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Update dcgan_faces_tutorial.py
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beginner_source/dcgan_faces_tutorial.py

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# with the discriminator. Let :math:`x` be data representing an image.
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# :math:`D(x)` is the discriminator network which outputs the (scalar)
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# probability that :math:`x` came from training data rather than the
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# generator. Here, since we are dealing with images the input to
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# generator. Here, since we are dealing with images, the input to
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# :math:`D(x)` is an image of CHW size 3x64x64. Intuitively, :math:`D(x)`
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# should be HIGH when :math:`x` comes from training data and LOW when
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# :math:`x` comes from the generator. :math:`D(x)` can also be thought of

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