code: def test_batched_placeholders_from_feature_spec(self):
      feature_spec = {
          "fixed_len_float": tf.io.FixedLenFeature([2, 3], tf.float32),
          "fixed_len_string": tf.io.FixedLenFeature([], tf.string),
          "_var_len_underscored": tf.io.VarLenFeature(tf.string),
          "var_len_int": tf.io.VarLenFeature(tf.int64),
          "sparse_1d": tf.io.SparseFeature(
              "1d_idx", "1d_value", tf.int64, 7
          ),
          "sparse_2d": tf.io.SparseFeature(
              ["2d_idx0", "2d_idx1"], "2d_value", tf.int64, [2, 17]
          ),
      }
      with tf.compat.v1.Graph().as_default():
          features = impl_helper.batched_placeholders_from_specs(
              feature_spec
          )
      self.assertCountEqual(
          features.keys(),
          [
              "fixed_len_float",
              "fixed_len_string",
              "var_len_int",
              "_var_len_underscored",
              "sparse_1d",
              "sparse_2d",
          ],
      )
      self.assertIsInstance(features["fixed_len_float"], tf.Tensor)
      self.assertEqual(
          features["fixed_len_float"].get_shape().as_list(),
          [None, 2, 3],
      )
      self.assertIsInstance(features["fixed_len_string"], tf.Tensor)
      self.assertEqual(
          features["fixed_len_string"].get_shape().as_list(), [None]
      )
      self.assertEqual(type(features["var_len_int"]), tf.SparseTensor)
      self.assertEqual(
          features["var_len_int"].get_shape().as_list(), [None, None]
      )
      self.assertEqual(
          type(features["_var_len_underscored"]), tf.SparseTensor
      )
      self.assertEqual(
          features["_var_len_underscored"].get_shape().as_list(),
          [None, None],
      )
      self.assertEqual(type(features["sparse_1d"]), tf.SparseTensor)
      self.assertEqual(type(features["sparse_2d"]), tf.SparseTensor)
      if version.parse(tf.__version__) >= version.parse("2"):
          self.assertEqual(
              features["sparse_1d"].get_shape().as_list(), [None, 7]
          )
          self.assertEqual(
              features["sparse_2d"].get_shape().as_list(), [None, 2, 17]
          )
      else:
          self.assertEqual(
              features["sparse_1d"].get_shape().as_list(), [None, None]
          )
          self.assertEqual(
              features["sparse_2d"].get_shape().as_list(),
              [None, None, None],
          )
  
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 1 for calling the ImplHelperTest obj's underlying member method code with example usage: obj.test_batched_placeholders_from_feature_spec() without return types