parameters: (self, dataset_fn, input_workers, input_contexts, strategy)
docstring: Makes an iterable from datasets created by the given function.
  
      Args:
        dataset_fn: A function that returns a `Dataset` given an `InputContext`.
        input_workers: an `InputWorkers` object.
        input_contexts: A list of `InputContext` instances to be passed to call(s)
          to `dataset_fn`. Length and order should match worker order in
          `worker_device_pairs`.
        strategy: a `tf.distribute.Strategy` object, used to run all-reduce to
          handle last partial batch.
docstring_summary: Makes an iterable from datasets created by the given function.
docstring_tokens: Makes an iterable from datasets created by the given function .
function: def __init__(self, dataset_fn, input_workers, input_contexts, strategy):
      """Makes an iterable from datasets created by the given function.
  
      Args:
        dataset_fn: A function that returns a `Dataset` given an `InputContext`.
        input_workers: an `InputWorkers` object.
        input_contexts: A list of `InputContext` instances to be passed to call(s)
          to `dataset_fn`. Length and order should match worker order in
          `worker_device_pairs`.
        strategy: a `tf.distribute.Strategy` object, used to run all-reduce to
          handle last partial batch.
      """
      super(DistributedDatasetsFromFunction, self).__init__(
          input_workers=input_workers)
  
      if input_workers.num_workers != len(input_contexts):
        raise ValueError(
            "Number of input workers (%d) is not same as number of "
            "input_contexts (%d)" %
            (input_workers.num_workers, len(input_contexts)))
  
      self._dataset_fn = dataset_fn
      self._input_workers = input_workers
      self._input_contexts = input_contexts
      self._strategy = strategy
function_tokens: def __init__ ( self , dataset_fn , input_workers , input_contexts , strategy ) : super ( DistributedDatasetsFromFunction , self ) . __init__ ( input_workers = input_workers ) if input_workers . num_workers != len ( input_contexts ) : raise ValueError ( "Number of input workers (%d) is not same as number of " "input_contexts (%d)" % ( input_workers . num_workers , len ( input_contexts ) ) ) self . _dataset_fn = dataset_fn self . _input_workers = input_workers self . _input_contexts = input_contexts self . _strategy = strategy