code: def test_embed_single_feature_2D_input(self, sigma_dimension):
      emb_dim = 5 + sigma_dimension
      config = test_util.default_de_config(emb_dim, [1] * emb_dim)
      (
          emb,
          vc,
          sigma,
          input_embed,
          var,
      ) = sparse_features.embed_single_feature(
          [["input1", ""], ["input2", "input3"]],
          config,
          5,
          sigma_dimension,
          "feature_name3_%d" % sigma_dimension,
          service_address=self._kbs_address,
      )
  
      if sigma_dimension > 0:
          self.assertIsNotNone(var)
          self.assertEqual((2, 5), emb.shape)
          self.assertEqual(5, vc.shape)
          self.assertEqual((2, 2), sigma.shape)
          self.assertEqual((2, 2, 5), input_embed.shape)
      else:
          self.assertAllClose([[1] * 5, [1] * 5], emb)
          self.assertIsNone(vc)
          self.assertIsNone(sigma)
          self.assertEqual((2, 2, 5), input_embed.shape)
  
imports: from absl.testing import parameterized
  from research.carls.models.caml import sparse_features
  from research.carls.testing import test_util
  import numpy
  import tensorflow
label_desc: Use image node_id 6 for calling the FeatureEmbeddingTest obj's underlying member method code with example usage: obj.test_embed_single_feature_2D_input(sigma_dimension) without return types