tensorflow_probability/examples/disentangled_vae.py
def image_summary(seqs, name, num=None):
  """Visualizes sequences as TensorBoard summaries.

  Args:
    seqs: A tensor of shape [n, t, h, w, c].
    name: String name of this summary.
    num: Integer for the number of examples to visualize. Defaults to
      all examples.
  """
  seqs = tf.clip_by_value(seqs, 0., 1.)
  seqs = tf.unstack(seqs[:num])
  joined_seqs = [tf.concat(tf.unstack(seq), 1) for seq in seqs]
  joined_seqs = tf.expand_dims(tf.concat(joined_seqs, 0), 0)
  tf.compat.v2.summary.image(
      name,
      joined_seqs,
      max_outputs=1,
      step=tf.compat.v1.train.get_or_create_global_step())
def image_summary(seqs, name, num=None):
  seqs = tf.clip_by_value(seqs, 0., 1.)
  seqs = tf.unstack(seqs[:num])
  joined_seqs = [tf.concat(tf.unstack(seq), 1) for seq in seqs]
  joined_seqs = tf.expand_dims(tf.concat(joined_seqs, 0), 0)
  tf.compat.v2.summary.image(
      name,
      joined_seqs,
      max_outputs=1,
      step=tf.compat.v1.train.get_or_create_global_step())
def image_summary ( seqs , name , num = None ) : seqs = tf . clip_by_value ( seqs , 0. , 1. ) seqs = tf . unstack ( seqs [ : num ] ) joined_seqs = [ tf . concat ( tf . unstack ( seq ) , 1 ) for seq in seqs ] joined_seqs = tf . expand_dims ( tf . concat ( joined_seqs , 0 ) , 0 ) tf . compat . v2 . summary . image ( name , joined_seqs , max_outputs = 1 , step = tf . compat . v1 . train . get_or_create_global_step ( ) )
Visualizes sequences as TensorBoard summaries.

  Args:
    seqs: A tensor of shape [n, t, h, w, c].
    name: String name of this summary.
    num: Integer for the number of examples to visualize. Defaults to
      all examples.
Visualizes sequences as TensorBoard summaries .