def test_static_graph_functional(self):
for use_cuda in ([False, True]
if core.is_compiled_with_cuda() else [False]):
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
paddle.enable_static()
x_1 = paddle.fluid.data(name="x",
shape=[2, 9, 4, 4],
dtype="float64")
x_2 = paddle.fluid.data(name="x2",
shape=[2, 4, 4, 9],
dtype="float64")
out_1 = F.pixel_shuffle(x_1, 3)
out_2 = F.pixel_shuffle(x_2, 3, "NHWC")
exe = paddle.static.Executor(place=place)
res_1 = exe.run(fluid.default_main_program(),
feed={"x": self.x_1_np},
fetch_list=out_1,
use_prune=True)
res_2 = exe.run(fluid.default_main_program(),
feed={"x2": self.x_2_np},
fetch_list=out_2,
use_prune=True)
assert np.allclose(res_1, self.out_1_np)
assert np.allclose(res_2, self.out_2_np)
def run_dygraph(self, up_factor, data_format):
n, c, h, w = 2, 9, 4, 4
if data_format == "NCHW":
shape = [n, c, h, w]
if data_format == "NHWC":
shape = [n, h, w, c]
x = np.random.random(shape).astype("float64")
npresult = pixel_shuffle_np(x, up_factor, data_format)
for use_cuda in ([False, True]
if core.is_compiled_with_cuda() else [False]):
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
paddle.disable_static(place=place)
pixel_shuffle = paddle.nn.PixelShuffle(up_factor,
data_format=data_format)
result = pixel_shuffle(paddle.to_tensor(x))
self.assertTrue(np.allclose(result.numpy(), npresult))
result_functional = F.pixel_shuffle(paddle.to_tensor(x), 3,
data_format)
self.assertTrue(np.allclose(result_functional.numpy(), npresult))
def forward(self, x):
return F.pixel_shuffle(x, self.upscale_factor)
def error_data_format():
with paddle.fluid.dygraph.guard():
x = np.random.random([2, 9, 4, 4]).astype("float64")
pixel_shuffle = F.pixel_shuffle(paddle.to_tensor(x), 3, "WOW")
def error_upscale_factor():
with paddle.fluid.dygraph.guard():
x = np.random.random([2, 9, 4, 4]).astype("float64")
pixel_shuffle = F.pixel_shuffle(paddle.to_tensor(x), 3.33)
