message: Remove CuDNNRNN timing test.
diff: @@ -18,8 +18,6 @@ from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  -import time
  -
  from absl.testing import parameterized
  import numpy as np
  @@ -32,43 +30,6 @@ from tensorflow.python.training.rmsprop import RMSPropOptimizer
  class CuDNNTest(test.TestCase, parameterized.TestCase):
  - @test_util.run_in_graph_and_eager_modes()
  - def test_cudnn_rnn_timing(self):
  - if test.is_gpu_available(cuda_only=True):
  - with self.test_session(use_gpu=True):
  - input_size = 10
  - timesteps = 6
  - units = 2
  - num_samples = 32
  -
  - for rnn_type in ['lstm', 'gru']:
  - times = []
  - for use_cudnn in [True, False]:
  - start_time = time.time()
  - inputs = keras.layers.Input(shape=(None, input_size))
  - if use_cudnn:
  - if rnn_type == 'lstm':
  - layer = keras.layers.CuDNNLSTM(units)
  - else:
  - layer = keras.layers.CuDNNGRU(units)
  - else:
  - if rnn_type == 'lstm':
  - layer = keras.layers.LSTM(units)
  - else:
  - layer = keras.layers.GRU(units)
  - outputs = layer(inputs)
  -
  - optimizer = RMSPropOptimizer(learning_rate=0.001)
  - model = keras.models.Model(inputs, outputs)
  - model.compile(optimizer, 'mse')
  -
  - x = np.random.random((num_samples, timesteps, input_size))
  - y = np.random.random((num_samples, units))
  - model.fit(x, y, epochs=4, batch_size=32)
  -
  - times.append(time.time() - start_time)
  - self.assertGreater(times[1], times[0])
  -
  @test_util.run_in_graph_and_eager_modes()
  def test_cudnn_rnn_basics(self):
  if test.is_gpu_available(cuda_only=True):
  