class_docstr: Tests for ops in byteps.keras.
code: def test_sparse_as_dense(self):
      with self.test_session(config=self.config) as sess:
          K.set_session(sess)
  
          opt = keras.optimizers.RMSprop(lr=0.0001)
          opt = bps.DistributedOptimizer(opt, sparse_as_dense=True)
  
          model = keras.models.Sequential()
          model.add(keras.layers.Embedding(1000, 64, input_length=10))
          model.compile(
              loss=keras.losses.mean_squared_error, optimizer=opt
          )
  
          x = np.random.randint(1000, size=(32, 10))
          y = np.random.random((32, 10, 64))
          # No assertions, we just need to verify that it doesn't hang
          model.train_on_batch(x, y)
  
file_path: byteps/tests/test_tensorflow_keras.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import numpy
  import warnings
  from distutils.version import LooseVersion
  from tensorflow import keras
  from tensorflow.python.keras import backend
  import byteps.tensorflow.keras
label_desc: Use image node_id 3 for calling the TfKerasTests obj's underlying member method code with example usage: obj.test_sparse_as_dense() without return types