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Exercise

Convolutional Generator

Define a convolutional generator following the DCGAN guidelines discussed in the last video.

torch.nn has been pre-imported as nn for your convenience. Additionally, a custom function dc_gen_block() is available, which eturns a block of a transposed convolution, batch norm, and ReLU activation. This function serves as a foundational component for constructing the convolutional generator. You can get familiar with dc_gen_block()'s definition below. 

def dc_gen_block(in_dim, out_dim, kernel_size, stride):
    return nn.Sequential(
        nn.ConvTranspose2d(in_dim, out_dim, kernel_size, stride=stride),
        nn.BatchNorm2d(out_dim),
        nn.ReLU()
    )

Instructions

100 XP
  • Add the last generator block, mapping the size of the feature maps to 256.
  • Add a transposed convolution with the output size of 3.
  • Add the tanh activation.