input_pipeline.py 文件源码

def make_input_pipeline_from_def(def_dict, mode, **kwargs):
  """Creates an InputPipeline object from a dictionary definition.

  Args:
    def_dict: A dictionary defining the input pipeline.
      It must have "class" and "params" that correspond to the class
      name and constructor parameters of an InputPipeline, respectively.
    mode: A value in tf.contrib.learn.ModeKeys

  Returns:
    A new InputPipeline object
  """
  if not "class" in def_dict:
    raise ValueError("Input Pipeline definition must have a class property.")

  class_ = def_dict["class"]
  if not hasattr(sys.modules[__name__], class_):
    raise ValueError("Invalid Input Pipeline class: {}".format(class_))

  pipeline_class = getattr(sys.modules[__name__], class_)

  # Constructor arguments
  params = {}
  if "params" in def_dict:
    params.update(def_dict["params"])
  params.update(kwargs)

  return pipeline_class(params=params, mode=mode)