code: def test_create(self, is_training):
      self.assertEqual(
          len(
              tf.compat.v1.get_collection(
                  tf.compat.v1.GraphKeys.UPDATE_OPS
              )
          ),
          0,
      )
      images = tf.compat.v1.placeholder(
          tf.float32,
          (
              4,
              dv_constants.PILEUP_DEFAULT_HEIGHT,
              dv_constants.PILEUP_DEFAULT_WIDTH,
              dv_constants.PILEUP_NUM_CHANNELS,
          ),
      )
      seq_type = tf.compat.v1.placeholder(tf.int64, (4,))
      endpoints = self.model._create(
          (images, seq_type),
          dv_constants.NUM_CLASSES,
          is_training=is_training,
      )
      if is_training:
          self.assertNotEqual(
              len(
                  tf.compat.v1.get_collection(
                      tf.compat.v1.GraphKeys.UPDATE_OPS
                  )
              ),
              0,
          )
      else:
          self.assertEqual(
              len(
                  tf.compat.v1.get_collection(
                      tf.compat.v1.GraphKeys.UPDATE_OPS
                  )
              ),
              0,
          )
      self.assertIn("Predictions", endpoints)
      self.assertIn("Logits", endpoints)
      self.assertEqual(
          endpoints["Predictions"].shape, (4, dv_constants.NUM_CLASSES)
      )
      self.assertIn("Embeddings", endpoints)
      self.assertEqual(
          endpoints["Embeddings"].shape,
          (4, 2048 + self.model.embedding_size),
      )
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tf_slim
  from deepvariant import dv_constants
  from deepvariant import dv_utils_using_clif
  from deepvariant import modeling
label_desc: Use image node_id 2 for calling the InceptionV3EmbeddingModelTest obj's underlying member method code with example usage: obj.test_create(is_training) without return types