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Deep Learning Course - Level: Advanced
When speaking about the input to a GAN generator, we usually have stated that the input is a batch of noise vectors with values randomly sampled from a standard normal distribution. We can think of a batch in this way as having the shape (batch_size, 100)
.
As we saw when we implemented a DCGAN in PyTorch and in TensorFlow, however, the input wasn't actually a batch of 1
-dimensional noise vectors of length 100
. Instead, the input was a batch having shape (batch_size, 100, 1, 1)
for PyTorch, or (batch_size, 1, 1, 100)
for TensorFlow.
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