class_docstr: Model for predicting autofills given context.
class_docstr_tok: ["Model","for","predicting","autofills","given","context","."]
code: def __init__(
      self,
      is_training,
      hparams,
      placeholders=None,
      direct_inputs=None,
      use_placeholders=True,
  ):
      self.hparams = hparams
      self.batch_size = hparams.batch_size
      self.num_pitches = hparams.num_pitches
      self.num_instruments = hparams.num_instruments
      self.is_training = is_training
      self.placeholders = placeholders
      self._direct_inputs = direct_inputs
      self._use_placeholders = use_placeholders
      self.hiddens = []
      self.popstats_by_batchstat = collections.OrderedDict()
      self.build()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  from magenta.models.coconet import lib_hparams
  from magenta.models.coconet import lib_tfutil
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new CoconetGraph object from inherited base classes: object with example: obj = CoconetGraph(is_training, hparams, placeholders, direct_inputs, use_placeholders)