def test_static_graph_functional(self):
'''test_static_graph_functional'''
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, 1, 12, 12], dtype="float64")
x_2 = paddle.fluid.data(
name="x2", shape=[2, 12, 12, 1], dtype="float64")
out_1 = F.pixel_unshuffle(x_1, 3)
out_2 = F.pixel_unshuffle(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, down_factor, data_format):
'''run_dygraph'''
n, c, h, w = 2, 1, 12, 12
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_unshuffle_np(x, down_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_unshuffle = paddle.nn.PixelUnshuffle(
down_factor, data_format=data_format)
result = pixel_unshuffle(paddle.to_tensor(x))
self.assertTrue(np.allclose(result.numpy(), npresult))
result_functional = F.pixel_unshuffle(
paddle.to_tensor(x), 3, data_format)
self.assertTrue(np.allclose(result_functional.numpy(), npresult))
pixel_unshuffle_str = 'downscale_factor={}'.format(down_factor)
if data_format != 'NCHW':
pixel_unshuffle_str += ', data_format={}'.format(data_format)
self.assertEqual(pixel_unshuffle.extra_repr(), pixel_unshuffle_str)
def error_data_format():
with paddle.fluid.dygraph.guard():
x = np.random.random([2, 1, 12, 12]).astype("float64")
pixel_unshuffle = F.pixel_unshuffle(
paddle.to_tensor(x), 3, "WOW")
def error_downscale_factor_2():
with paddle.fluid.dygraph.guard():
x = np.random.random([2, 1, 12, 12]).astype("float64")
pixel_unshuffle = F.pixel_unshuffle(paddle.to_tensor(x), -1)
def error_input():
with paddle.fluid.dygraph.guard():
x = np.random.random([4, 12, 12]).astype("float64")
pixel_unshuffle = F.pixel_unshuffle(paddle.to_tensor(x), 2)