def _extract_log_probs(num_states, dist):
  """Tabulate log probabilities from a batch of distributions."""

  states = tf.reshape(tf.range(num_states),
                      tf.concat([[num_states],
                                 tf.ones_like(dist.batch_shape_tensor())],
                                axis=0))
  return distribution_util.move_dimension(dist.log_prob(states), 0, -1)
def _extract_log_probs(num_states, dist):
  

  states = tf.reshape(tf.range(num_states),
                      tf.concat([[num_states],
                                 tf.ones_like(dist.batch_shape_tensor())],
                                axis=0))
  return distribution_util.move_dimension(dist.log_prob(states), 0, -1)
def _extract_log_probs ( num_states , dist ) : states = tf . reshape ( tf . range ( num_states ) , tf . concat ( [ [ num_states ] , tf . ones_like ( dist . batch_shape_tensor ( ) ) ] , axis = 0 ) ) return distribution_util . move_dimension ( dist . log_prob ( states ) , 0 , - 1 )
Tabulate log probabilities from a batch of distributions.
Tabulate log probabilities from a batch of distributions .