code: def softmax(model, blob_in, blob_out=None, use_cudnn=False, **kwargs):
      """Softmax."""
      if use_cudnn:
          kwargs["engine"] = "CUDNN"
      if blob_out is not None:
          return model.net.Softmax(blob_in, blob_out, **kwargs)
      else:
          return model.net.Softmax(blob_in, **kwargs)
  
file_path: pytorch/caffe2/python/helpers/normalization.py
imports: from caffe2.python import scope
  from caffe2.python.modeling.parameter_info import ParameterTags
  from caffe2.proto import caffe2_pb2
  from caffe2.python.modeling import initializers
label_desc: Use image node_id 2 for calling a global function with example usage: softmax(model, blob_in, blob_out, use_cudnn) and returns: model, model