class_docstr: Stores hyperparameters for initialization, batch norm and training.
class_docstr_tok: ["Stores","hyperparameters","for","initialization",",","batch","norm","and","training","."]
code: def use_softmax_loss(self):
      if not self.separate_instruments and (
          self.num_instruments > 1 or self.num_instruments == 0
      ):
          return False
      else:
          return True
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  import os
  from magenta.models.coconet import lib_util
  import numpy
  import six
  import tensorflow.compat.v1
  import yaml
label_desc: Use image node_id 11 for calling the Hyperparameters obj's underlying member method code with example usage: obj.use_softmax_loss() and returns: False, True