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import tensorflow as tf
import hyperchamber as hc
import os
import hypergan
from hypergan.discriminators.common import *
from hypergan.discriminators.pyramid_discriminator import PyramidDiscriminator
from hypergan.generators.resize_conv_generator import ResizeConvGenerator
from .base_discriminator import BaseDiscriminator
class AutoencoderDiscriminator(BaseDiscriminator):
def build(self, net):
config = self.config
gan = self.gan
ops = self.ops
generator = config.decoder(gan, gan.config.generator)
generator.ops = ops # share variable allocation to make variables part of the discriminator training step
encoder = config.encoder(gan, config)
encoder.ops = ops
ops.describe(ops.description+"autoencoder-d")
hidden = encoder.build(net)
ops.describe(ops.description+"autoencoder-g")
reconstruction = generator.build(hidden)
print("[autoencoder discriminator] hidden layer ", hidden)
error = config.distance(net, reconstruction)
self.reconstruction = reconstruction
return error
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