Im trying to train my hand image dataset into CNN by following the MNIST CNN code given on github, but im getting input size mismatch error, So can anyone help me with this.
my Images are 3 channel 200x200 images
and number of classes = 32
and my mini batch size in dataloader class is 10
class CNN(nn.Module):
    def __init__(self):
        super(CNN, self).__init__()
        self.layer1 = nn.Sequential(
            nn.Conv2d(3, 16, kernel_size=5, padding=2),
            nn.BatchNorm2d(16),
            nn.ReLU(),
            nn.MaxPool2d(2))
        self.layer2 = nn.Sequential(
            nn.Conv2d(16, 32, kernel_size=5, padding=2),
            nn.BatchNorm2d(32),
            nn.ReLU(),
            nn.MaxPool2d(2))
        self.fc = nn.Linear(7*7*32, 10)
        
    def forward(self, x):
        out = self.layer1(x)
        out = self.layer2(out)
        out = out.view(out.size(0), -1)
        out = self.fc(out)
        return out

Where should i change in this code to get this working, right now im getting this input mismatch error
RuntimeError: size mismatch, m1: [10 x 80000], m2: [1568 x 10] at /Users/soumith/minicondabuild3/conda-bld/pytorch_1518371252923/work/torch/lib/TH/generic/THTensorMath.c:1434