convolutional neural network pytorch code example

Example 1: how to save a neural network pytorch

Saving:
	torch.save(model, PATH)


Loading: 
	model = torch.load(PATH)
	model.eval()

Example 2: torch cnn

train_loader = DataLoader(train_data, batch_size=10,shuffle=True)
test_loader = DataLoader(test_data, batch_size=10, shuffle=False)
class ConvolutionalNetwork(nn.Module):
    def __init__(self):
        super().__init__()
        self.conv1 = nn.Conv2d(1,6,3,1)
        self.conv2 = nn.Conv2d(6,16, 3, 1)
        self.fc1 = nn.Linear(5*5*16, 100)
        self.fc2 = nn.Linear(100, 10)

    def forward(self, X):
        X = F.relu(self.conv1(X))
        X = F.max_pool2d(X, 2, 2)
        X = F.relu(self.conv2(X))
        X = F.max_pool2d(X, 2, 2)
        X = X.view(-1, 5*5*16)
        X = F.relu(self.fc1(X))
        X = self.fc2(X)
        return F.log_softmax(X,dim=1)
    
torch.manual_seed(101)
model = ConvolutionalNetwork()