Optimization, Pytorch, Machine Learning, Deep Learning, Tensorboard.
num_classes=num_classes): super().__init__() self.conv_in = nn.Conv2d(3, hidden_size, 3, padding='same') num_hidden = int(log2(img_size)) hidden = [] for i in range(num_hidden): hidden.append(nn.Conv2d(hidden_size, hidden_size, 3, padding='same')) hidden.append(nn.ReLU())