tensorflow_probability/examples/disentangled_vae.py
def summarize_mean_in_nats_and_bits(inputs, units, name,
                                    nats_name_scope="nats",
                                    bits_name_scope="bits_per_dim"):
  """Summarize the mean of a tensor in nats and bits per unit.

  Args:
    inputs: A tensor of values measured in nats.
    units: The units of the tensor with which to compute the mean bits
      per unit.
    name: The name of the tensor.
    nats_name_scope: The name scope of the nats summary.
    bits_name_scope: The name scope of the bits summary.
  """
  mean = tf.reduce_mean(input_tensor=inputs)
  with tf.compat.v1.name_scope(nats_name_scope):
    tf.compat.v2.summary.scalar(
        name,
        mean,
        step=tf.compat.v1.train.get_or_create_global_step())
  with tf.compat.v1.name_scope(bits_name_scope):
    tf.compat.v2.summary.scalar(
        name,
        mean / units / tf.math.log(2.),
        step=tf.compat.v1.train.get_or_create_global_step())
def summarize_mean_in_nats_and_bits(inputs, units, name,
                                    nats_name_scope="nats",
                                    bits_name_scope="bits_per_dim"):
  """Summarize the mean of a tensor in nats and bits per unit.

  Args:
    inputs: A tensor of values measured in nats.
    units: The units of the tensor with which to compute the mean bits
      per unit.
    name: The name of the tensor.
    nats_name_scope: The name scope of the nats summary.
    bits_name_scope: The name scope of the bits summary.
  """
  mean = tf.reduce_mean(input_tensor=inputs)
  with tf.compat.v1.name_scope(nats_name_scope):
    tf.compat.v2.summary.scalar(
        name,
        mean,
        step=tf.compat.v1.train.get_or_create_global_step())
  with tf.compat.v1.name_scope(bits_name_scope):
    tf.compat.v2.summary.scalar(
        name,
        mean / units / tf.math.log(2.),
        step=tf.compat.v1.train.get_or_create_global_step())
def summarize_mean_in_nats_and_bits ( inputs , units , name , nats_name_scope = "nats" , bits_name_scope = "bits_per_dim" ) : mean = tf . reduce_mean ( input_tensor = inputs ) with tf . compat . v1 . name_scope ( nats_name_scope ) : tf . compat . v2 . summary . scalar ( name , mean , step = tf . compat . v1 . train . get_or_create_global_step ( ) ) with tf . compat . v1 . name_scope ( bits_name_scope ) : tf . compat . v2 . summary . scalar ( name , mean / units / tf . math . log ( 2. ) , step = tf . compat . v1 . train . get_or_create_global_step ( ) )
Summarize the mean of a tensor in nats and bits per unit.

  Args:
    inputs: A tensor of values measured in nats.
    units: The units of the tensor with which to compute the mean bits
      per unit.
    name: The name of the tensor.
    nats_name_scope: The name scope of the nats summary.
    bits_name_scope: The name scope of the bits summary.
Summarize the mean of a tensor in nats and bits per unit .