class_docstr: Graph for Gibbs sampling from Coconet.
docstr: Initializes inputs for the Coconet sampling graph.
  
  Does not build or restore the graph. That happens lazily if you call run(),
  or explicitly using instantiate_sess_and_restore_checkpoint.
  
  Args:
    chkpt_path: Checkpoint directory for loading the model.
        Uses the latest checkpoint.
    placeholders: Optional placeholders.
docstr_tok: ["Initializes","inputs","for","the","Coconet","sampling","graph",".","Does","not","build","or","restore","the","graph",".","That","happens","lazily","if","you","call","run","(",")",",","or","explicitly","using","instantiate_sess_and_restore_checkpoint",".","Args",":","chkpt_path",":","Checkpoint","directory","for","loading","the","model",".","Uses","the","latest","checkpoint",".","placeholders",":","Optional","placeholders","."]
code: def __init__(self, chkpt_path, placeholders=None):
      """Initializes inputs for the Coconet sampling graph.
  
      Does not build or restore the graph. That happens lazily if you call run(),
      or explicitly using instantiate_sess_and_restore_checkpoint.
  
      Args:
        chkpt_path: Checkpoint directory for loading the model.
            Uses the latest checkpoint.
        placeholders: Optional placeholders.
      """
      self.chkpt_path = chkpt_path
      self.hparams = lib_hparams.load_hparams(chkpt_path)
      if placeholders is None:
          self.placeholders = self.get_placeholders()
      else:
          self.placeholders = placeholders
      self.samples = None
      self.sess = None
  
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 1 to create a new CoconetSampleGraph object from inherited base classes: object with example: obj = CoconetSampleGraph(chkpt_path, placeholders)