def __init__(self, arch, is_training=False):
'''
Variational auto-encoder implemented in 2D convolutional neural nets
Input:
`arch`: network architecture (`dict`)
`is_training`: (unused now) it was kept for historical reasons (for `BatchNorm`)
'''
self.arch = arch
self._sanity_check()
self.is_training = is_training
with tf.name_scope('SpeakerRepr'):
self.y_emb = self._l2_regularized_embedding(
self.arch['y_dim'],
self.arch['z_dim'],
'y_embedding')
self._generate = tf.make_template(
'Generator',
self._generator)
self._encode = tf.make_template(
'Encoder',
self._encoder)
self.generate = self.decode # for VAE-GAN extension
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