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Fix cuDNN tests #8189

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Oct 20, 2017
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Fix cuDNN tests #8189

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49 changes: 24 additions & 25 deletions tests/keras/layers/cudnn_recurrent_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -122,46 +122,45 @@ def test_cudnn_rnn_canonical_to_params_gru():


@keras_test
@pytest.mark.parametrize('rnn_type', ['lstm', 'gru'], ids=['LSTM', 'GRU'])
@pytest.mark.skipif((keras.backend.backend() != 'tensorflow'),
reason='Requires TensorFlow backend')
@pytest.mark.skipif(not keras.backend.tensorflow_backend._get_available_gpus(),
reason='Requires GPU')
def test_cudnn_rnn_timing():
def test_cudnn_rnn_timing(rnn_type):
input_size = 1000
timesteps = 60
units = 256
num_samples = 10000

times = []
for rnn_type in ['lstm', 'gru']:
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)
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:
if rnn_type == 'lstm':
layer = keras.layers.LSTM(units)
else:
layer = keras.layers.GRU(units)
outputs = layer(inputs)
layer = keras.layers.CuDNNGRU(units)
else:
if rnn_type == 'lstm':
layer = keras.layers.LSTM(units)
else:
layer = keras.layers.GRU(units)
outputs = layer(inputs)

model = keras.models.Model(inputs, outputs)
model.compile('sgd', 'mse')
model = keras.models.Model(inputs, outputs)
model.compile('sgd', '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)
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)
times.append(time.time() - start_time)

speedup = times[1] / times[0]
print(rnn_type, 'speedup', speedup)
assert speedup > 3
keras.backend.clear_session()
speedup = times[1] / times[0]
print(rnn_type, 'speedup', speedup)
assert speedup > 3


@keras_test
Expand Down