code: def test_cpu_sparse_lookup_with_non_sparse_weights(self):
      mid_level = self._create_mid_level()
      features = self._get_sparse_tensors()
      weights = self._get_dense_tensors(dtype=dtypes.float32)
      with self.assertRaisesRegex(
          ValueError, "but it does not match type of the input which is"
      ):
          mid_level(features, weights=weights)
  
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 9 for calling the TPUEmbeddingForServingTest obj's underlying member method code with example usage: obj.test_cpu_sparse_lookup_with_non_sparse_weights() without return types