def swith_rng_state(rng_state):
orig_cuda_rng_state = paddle.get_cuda_rng_state()
paddle.set_cuda_rng_state(rng_state)
try:
yield
finally:
paddle.set_cuda_rng_state(orig_cuda_rng_state)
def rng_state(self, name=MODEL_PARALLEL_RNG):
if name not in self.states_:
raise ValueError('state {} does not exist'.format(name))
orig_cuda_rng_state = paddle.get_cuda_rng_state()
paddle.set_cuda_rng_state(self.states_[name])
try:
yield
finally:
self.states_[name] = paddle.get_cuda_rng_state()
paddle.set_cuda_rng_state(orig_cuda_rng_state)
def add(self, name, seed):
if seed in self.seeds_:
raise ValueError('seed {} already exists'.format(seed))
self.seeds_.add(seed)
if name in self.states_:
raise ValueError('state {} already exists'.format(name))
orig_rng_state = paddle.get_cuda_rng_state()
paddle.seed(seed)
self.states_[name] = paddle.get_cuda_rng_state()
paddle.set_cuda_rng_state(orig_rng_state)
def _swith_rng_state_tracker(rng_state, tracker):
orig_cuda_rng_state = paddle.get_cuda_rng_state()
orig_cuda_rng_tracker = get_rng_state_tracker().get_states_tracker()
paddle.set_cuda_rng_state(rng_state)
get_rng_state_tracker().set_states_tracker(tracker)
try:
yield
finally:
paddle.set_cuda_rng_state(orig_cuda_rng_state)
get_rng_state_tracker().set_states_tracker(orig_cuda_rng_tracker)
def test_gen_dropout_dygraph(self):
gen = paddle.seed(12343)
fluid.enable_dygraph()
gen.manual_seed(111111111)
st = paddle.get_cuda_rng_state()
x = fluid.layers.uniform_random([2, 10],
dtype="float32",
min=0.0,
max=1.0)
x_again = fluid.layers.uniform_random([2, 10],
dtype="float32",
min=0.0,
max=1.0)
x_third = fluid.layers.uniform_random([2, 10],
dtype="float32",
min=0.0,
max=1.0)
print("x: {}".format(x.numpy()))
print("x_again: {}".format(x_again.numpy()))
x = x + x_again + x_third
y = fluid.layers.dropout(x, 0.5)
paddle.set_cuda_rng_state(st)
x1 = fluid.layers.uniform_random([2, 10],
dtype="float32",
min=0.0,
max=1.0)
x1_again = fluid.layers.uniform_random([2, 10],
dtype="float32",
min=0.0,
max=1.0)
x1_third = fluid.layers.uniform_random([2, 10],
dtype="float32",
min=0.0,
max=1.0)
x1 = x1 + x1_again + x1_third
y1 = fluid.layers.dropout(x1, 0.5)
y_np = y.numpy()
y1_np = y1.numpy()
if core.is_compiled_with_cuda():
print(">>>>>>> dropout dygraph >>>>>>>")
self.assertTrue(np.allclose(y_np, y1_np))
def test_generator_gaussian_random_dygraph(self):
"""Test Generator seed."""
fluid.enable_dygraph()
paddle.seed(12312321111)
x = fluid.layers.gaussian_random([120], dtype="float32")
st1 = paddle.get_cuda_rng_state()
x1 = fluid.layers.gaussian_random([120], dtype="float32")
paddle.set_cuda_rng_state(st1)
x2 = fluid.layers.gaussian_random([120], dtype="float32")
paddle.seed(12312321111)
x3 = fluid.layers.gaussian_random([120], dtype="float32")
x_np = x.numpy()
x1_np = x1.numpy()
x2_np = x2.numpy()
x3_np = x3.numpy()
if core.is_compiled_with_cuda():
print(">>>>>>> gaussian random dygraph >>>>>>>")
self.assertTrue(np.allclose(x1_np, x2_np))
self.assertTrue(np.allclose(x_np, x3_np))