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
}
}