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Deep Learning By Example by Ahmed Menshawy

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Model training

Finally, let's go ahead and kick off the training process after putting it all together:

class GAN:        def __init__(self, real_size, z_size, learning_rate, num_classes=10, alpha=0.2, beta1=0.5):            tf.reset_default_graph()            self.learning_rate = tf.Variable(learning_rate, trainable=False)            model_inputs = inputs(real_size, z_size)            self.input_actual, self.input_latent_z, self.target, self.label_mask = model_inputs            self.drop_out_rate = tf.placeholder_with_default(.5, (), "drop_out_rate")            losses_results = model_losses(self.input_actual, self.input_latent_z,                                          real_size[2], self.target, num_classes,                                          label_mask=self.label_mask,                                          leaky_alpha=0.2,                                          drop_out_rate=self.drop_out_rate)            self.disc_loss, self.gen_loss, self.correct, self.masked_correct ...

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