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chenminhuaaymericdamien
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Update dcgan.py (aymericdamien#320)
correct some misunderstanding comments
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examples/3_NeuralNetworks/dcgan.py

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@@ -82,7 +82,7 @@ def discriminator(x, reuse=False):
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# Build Generator Network
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gen_sample = generator(noise_input)
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# Build 2 Discriminator Networks (one from noise input, one from generated samples)
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# Build 2 Discriminator Networks (one from real image input, one from generated samples)
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disc_real = discriminator(real_image_input)
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disc_fake = discriminator(gen_sample, reuse=True)
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disc_concat = tf.concat([disc_real, disc_fake], axis=0)
@@ -135,7 +135,7 @@ def discriminator(x, reuse=False):
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z = np.random.uniform(-1., 1., size=[batch_size, noise_dim])
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# Prepare Targets (Real image: 1, Fake image: 0)
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# The first half of data fed to the generator are real images,
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# The first half of data fed to the discriminator are real images,
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# the other half are fake images (coming from the generator).
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batch_disc_y = np.concatenate(
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[np.ones([batch_size]), np.zeros([batch_size])], axis=0)

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