code: def _softmax_cross_entropy_with_logits(logits, target):
      soft_target = np.zeros(len(logits))
      soft_target[target] = 1
      return -np.sum(_log_softmax(logits) * soft_target)
  
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 3 for calling a global function with example usage: _softmax_cross_entropy_with_logits(logits, target) and returns: unknown