message: Update embedding test to run in 2.0 mode.
diff: @@ -23,15 +23,19 @@ import numpy as np
  from tensorflow.python import keras
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import test_util as tf_test_util
  +from tensorflow.python.keras import keras_parameterized
  from tensorflow.python.keras import testing_utils
  from tensorflow.python.platform import test
  from tensorflow.python.training import adagrad
  -class EmbeddingTest(test.TestCase):
  +class EmbeddingTest(keras_parameterized.TestCase):
  - @tf_test_util.run_in_graph_and_eager_modes(use_gpu=False)
  + @keras_parameterized.run_all_keras_modes
  def test_embedding(self):
  + if tf_test_util.is_gpu_available():
  + self.skipTest('Only test embedding on CPU.')
  +
  testing_utils.layer_test(
  keras.layers.Embedding,
  kwargs={'output_dim': 4,
  @@ -69,18 +73,17 @@ class EmbeddingTest(test.TestCase):
  input_dtype='int32',
  expected_output_dtype='float32')
  - @tf_test_util.run_in_graph_and_eager_modes()
  + @keras_parameterized.run_all_keras_modes
  def test_embedding_correctness(self):
  layer = keras.layers.Embedding(output_dim=2, input_dim=2)
  - layer.build((None, 2))
  - matrix = np.array([[1, 1], [2, 2]])
  - layer.set_weights([matrix])
  + model = keras.models.Sequential([layer])
  - inputs = keras.backend.constant([[0, 1, 0]], dtype='int32')
  - outputs = keras.backend.eval(layer(inputs))
  + layer.set_weights([np.array([[1, 1], [2, 2]])])
  + model.run_eagerly = testing_utils.should_run_eagerly()
  + outputs = model.predict(np.array([[0, 1, 0]], dtype='int32'))
  self.assertAllClose(outputs, [[[1, 1], [2, 2], [1, 1]]])
  - @tf_test_util.run_in_graph_and_eager_modes()
  + @tf_test_util.run_in_graph_and_eager_modes
  def test_eager_gpu_cpu(self):
  l = keras.layers.Embedding(output_dim=2, input_dim=2)
  l.build((None, 2))
  