def func_dygraph(self):
for place in self.places:
paddle.disable_static()
x = paddle.to_tensor(self.input, place=place)
if self.prepend is not None:
self.prepend = paddle.to_tensor(self.prepend, place=place)
if self.append is not None:
self.append = paddle.to_tensor(self.append, place=place)
out = paddle.diff(x,
n=self.n,
axis=self.axis,
prepend=self.prepend,
append=self.append)
self.assertTrue((out.numpy() == self.output).all(), True)
def func_grad(self):
for place in self.places:
x = paddle.to_tensor(self.input, place=place, stop_gradient=False)
if self.prepend is not None:
self.prepend = paddle.to_tensor(self.prepend, place=place)
if self.append is not None:
self.append = paddle.to_tensor(self.append, place=place)
out = paddle.diff(x,
n=self.n,
axis=self.axis,
prepend=self.prepend,
append=self.append)
try:
out.backward()
x_grad = x.grad
except:
raise RuntimeError("Check Diff Gradient Failed")
def test_static(self):
paddle.enable_static()
places = [fluid.CPUPlace()]
if core.is_compiled_with_cuda():
places.append(fluid.CUDAPlace(0))
for place in places:
with fluid.program_guard(fluid.Program(), fluid.Program()):
x = paddle.fluid.data(
name="input",
shape=self.input.shape,
dtype=self.input.dtype)
has_pend = False
prepend = None
append = None
if self.prepend is not None:
has_pend = True
prepend = paddle.fluid.data(
name="prepend",
shape=self.prepend.shape,
dtype=self.prepend.dtype)
if self.append is not None:
has_pend = True
append = paddle.fluid.data(
name="append",
shape=self.append.shape,
dtype=self.append.dtype)
exe = fluid.Executor(place)
out = paddle.diff(
x, n=self.n, axis=self.axis, prepend=prepend, append=append)
fetches = exe.run(fluid.default_main_program(),
feed={
"input": self.input,
"prepend": self.prepend,
"append": self.append
},
fetch_list=[out])
self.assertTrue((fetches[0] == self.output).all(), True)