code: def _multi_class_head_with_softmax_cross_entropy_loss(
      n_classes,
      weight_column=None,
      label_vocabulary=None,
      loss_reduction=tf.compat.v1.losses.Reduction.SUM,
      loss_fn=None,
      name=None,
  ):
      """See `tensorflow_estimator/python/estimator/canned/head.py`."""
  
      if label_vocabulary is not None and not isinstance(
          label_vocabulary, (list, tuple)
      ):
          raise ValueError(
              "label_vocabulary should be a list or a tuple. Given type: {}".format(
                  type(label_vocabulary)
              )
          )
      if loss_reduction not in tf.compat.v1.losses.Reduction.all():
          raise ValueError(
              "Invalid loss_reduction: {}".format(loss_reduction)
          )
      if loss_fn:
          _validate_loss_fn_args(loss_fn)
      return _MultiClassHeadWithSoftmaxCrossEntropyLoss(
          n_classes=n_classes,
          weight_column=weight_column,
          label_vocabulary=label_vocabulary,
          loss_reduction=loss_reduction,
          loss_fn=loss_fn,
          name=name,
      )
  
file_path: privacy/tensorflow_privacy/privacy/estimators/v1/head.py
imports: import tensorflow
  from tensorflow.python.ops import lookup_ops
  from tensorflow_estimator.python.estimator import model_fn
  from tensorflow_estimator.python.estimator.canned import head
  from tensorflow_estimator.python.estimator.canned import metric_keys
  from tensorflow_estimator.python.estimator.canned import prediction_keys
  from tensorflow_estimator.python.estimator.export import export_output
  from tensorflow_estimator.python.estimator.mode_keys import ModeKeys
label_desc: Use image node_id 1 for calling a global function with example usage: _multi_class_head_with_softmax_cross_entropy_loss(n_classes, weight_column, label_vocabulary, loss_reduction, loss_fn, name) and returns: _MultiClassHeadWithSoftmaxCrossEntropyLoss