class_docstr: Graph for Gibbs sampling from Coconet.
docstr: Returns outer masks, if all zeros created by completion masking.
docstr_tok: ["Returns","outer","masks",",","if","all","zeros","created","by","completion","masking","."]
code: def make_outer_masks(self, outer_masks, input_pianorolls):
      """Returns outer masks, if all zeros created by completion masking."""
      outer_masks = tf.to_float(outer_masks)
      # If outer_masks come in as all zeros, it means there's no masking,
      # which also means nothing will be generated. In this case, use
      # completion mask to make new outer masks.
      outer_masks = tf.cond(
          tf.reduce_all(tf.equal(outer_masks, 0)),
          lambda: make_completion_masks(input_pianorolls),
          lambda: outer_masks,
      )
      return outer_masks
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import time
  from magenta.models.coconet import lib_graph
  from magenta.models.coconet import lib_hparams
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling the CoconetSampleGraph obj's underlying member method code with example usage: obj.make_outer_masks(outer_masks, input_pianorolls) and returns: outer_masks