def test_default_CPU(self):
paddle.enable_static()
with paddle.static.program_guard(paddle.static.Program(),
paddle.static.Program()):
data = paddle.tril_indices(4, None, 2)
exe = paddle.static.Executor(paddle.CPUPlace())
result = exe.run(feed={}, fetch_list=[data])
expected_result = np.tril_indices(4, 2)
self.assertTrue(np.allclose(result, expected_result))
with fluid.dygraph.base.guard(paddle.CPUPlace()):
out = paddle.tril_indices(4, None, 2)
expected_result = np.tril_indices(4, 2)
self.assertEqual((out.numpy() == expected_result).all(), True)
def test_dygraph(self):
places = [
paddle.CPUPlace(), paddle.fluid.CUDAPlace(0)
] if fluid.core.is_compiled_with_cuda() else [paddle.CPUPlace()]
for place in places:
with fluid.dygraph.base.guard(place=place):
out1 = paddle.tril_indices(4, 4, 2)
expected_result1 = np.tril_indices(4, 2, 4)
self.assertEqual((out1.numpy() == expected_result1).all(), True)
def test_static(self):
places = [
paddle.CPUPlace(), paddle.fluid.CUDAPlace(0)
] if fluid.core.is_compiled_with_cuda() else [paddle.CPUPlace()]
paddle.enable_static()
for place in places:
with paddle.static.program_guard(paddle.static.Program(),
paddle.static.Program()):
data1 = paddle.tril_indices(4, 4, -1)
exe1 = paddle.static.Executor(place)
result1 = exe1.run(feed={}, fetch_list=[data1])
expected_result1 = np.tril_indices(4, -1, 4)
self.assertTrue(np.allclose(result1, expected_result1))
def test_num_columns_type_check():
out2 = paddle.tril_indices(4, -1, 2)
def test_num_rows_type_check():
out1 = paddle.tril_indices(1.0, 1, 2)
def test_num_offset_type_check():
out3 = paddle.tril_indices(4, 4, 2.0)