code: def test_no_data_needed(self):
      span_0_key = analyzer_cache.DatasetKey("span-0")
      span_1_key = analyzer_cache.DatasetKey("span-1")
  
      def preprocessing_fn(inputs):
          return {k: tf.identity(v) for k, v in inputs.items()}
  
      input_metadata = (
          dataset_metadata.DatasetMetadata.from_feature_spec(
              {
                  "x": tf.io.FixedLenFeature([], tf.float32),
              }
          )
      )
      input_data_dict = {
          span_0_key: None,
          span_1_key: None,
      }
  
      with self._TestPipeline() as p:
          cache_dict = {
              span_0_key: {},
              span_1_key: {},
          }
  
          _, output_cache = (
              input_data_dict,
              cache_dict,
              input_metadata,
          ) | "Analyze" >> tft_beam.AnalyzeDatasetWithCache(
              preprocessing_fn, pipeline=p
          )
          self.assertFalse(output_cache)
  
imports: import functools
  import os
  import struct
  from typing import Callable, Mapping, List
  import uuid
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import tensorflow
  import tensorflow_transform
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import common_types
  from tensorflow_transform import impl_helper
  from tensorflow_transform import nodes
  import tensorflow_transform.beam
  from tensorflow_transform.beam import analysis_graph_builder
  from tensorflow_transform.beam import analyzer_cache
  from tensorflow_transform.beam import tft_unit
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tfx_bsl.types import tfx_namedtuple
label_desc: Use image node_id 13 for calling the CachedImplTest obj's underlying member method code with example usage: obj.test_no_data_needed() and returns: unknown