code: def _log_softmax(logits):
      log_z = scipy.special.logsumexp(logits)
      return logits - log_z
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import mesh_tensorflow
  from mesh_tensorflow.transformer import adaptive_softmax
  import mock
  import numpy
  import scipy.special
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 2 for calling a global function with example usage: _log_softmax(logits) and returns: unknown