code: def test_cpu_high_dimensional_invalid_lookup_ragged(self):
      # Prod of output shape is not a factor of the data batch size.
      # An error will be raised in this case.
      feature_config = (
          tpu_embedding_v2_utils.FeatureConfig(
              table=self.table_user, name="friends", output_shape=[3]
          ),
      )
      optimizer = tpu_embedding_v2_utils.SGD(learning_rate=0.1)
      mid_level = tpu_embedding_for_serving.TPUEmbeddingForServing(
          feature_config=feature_config, optimizer=optimizer
      )
      features = self._get_ragged_tensors()[2:3]
      with self.assertRaisesRegex(
          ValueError,
          "Output shape set in the FeatureConfig should be the factor",
      ):
          mid_level(features, weights=None)
  
imports: import numpy
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import init_ops_v2
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow.python.tpu import tpu_embedding_for_serving
  from tensorflow.python.tpu import tpu_embedding_v2_utils
  from tensorflow.python.util import nest
label_desc: Use image node_id 19 for calling the TPUEmbeddingForServingTest obj's underlying member method code with example usage: obj.test_cpu_high_dimensional_invalid_lookup_ragged() without return types