4, 6])) that is different to the input size (torch.Size([1, 6])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.
I read many discussions here but sorry I am not getting it. please help me.
class MultiLabelNN(nn.Module):
def __init__(self):
super(MultiLabelNN, self).__init__()
self.conv1 = nn.Conv2d(3,64, 5)
self.pool = nn.MaxPool2d(2,2)
self.relu = nn.ReLU()
self.sigmoid = nn.Sigmoid()
self.conv2 = nn.Conv2d(64, 128, 5)
self.conv3 = nn.Conv2d(128, 256, 5)
self.conv4 = nn.Conv2d(256,320,5)
self.fc1 = nn.Linear(20480,2048)
self.fc2 = nn.Linear(2048, 1024)
self.fc3 = nn.Linear(1024, 512)
self.fc4 = nn.Linear(512, 256)
self.fc5 = nn.Linear(256, 6)
def forward(self, x):
x = self.conv1(x)
x = self.relu(x)
x = self.pool(x)
x = self.conv2(x)
x = self.relu(x)
x = self.pool(x)
x = self.conv3(x)
x = self.relu(x)
x = self.pool(x)
x = self.conv4(x)
x = self.relu(x)
x = self.pool(x)
x = x.view(-1, 20480)
x = self.fc1(x)
x = self.relu(x)
x = self.fc2(x)
x = self.relu(x)
x = self.fc3(x)
x = self.relu(x)
x = self.fc4(x)
x = self.relu(x)
x = self.fc5(x)
x = self.sigmoid(x)
return x
