class_docstr: A `Dataset` that groups its input and performs a windowed reduction.
docstr: Make wrapping defun for window_size_func.
docstr_tok: ["Make","wrapping","defun","for","window_size_func","."]
code: def _make_window_size_func(self, window_size_func):
      """Make wrapping defun for window_size_func."""
  
      def window_size_func_wrapper(key):
          return ops.convert_to_tensor(
              window_size_func(key), dtype=dtypes.int64
          )
  
      self._window_size_func = (
          structured_function.StructuredFunctionWrapper(
              window_size_func_wrapper,
              self._transformation_name(),
              input_structure=tensor_spec.TensorSpec([], dtypes.int64),
          )
      )
      if not self._window_size_func.output_structure.is_compatible_with(
          tensor_spec.TensorSpec([], dtypes.int64)
      ):
          raise ValueError(
              f"Invalid `window_size_func`. `window_size_func` must "
              f"return a single `tf.int64` scalar tensor but its "
              f"return type is "
              f"{self._window_size_func.output_structure}."
          )
  
file_path: tensorflow-upstream/tensorflow/python/data/ops/group_by_window_op.py
imports: from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import structured_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import gen_experimental_dataset_ops
label_desc: Use image node_id 2 for calling the _GroupByWindowDataset obj's underlying member method code with example usage: obj._make_window_size_func(window_size_func) and returns: ops