tensorflow_probability/examples/disentangled_vae.py
def sample_static_prior(self, samples, batch_size, fixed=False):
    """Sample the static latent prior.

    Args:
      samples: Number of samples to draw from the latent distribution.
      batch_size: Number of sequences to sample.
      fixed: Boolean for whether or not to share the same random
        sample across all sequences.

    Returns:
      A tuple of a sample tensor of shape [samples, batch_size,
      latent_size], and a MultivariateNormalDiag distribution from which
      the tensor was sampled, with event shape [latent_size], and batch
      shape [].
    """
    dist = self.static_prior()
    if fixed:  # in either case, shape is (samples, batch, latent)
      sample = dist.sample((samples, 1)) + tf.zeros([batch_size, 1])
    else:
      sample = dist.sample((samples, batch_size))
    return sample, dist
def sample_static_prior(self, samples, batch_size, fixed=False):
    dist = self.static_prior()
    if fixed:  # in either case, shape is (samples, batch, latent)
      sample = dist.sample((samples, 1)) + tf.zeros([batch_size, 1])
    else:
      sample = dist.sample((samples, batch_size))
    return sample, dist
def sample_static_prior ( self , samples , batch_size , fixed = False ) : dist = self . static_prior ( ) if fixed : # in either case, shape is (samples, batch, latent) sample = dist . sample ( ( samples , 1 ) ) + tf . zeros ( [ batch_size , 1 ] ) else : sample = dist . sample ( ( samples , batch_size ) ) return sample , dist
Sample the static latent prior.

    Args:
      samples: Number of samples to draw from the latent distribution.
      batch_size: Number of sequences to sample.
      fixed: Boolean for whether or not to share the same random
        sample across all sequences.

    Returns:
      A tuple of a sample tensor of shape [samples, batch_size,
      latent_size], and a MultivariateNormalDiag distribution from which
      the tensor was sampled, with event shape [latent_size], and batch
      shape [].
Sample the static latent prior .