class_docstr: Performs a softmax with optional masking on a tensor.
  
  Attributes:
    mask_expansion_axes: Any axes that should be padded on the mask tensor.
code: def get_config(self):
      config = {"mask_expansion_axes": self._mask_expansion_axes}
      base_config = super(MaskedSoftmax, self).get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
file_path: autodist/examples/benchmark/utils/modeling/layers/masked_softmax.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 3 for calling the MaskedSoftmax obj's underlying member method code with example usage: obj.get_config() and returns: dict