code: def test_features_multi_none_sequence(
      self,
      dtype,
      encoding: features_lib.Encoding,
      shape,
  ):
      x = np.random.randint(256, size=(3, 2, 3, 1), dtype=np.uint8)
      x_other_shape = np.random.randint(
          256, size=(3, 2, 2, 1), dtype=np.uint8
      )
  
      self.assertFeature(
          feature=features_lib.Sequence(
              features_lib.Tensor(
                  shape=shape,
                  dtype=dtype,
                  encoding=encoding,
              ),
          ),
          shape=(None,) + shape,
          dtype=dtype,
          tests=[
              testing.FeatureExpectationItem(
                  value=x,
                  expected=x,
                  expected_np=x,
              ),
              testing.FeatureExpectationItem(
                  value=x_other_shape,
                  expected=x_other_shape,
                  expected_np=x_other_shape,
              ),
              # TODO(epot): Is there a way to catch if the user try to encode
              # tensors with different shapes ?
          ],
      )
  
imports: from absl.testing import parameterized
  import jax.numpy
  import numpy
  import pytest
  import tensorflow
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import features
label_desc: Use image node_id 5 for calling the FeatureTensorTest obj's underlying member method code with example usage: obj.test_features_multi_none_sequence(dtype, encoding, shape) without return types