code: def test_analyze_in_place(self, force_tf_compat_v1):
      if not force_tf_compat_v1:
          test_case.skip_if_not_tf2("Tensorflow 2.x required")
  
      def preprocessing_fn(inputs):
          return {"x_add_1": inputs["x"] + 1}
  
      feature_spec = {"x": tf.io.FixedLenFeature([], tf.int64)}
      type_spec = {
          "x": tf.TensorSpec(
              dtype=tf.int64,
              shape=[
                  None,
              ],
          )
      }
      output_path = os.path.join(
          self.get_temp_dir(), self._testMethodName
      )
      impl_helper.analyze_in_place(
          preprocessing_fn,
          force_tf_compat_v1,
          feature_spec,
          type_spec,
          output_path,
      )
  
      tft_output = TFTransformOutput(output_path)
      expected_value = np.array([2], dtype=np.int64)
      if force_tf_compat_v1:
          with tf.Graph().as_default() as graph:
              with tf.compat.v1.Session(graph=graph).as_default():
                  transformed_features = (
                      tft_output.transform_raw_features(
                          {"x": tf.constant([1], dtype=tf.int64)}
                      )
                  )
                  transformed_value = transformed_features[
                      "x_add_1"
                  ].eval()
      else:
          transformed_features = tft_output.transform_raw_features(
              {"x": tf.constant([1], dtype=tf.int64)}
          )
          transformed_value = transformed_features["x_add_1"].numpy()
      self.assertEqual(transformed_value, expected_value)
  
      transformed_feature_spec = tft_output.transformed_feature_spec()
      expected_feature_spec = feature_spec = {
          "x_add_1": tf.io.FixedLenFeature([], tf.int64)
      }
      self.assertEqual(transformed_feature_spec, expected_feature_spec)
  
imports: import copy
  import os
  import numpy
  from packaging import version
  import pyarrow
  import tensorflow
  from tensorflow_transform import analyzers
  from tensorflow_transform import impl_helper
  from tensorflow_transform import schema_inference
  from tensorflow_transform import test_case
  from tensorflow_transform.output_wrapper import TFTransformOutput
  from tensorflow_transform.tf_metadata import schema_utils
label_desc: Use image node_id 9 for calling the ImplHelperTest obj's underlying member method code with example usage: obj.test_analyze_in_place(force_tf_compat_v1) and returns: dict