class_docstr: Class for RNN event sequence generation models.
  
  Currently this class only supports generation, of both event sequences and
  note sequences (via event sequences). Support for model training will be added
  at a later time.
class_docstr_tok: ["Class","for","RNN","event","sequence","generation","models",".","Currently","this","class","only","supports","generation",",","of","both","event","sequences","and","note","sequences","(","via","event","sequences",")",".","Support","for","model","training","will","be","added","at","a","later","time","."]
docstr: Initialize the EventSequenceRnnModel.
  
  Args:
    config: An EventSequenceRnnConfig containing the encoder/decoder and
      HParams to use.
docstr_tok: ["Initialize","the","EventSequenceRnnModel",".","Args",":","config",":","An","EventSequenceRnnConfig","containing","the","encoder\/decoder","and","HParams","to","use","."]
code: def __init__(self, config):
      """Initialize the EventSequenceRnnModel.
  
      Args:
        config: An EventSequenceRnnConfig containing the encoder/decoder and
          HParams to use.
      """
      super(EventSequenceRnnModel, self).__init__()
      self._config = config
  
imports: import collections
  import copy
  import functools
  from magenta.common import beam_search
  from magenta.common import state_util
  from magenta.contrib import training
  from magenta.models.shared import events_rnn_graph
  from magenta.models.shared import model
  import note_seq
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new EventSequenceRnnModel object from inherited base classes: model with example: obj = EventSequenceRnnModel(config)