code: def test_input_types(self, x_dtype):
      # Tests different input dtypes.
      x = tf.constant([1.0, 0.1, 0.01, 0.001, 0.0001], dtype=x_dtype)
      threshold = 0.05
      stage = misc.SplitBySmallValueEncodingStage(threshold=threshold)
      encode_params, decode_params = stage.get_params()
      encoded_x, decoded_x = self.encode_decode_x(
          stage, x, encode_params, decode_params
      )
      test_data = test_utils.TestData(x, encoded_x, decoded_x)
      test_data = self.evaluate_test_data(test_data)
  
      self._assert_is_integer(
          test_data.encoded_x[
              misc.SplitBySmallValueEncodingStage.ENCODED_INDICES_KEY
          ]
      )
  
      # The numpy arrays must have the same dtype as the arrays from test_data.
      expected_encoded_values = np.array(
          [1.0, 0.1], dtype=x.dtype.as_numpy_dtype
      )
      expected_encoded_indices = np.array([0, 1], dtype=np.int32)
      expected_decoded_x = np.array(
          [1.0, 0.1, 0.0, 0.0, 0.0], dtype=x_dtype.as_numpy_dtype
      )
      self.assertAllEqual(
          test_data.encoded_x[stage.ENCODED_VALUES_KEY],
          expected_encoded_values,
      )
      self.assertAllEqual(
          test_data.encoded_x[stage.ENCODED_INDICES_KEY],
          expected_encoded_indices,
      )
      self.assertAllEqual(test_data.decoded_x, expected_decoded_x)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.stages.research import misc
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.testing import test_utils
label_desc: Use image node_id 6 for calling the SplitBySmallValueEncodingStageTest obj's underlying member method code with example usage: obj.test_input_types(x_dtype) without return types