code: def _softmax(logits):
      """Applies softmax non-linearity on inputs."""
      return np.exp(logits) / np.sum(
          np.exp(np.array(logits)), axis=-1, keepdims=True
      )
  
file_path: maze/maze/test/train/impala/test_vtrace.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gym
  import numpy
  from maze.distributions.distribution_mapper import DistributionMapper
  from maze.perception.perception_utils import convert_to_torch
  from maze.train.trainers.impala import impala_vtrace
label_desc: Use image node_id 2 for calling a global function with example usage: _softmax(logits) and returns: unknown