def __init__(self, num_classes=200, num_channels=3):
        """
        :param num_classes: model output size
        :param num_channels: number of input channels
        """
        super(SimpleMLP_TinyImageNet, self).__init__()

        self.features = nn.Sequential(
            nn.Linear(num_channels * 64 * 64, 1024),
            nn.ReLU(inplace=True),
            nn.Dropout(),
        )
        self.classifier = nn.Linear(1024, num_classes)

        :param num_classes: model output size
        :param num_channels: number of input channels
        
avalanche/models/mlp_tiny_imagenet.py