def test_fprop(self):
activation = "tanh"
seed = 1234
repeat = 1000
layer = LayerLSTM(input_size=DATA['features_size'],
hidden_size=DATA['hidden_size'],
activation=activation)
layer.initialize(initer.UniformInitializer(seed))
# input = T.tensor3('input')
input = T.matrix('input')
input.tag.test_value = DATA['batch_one_step']
last_h = sharedX(DATA['state_h'])
last_m = sharedX(DATA['state_m'])
fprop = theano.function([input], layer.fprop_faster(input, last_h, last_m))
fprop_time = measure("h, m = fprop(DATA['batch_one_step'])", repeat)
print("fprop time: {:.2f} sec.", fprop_time)
h, m = fprop(DATA['batch_one_step'])
def test_fprop(self):
activation = "tanh"
seed = 1234
repeat = 1000
layer = LayerLSTM(input_size=DATA['features_size'],
hidden_size=DATA['hidden_size'],
activation=activation)
layer.initialize(initer.UniformInitializer(seed))
# input = T.tensor3('input')
input = T.matrix('input')
input.tag.test_value = DATA['batch_one_step']
last_h = sharedX(DATA['state_h'])
last_m = sharedX(DATA['state_m'])
fprop = theano.function([input],
layer.fprop_faster(input, last_h, last_m))
fprop_time = measure("h, m = fprop(DATA['batch_one_step'])", repeat)
print("fprop time: {:.2f} sec.", fprop_time)
h, m = fprop(DATA['batch_one_step'])
