parameters: (self, variant_tensor, resource_creator)
docstring: Record that `variant_tensor` is associated with `resource_creator`.
  
      Args:
        variant_tensor: The variant-dtype Tensor associated with the Dataset. This
          Tensor will be a captured input to functions which use the Dataset, and
          is used by saving code to identify the corresponding _VariantTracker.
        resource_creator: A zero-argument function which creates a new
          variant-dtype Tensor. This function will be included in SavedModels and
          run to re-create the Dataset's variant Tensor on restore.
docstring_summary: Record that `variant_tensor` is associated with `resource_creator`.
docstring_tokens: Record that variant_tensor is associated with resource_creator .
function: def __init__(self, variant_tensor, resource_creator):
      """Record that `variant_tensor` is associated with `resource_creator`.
  
      Args:
        variant_tensor: The variant-dtype Tensor associated with the Dataset. This
          Tensor will be a captured input to functions which use the Dataset, and
          is used by saving code to identify the corresponding _VariantTracker.
        resource_creator: A zero-argument function which creates a new
          variant-dtype Tensor. This function will be included in SavedModels and
          run to re-create the Dataset's variant Tensor on restore.
      """
      super(_VariantTracker, self).__init__(device="CPU")
      self._resource_handle = variant_tensor
      if not isinstance(resource_creator, def_function.Function):
        # Internal validation -- _VariantTracker assumes that resource creator is
        # already a tf.function.
        raise TypeError("Resource creator should already be a tf.function.")
      self._create_resource = resource_creator
function_tokens: def __init__ ( self , variant_tensor , resource_creator ) : super ( _VariantTracker , self ) . __init__ ( device = "CPU" ) self . _resource_handle = variant_tensor if not isinstance ( resource_creator , def_function . Function ) : # Internal validation -- _VariantTracker assumes that resource creator is # already a tf.function. raise TypeError ( "Resource creator should already be a tf.function." ) self . _create_resource = resource_creator