def test_api_with_dygraph(self):
with fluid.dygraph.guard():
data = np.random.random([1, 9, 9, 4]).astype('float32')
x = fluid.dygraph.to_variable(data)
tril_out, triu_out = tensor.tril(x).numpy(), tensor.triu(x).numpy()
self.assertTrue(np.allclose(tril_out, np.tril(data)))
self.assertTrue(np.allclose(triu_out, np.triu(data)))
def test_api_with_dygraph(self):
paddle.disable_static()
dtypes = ['float16', 'float32']
for dtype in dtypes:
with fluid.dygraph.guard():
data = np.random.random([1, 9, 9, 4]).astype(dtype)
x = fluid.dygraph.to_variable(data)
tril_out, triu_out = tensor.tril(x).numpy(), tensor.triu(
x).numpy()
self.assertTrue(np.allclose(tril_out, np.tril(data)))
self.assertTrue(np.allclose(triu_out, np.triu(data)))
def test_api(self):
data = np.random.random([1, 9, 9, 4]).astype('float32')
x = fluid.data(shape=[1, 9, -1, 4], dtype='float32', name='x')
tril_out, triu_out = tensor.tril(x), tensor.triu(x)
place = fluid.CUDAPlace(
0) if fluid.core.is_compiled_with_cuda() else fluid.CPUPlace()
exe = fluid.Executor(place)
tril_out, triu_out = exe.run(
fluid.default_main_program(),
feed={"x": data},
fetch_list=[tril_out, triu_out],
)
self.assertTrue(np.allclose(tril_out, np.tril(data)))
self.assertTrue(np.allclose(triu_out, np.triu(data)))
def test_api(self):
paddle.enable_static()
dtypes = ['float16', 'float32']
for dtype in dtypes:
prog = Program()
startup_prog = Program()
with program_guard(prog, startup_prog):
data = np.random.random([1, 9, 9, 4]).astype(dtype)
x = fluid.data(shape=[1, 9, -1, 4], dtype=dtype, name='x')
tril_out, triu_out = tensor.tril(x), tensor.triu(x)
place = fluid.NPUPlace(0)
exe = fluid.Executor(place)
tril_out, triu_out = exe.run(
fluid.default_main_program(),
feed={"x": data},
fetch_list=[tril_out, triu_out],
)
self.assertTrue(np.allclose(tril_out, np.tril(data)))
self.assertTrue(np.allclose(triu_out, np.triu(data)))