tensorflow_probability/examples/disentangled_vae.py
def summarize_dist_params(dist, name, name_scope="dist_params"):
  """Summarize the parameters of a distribution.

  Args:
    dist: A Distribution object with mean and standard deviation
      parameters.
    name: The name of the distribution.
    name_scope: The name scope of this summary.
  """
  with tf.compat.v1.name_scope(name_scope):
    tf.compat.v2.summary.histogram(
        name="{}/{}".format(name, "mean"),
        data=dist.mean(),
        step=tf.compat.v1.train.get_or_create_global_step())
    tf.compat.v2.summary.histogram(
        name="{}/{}".format(name, "stddev"),
        data=dist.stddev(),
        step=tf.compat.v1.train.get_or_create_global_step())
def summarize_dist_params(dist, name, name_scope="dist_params"):
  with tf.compat.v1.name_scope(name_scope):
    tf.compat.v2.summary.histogram(
        name="{}/{}".format(name, "mean"),
        data=dist.mean(),
        step=tf.compat.v1.train.get_or_create_global_step())
    tf.compat.v2.summary.histogram(
        name="{}/{}".format(name, "stddev"),
        data=dist.stddev(),
        step=tf.compat.v1.train.get_or_create_global_step())
def summarize_dist_params ( dist , name , name_scope = "dist_params" ) : with tf . compat . v1 . name_scope ( name_scope ) : tf . compat . v2 . summary . histogram ( name = "{}/{}" . format ( name , "mean" ) , data = dist . mean ( ) , step = tf . compat . v1 . train . get_or_create_global_step ( ) ) tf . compat . v2 . summary . histogram ( name = "{}/{}" . format ( name , "stddev" ) , data = dist . stddev ( ) , step = tf . compat . v1 . train . get_or_create_global_step ( ) )
Summarize the parameters of a distribution.

  Args:
    dist: A Distribution object with mean and standard deviation
      parameters.
    name: The name of the distribution.
    name_scope: The name scope of this summary.
Summarize the parameters of a distribution .