def check_static_result_4(self, place):
paddle.enable_static()
with program_guard(Program(), Program()):
input_shape = (2, 3, 4, 5, 6)
pad = [1, 2, 1, 1, 3, 4]
mode = "circular"
input_data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
result1 = F.pad(x=x, pad=pad, mode=mode, data_format="NCDHW")
result2 = F.pad(x=x, pad=pad, mode=mode, data_format="NDHWC")
exe = Executor(place)
fetches = exe.run(default_main_program(),
feed={"x": input_data},
fetch_list=[result1, result2])
np_out1 = self._get_numpy_out(input_data,
pad,
mode,
data_format="NCDHW")
np_out2 = self._get_numpy_out(input_data,
pad,
mode,
data_format="NDHWC")
self.assertTrue(np.allclose(fetches[0], np_out1))
self.assertTrue(np.allclose(fetches[1], np_out2))
def test_reflect_3():
input_shape = (1, 2, 3, 4, 5)
data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
y = F.pad(x, pad=[1, 1, 1, 1, 2, 3], value=1, mode='reflect')
place = paddle.CPUPlace()
exe = Executor(place)
outputs = exe.run(feed={'x': data}, fetch_list=[y.name])
def check_static_result_1(self, place):
paddle.enable_static()
with program_guard(Program(), Program()):
input_shape = (1, 2, 3, 4, 5)
pad = [1, 2, 1, 1, 3, 4]
mode = "constant"
value = 100
input_data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
result = F.pad(x=x,
pad=pad,
value=value,
mode=mode,
data_format="NCDHW")
exe = Executor(place)
fetches = exe.run(default_main_program(),
feed={"x": input_data},
fetch_list=[result])
np_out = self._get_numpy_out(input_data, pad, mode, value)
self.assertTrue(np.allclose(fetches[0], np_out))
def check_static_result(self, place):
paddle.enable_static()
with program_guard(Program(), Program()):
shape = [10, 15]
axis = 1
eps = 1e-8
np.random.seed(0)
np_x1 = np.random.rand(*shape).astype(np.float32)
np_x2 = np.random.rand(*shape).astype(np.float32)
x1 = paddle.fluid.data(name="x1", shape=shape)
x2 = paddle.fluid.data(name="x2", shape=shape)
result = F.cosine_similarity(x1, x2, axis=axis, eps=eps)
exe = Executor(place)
fetches = exe.run(default_main_program(),
feed={"x1": np_x1,
"x2": np_x2},
fetch_list=[result])
np_out = self._get_numpy_out(np_x1, np_x2, axis=axis, eps=eps)
self.assertTrue(np.allclose(fetches[0], np_out))
def test_static(self):
paddle.enable_static()
self.place = fluid.NPUPlace(
0) if fluid.core.is_compiled_with_npu() else fluid.CPUPlace()
with program_guard(Program(), Program()):
input_shape = (1, 2, 3, 4, 5)
pad = [1, 2, 1, 1, 3, 4]
mode = "constant"
value = 0
input_data = np.random.rand(*input_shape).astype(np.float32)
x = paddle.fluid.data(name="x", shape=input_shape)
result1 = F.pad(x=x,
pad=pad,
value=value,
mode=mode,
data_format="NCDHW")
result2 = F.pad(x=x,
pad=pad,
value=value,
mode=mode,
data_format="NDHWC")
exe = Executor(self.place)
fetches = exe.run(default_main_program(),
feed={"x": input_data},
fetch_list=[result1, result2])
np_out1 = self._get_numpy_out(input_data,
pad,
mode,
value,
data_format="NCDHW")
np_out2 = self._get_numpy_out(input_data,
pad,
mode,
value,
data_format="NDHWC")
self.assertTrue(np.allclose(fetches[0], np_out1))
self.assertTrue(np.allclose(fetches[1], np_out2))
