code: def softmax(outputs):
      maxes = np.max(outputs, axis=-1, keepdims=True)
      shifted_exp = np.exp(outputs - maxes)
      return shifted_exp / shifted_exp.sum(axis=-1, keepdims=True)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/utils/test_module/custom_pipeline.py
imports: import numpy
  from transformers import Pipeline
label_desc: Use image node_id 1 for calling a global function with example usage: softmax(outputs) and returns: unknown