class_docstr: Implements a recurrent DQN designed to produce melody sequences.
class_docstr_tok: ["Implements","a","recurrent","DQN","designed","to","produce","melody","sequences","."]
docstr: Starts the models internal composition over at beat 0, with no notes.
  
  Also resets statistics about whether the composition is in the middle of a
  melodic leap.
docstr_tok: ["Starts","the","models","internal","composition","over","at","beat","0",",","with","no","notes",".","Also","resets","statistics","about","whether","the","composition","is","in","the","middle","of","a","melodic","leap","."]
code: def reset_composition(self):
      """Starts the models internal composition over at beat 0, with no notes.
  
      Also resets statistics about whether the composition is in the middle of a
      melodic leap.
      """
      self.beat = 0
      self.composition = []
      self.composition_direction = 0
      self.leapt_from = None
      self.steps_since_last_leap = 0
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import random
  import urllib
  from magenta.models.rl_tuner import note_rnn_loader
  from magenta.models.rl_tuner import rl_tuner_eval_metrics
  from magenta.models.rl_tuner import rl_tuner_ops
  import matplotlib.pyplot
  from note_seq import melodies_lib
  from note_seq import midi_io
  import numpy
  import scipy.special
  from six.moves import range
  from six.moves import reload_module
  from six.moves import urllib
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the RLTuner obj's underlying member method code with example usage: obj.reset_composition() without return types