def __init__( self, episode_len, **kwargs ): self.episode_len = episode_len self.input_scale = 1 baseVAE.__init__(self, **kwargs)
def __init__(self, strategy=None, **kwargs): self.strategy = strategy autoencoder.__init__(self, **kwargs) self.ONES = tf.ones(shape=[self.batch_size, 1]) self.ZEROS = tf.zeros(shape=[self.batch_size, 1]) self.adversarial_models = { 'inference_discriminator_real': { 'variable': None, 'adversarial_item': 'generative', 'adversarial_value': self.ONES }, 'inference_discriminator_fake': { 'variable': None, 'adversarial_item': 'generative', 'adversarial_value': self.ZEROS }, 'inference_generator_fake': { 'variable': None, 'adversarial_item': 'generative', 'adversarial_value': self.ONES }, 'generative_discriminator_real': { 'variable': None, 'adversarial_item': 'inference_mean', 'adversarial_value': self.ONES }, 'generative_discriminator_fake': { 'variable': None, 'adversarial_item': 'inference_mean', 'adversarial_value': self.ZEROS }, 'generative_generator_fake': { 'variable': None, 'adversarial_item': 'inference_mean', 'adversarial_value': self.ONES } }