parameters: (self, init_args, init_func, next_func, finalize_func)
docstring: Constructs a `_GeneratorDataset`.
  
      Args:
        init_args: A nested structure representing the arguments to `init_func`.
        init_func: A TensorFlow function that will be called on `init_args` each
          time a C++ iterator over this dataset is constructed. Returns a nested
          structure representing the "state" of the dataset.
        next_func: A TensorFlow function that will be called on the result of
          `init_func` to produce each element, and that raises `OutOfRangeError`
          to terminate iteration.
        finalize_func: A TensorFlow function that will be called on the result of
          `init_func` immediately before a C++ iterator over this dataset is
          destroyed. The return value is ignored.
docstring_summary: Constructs a `_GeneratorDataset`.
docstring_tokens: Constructs a _GeneratorDataset .
function: def __init__(self, init_args, init_func, next_func, finalize_func):
      """Constructs a `_GeneratorDataset`.
  
      Args:
        init_args: A nested structure representing the arguments to `init_func`.
        init_func: A TensorFlow function that will be called on `init_args` each
          time a C++ iterator over this dataset is constructed. Returns a nested
          structure representing the "state" of the dataset.
        next_func: A TensorFlow function that will be called on the result of
          `init_func` to produce each element, and that raises `OutOfRangeError`
          to terminate iteration.
        finalize_func: A TensorFlow function that will be called on the result of
          `init_func` immediately before a C++ iterator over this dataset is
          destroyed. The return value is ignored.
      """
      self._init_args = init_args
  
      self._init_structure = structure.type_spec_from_value(init_args)
  
      self._init_func = StructuredFunctionWrapper(
          init_func,
          self._transformation_name(),
          input_structure=self._init_structure)
  
      self._next_func = StructuredFunctionWrapper(
          next_func,
          self._transformation_name(),
          input_structure=self._init_func.output_structure)
  
      self._finalize_func = StructuredFunctionWrapper(
          finalize_func,
          self._transformation_name(),
          input_structure=self._init_func.output_structure)
      variant_tensor = gen_dataset_ops.generator_dataset(
          structure.to_tensor_list(self._init_structure, self._init_args) +
          self._init_func.function.captured_inputs,
          self._next_func.function.captured_inputs,
          self._finalize_func.function.captured_inputs,
          init_func=self._init_func.function,
          next_func=self._next_func.function,
          finalize_func=self._finalize_func.function,
          **self._flat_structure)
      super(_GeneratorDataset, self).__init__(variant_tensor)
function_tokens: def __init__ ( self , init_args , init_func , next_func , finalize_func ) : self . _init_args = init_args self . _init_structure = structure . type_spec_from_value ( init_args ) self . _init_func = StructuredFunctionWrapper ( init_func , self . _transformation_name ( ) , input_structure = self . _init_structure ) self . _next_func = StructuredFunctionWrapper ( next_func , self . _transformation_name ( ) , input_structure = self . _init_func . output_structure ) self . _finalize_func = StructuredFunctionWrapper ( finalize_func , self . _transformation_name ( ) , input_structure = self . _init_func . output_structure ) variant_tensor = gen_dataset_ops . generator_dataset ( structure . to_tensor_list ( self . _init_structure , self . _init_args ) + self . _init_func . function . captured_inputs , self . _next_func . function . captured_inputs , self . _finalize_func . function . captured_inputs , init_func = self . _init_func . function , next_func = self . _next_func . function , finalize_func = self . _finalize_func . function , * * self . _flat_structure ) super ( _GeneratorDataset , self ) . __init__ ( variant_tensor )