class model(nn.Module):
    def __init__(self, num_classes=10):
        # ------------ConvNet Model
        # Definition-------------------------------------------
        super(model, self).__init__()

        self.layer1 = nn.Sequential(
            nn.Conv2d(in_channels=1, out_channels=16, kernel_size=3, stride=1,
                      padding=0),
            nn.ReLU(),
            nn.BatchNorm2d(num_features=16),
            nn.MaxPool2d(kernel_size=2, stride=1),
            Downsample(channels=16, filt_size=5, stride=2))

        self.layer2 = nn.Sequential(
            nn.Conv2d(in_channels=16, out_channels=32, kernel_size=4, stride=1,
                      padding=0),
            nn.ReLU(),
            nn.BatchNorm2d(num_features=32),
            nn.MaxPool2d(kernel_size=2, stride=1),
            Downsample(channels=32, filt_size=5, stride=2))

        self.fc1 = nn.Linear(2048, 100)
        self.fc2 = nn.Linear(100, num_classes)
        self.softmax = nn.Softmax(1)