dev(narugo): update cnns

class MonochromeAlexNet(nn.Module):

    __model_name__ = 'alexnet'

    def __init__(self, input_channels: int = 3, num_classes=2, avgpool_size: int = 7):

    def __init__(self, input_channels: int = 3, num_classes=2, avgpool_size: int = 4):

        super(MonochromeAlexNet, self).__init__()

        self.features = nn.Sequential(

            nn.Conv1d(input_channels, 96, kernel_size=11, stride=4, padding=2),

class ResNet(nn.Module):

    def __init__(self, block, num_blocks, num_classes, avgpool_size: int = 8):

    def __init__(self, block, num_blocks, num_classes, avgpool_size: int = 23):

        super(ResNet, self).__init__()

        self.in_planes = 64

if __name__ == '__main__':

    net = ResNet50(2)

    y = net(torch.randn(10, 3, 400))

    y = net(torch.randn(10, 3, 180))

    print(y.shape)