class_docstr: This layer operation converts the raw network outputs into final inference
  results.
code: def layer_op(self, inputs):
      if self.func == "SOFTMAX":
          output_tensor = tf.cast(tf.nn.softmax(inputs), tf.float32)
      elif self.func == "ARGMAX":
          output_tensor = tf.cast(tf.argmax(inputs, -1), tf.int32)
          output_tensor = tf.expand_dims(output_tensor, axis=-1)
      elif self.func == "IDENTITY":
          output_tensor = tf.cast(inputs, tf.float32)
      return output_tensor
  
file_path: NiftyNet/niftynet/layer/post_processing.py
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.layer.base_layer import Layer
  from niftynet.utilities.util_common import look_up_operations
label_desc: Use image node_id 3 for calling the PostProcessingLayer obj's underlying member method code with example usage: obj.layer_op(inputs) and returns: output_tensor