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Generative Adversarial Networks

1. GANs

Architecture (Tensorflow)

Play with shallow gan the min-max game

tensorboard --logdir=summary_directory/

localhost:6006

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2. DCGANs

Architecture (PyTorch)

Discriminator (
(sigmoid): Sigmoid ()
(batch_norm_2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True)
(leaky_relu): LeakyReLU (0.2)
(reduce): Linear (512 -> 1)
(d_layer_1): Conv2d(3, 128, kernel_size=(5, 5), stride=(2, 2))
(d_layer_2): Conv2d(128, 256, kernel_size=(5, 5), stride=(2, 2))
(d_layer_3): Conv2d(256, 512, kernel_size=(5, 5), stride=(2, 2))
)
Generator (
(project): Linear (100 -> 4608)
(batch_norm_2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True)
(relu): ReLU ()
(tanh): Tanh ()
(g_layer_1): ConvTranspose2d(512, 256, kernel_size=(3, 3), stride=(2, 2))
(g_layer_2): ConvTranspose2d(256, 128, kernel_size=(3, 3), stride=(2, 2))
(g_layer_3): ConvTranspose2d(128, 3, kernel_size=(4, 4), stride=(2, 2))
)

epoch 1

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epoch 2

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epoch 3

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epoch 4

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epoch 5

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epoch 6

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epoch 7

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epoch 8

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epoch 9

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epoch 10

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epoch 11

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epoch 12

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epoch 13

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epoch 14

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epoch 15

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3. Conditional GANs

4. InfoGANs

5. Wasserstein GANs