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support 0d tensor for interpolate #49929

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merged 9 commits into from
Jan 31, 2023
Merged

support 0d tensor for interpolate #49929

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1eed205
support 0d tensor for interpolate
tink2123 Jan 18, 2023
71127bd
support 0d tensor for interpolate
tink2123 Jan 18, 2023
d706fe7
add xpu unittest for interp
tink2123 Jan 18, 2023
324fccb
update unittest for interpolate
tink2123 Jan 20, 2023
ce439c9
Merge branch 'develop' into 0d_tensor
tink2123 Jan 20, 2023
31730d2
fix coverage
tink2123 Jan 28, 2023
9317496
fix code style
tink2123 Jan 28, 2023
1e8d701
fix for coverage
tink2123 Jan 29, 2023
872e1ea
fix coverage
tink2123 Jan 30, 2023
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46 changes: 27 additions & 19 deletions paddle/phi/infermeta/multiary.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -1424,16 +1424,18 @@ static void Interpolate1DInferShapeCheck(
if (scale_tensor) {
auto scale_tensor_dim = scale_tensor.dims();
PADDLE_ENFORCE_EQ(
scale_tensor_dim.size(),
1,
scale_tensor_dim.size() == 1 || scale_tensor_dim.size() == 0,
true,
phi::errors::InvalidArgument(
"Scale's dimension size must be 1, but got dimension = %d .",
"Scale's dimension size must be 1 or 0, but got dimension = %d .",
scale_tensor_dim.size()));
PADDLE_ENFORCE_EQ(scale_tensor_dim[0],
1,
phi::errors::InvalidArgument(
"Scale's shape must be 1, but got shape = %d .",
scale_tensor_dim[0]));
if (scale_tensor_dim.size() == 1) {
PADDLE_ENFORCE_EQ(scale_tensor_dim[0],
1,
phi::errors::InvalidArgument(
"Scale's shape must be 1, but got shape = %d .",
scale_tensor_dim[0]));
}
out_w_tmp = -1;
} else {
if (scale.size() > 0) {
Expand Down Expand Up @@ -1550,19 +1552,25 @@ static void Interpolate2DInferShapeCheck(
}

int out_h_tmp, out_w_tmp;

if (scale_tensor) {
auto scale_tensor_dim = scale_tensor.dims();
PADDLE_ENFORCE_EQ(
scale_tensor_dim.size(),
1,
scale_tensor_dim.size() == 1 || scale_tensor_dim.size() == 0,
true,
phi::errors::InvalidArgument(
"Scale's dimension size must be 1, but got dimension = %d .",
"Scale's dimension size must be 1 or 0, but got dimension = %d .",
scale_tensor_dim.size()));
PADDLE_ENFORCE_EQ(scale_tensor_dim[0] == 2 || scale_tensor_dim[0] == 1,
true,
phi::errors::InvalidArgument(
"Scale's shape must be 2 or 1, but got shape = %d .",
scale_tensor_dim[0]));

if (scale_tensor_dim.size() == 1) {
PADDLE_ENFORCE_EQ(
scale_tensor_dim[0] == 2 || scale_tensor_dim[0] == 1,
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什么情况下scale的shape会是[2]呀

true,
phi::errors::InvalidArgument(
"Scale's shape must be 2 or 1, but got shape = %d .",
scale_tensor_dim[0]));
}

out_h_tmp = -1;
out_w_tmp = -1;
} else {
Expand Down Expand Up @@ -1695,10 +1703,10 @@ static void Interpolate3DInferShapeCheck(
if (scale_tensor) {
auto scale_tensor_dim = scale_tensor.dims();
PADDLE_ENFORCE_EQ(
scale_tensor_dim.size(),
1,
scale_tensor_dim.size() == 1 || scale_tensor_dim.size() == 0,
true,
phi::errors::InvalidArgument(
"Scale's dimension size must be 1, but got size = %d .",
"Scale's dimension size must be 1 or 0, but got size = %d .",
scale_tensor_dim.size()));
PADDLE_ENFORCE_EQ(scale_tensor_dim[0] == 3 || scale_tensor_dim[0] == 1,
true,
Expand Down
14 changes: 8 additions & 6 deletions paddle/phi/kernels/funcs/interpolate_function.h
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Original file line number Diff line number Diff line change
Expand Up @@ -85,12 +85,14 @@ inline std::vector<int> get_new_shape(
std::vector<int> vec_new_shape;
for (size_t i = 0; i < list_new_shape_tensor.size(); ++i) {
auto tensor = list_new_shape_tensor[i];
PADDLE_ENFORCE_EQ(
tensor->dims(),
phi::make_ddim({1}),
errors::InvalidArgument("The shape of dimension tensor should be [1],"
"but received d%.",
tensor->dims()));
PADDLE_ENFORCE_EQ(tensor->dims() == phi::make_ddim({1}) ||
tensor->dims() == phi::make_ddim({}),
true,
errors::InvalidArgument(
"The shape of dimension tensor should be [1] or [],"
"but received d%.",
tensor->dims()));

#ifdef PADDLE_WITH_XPU
if (tensor->place().GetType() == phi::AllocationType::XPU) {
DenseTensor temp;
Expand Down
75 changes: 75 additions & 0 deletions python/paddle/fluid/tests/unittests/test_bilinear_interp_v2_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -816,5 +816,80 @@ def test_main(self):
np.testing.assert_allclose(x_g_np_1, x_g_np_2, atol=1e-2, rtol=1e-2)


class TestBilinearInterpOpAPI_0DTensorScale(unittest.TestCase):
def test_case(self):
import paddle

if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with fluid.dygraph.guard(place):
input_data = np.random.random((2, 3, 6, 6)).astype("float32")
input_x = paddle.to_tensor(input_data)
expect_res = bilinear_interp_np(
input_data, out_h=12, out_w=12, align_corners=False
)
scale_0d = paddle.full([], 2)
out = interpolate(
x=input_x,
scale_factor=scale_0d,
mode="bilinear",
align_corners=False,
)
np.testing.assert_allclose(out.numpy(), expect_res, rtol=1e-05)


class TestBilinearInterpOpAPI_0DTensorScale2(unittest.TestCase):
def test_case(self):
import paddle

if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with fluid.dygraph.guard(place):
input_data = np.random.random((2, 3, 6, 6)).astype("float32")
input_x = paddle.to_tensor(input_data)
expect_res = bilinear_interp_np(
input_data, out_h=12, out_w=12, align_corners=False
)
scale_0d = [paddle.full([], 2), paddle.full([], 2)]
out = interpolate(
x=input_x,
scale_factor=scale_0d,
mode="bilinear",
align_corners=False,
)
np.testing.assert_allclose(out.numpy(), expect_res, rtol=1e-05)


class TestBilinearInterpOpAPI_0DTensorOutSize(unittest.TestCase):
def test_case(self):
import paddle

if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
else:
place = core.CPUPlace()
with fluid.dygraph.guard(place):
input_data = np.random.random((2, 3, 6, 6)).astype("float32")
input_x = paddle.to_tensor(input_data)
expect_res = bilinear_interp_np(
input_data, out_h=12, out_w=12, align_corners=False
)
output_size = [
paddle.full([], 12, dtype="int32"),
paddle.full([], 12, dtype="int32"),
]
out = interpolate(
x=input_x,
size=output_size,
mode="bilinear",
align_corners=False,
)
np.testing.assert_allclose(out.numpy(), expect_res, rtol=1e-05)


if __name__ == "__main__":
unittest.main()
101 changes: 101 additions & 0 deletions python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1388,6 +1388,72 @@ def test_atan2(self):
self.assertEqual(x1.grad.numpy(), 0.5)
self.assertEqual(x2.grad.numpy(), 0)

def test_interpolate(self):
from paddle.nn.functional import interpolate

input_x = paddle.rand([2, 3, 6, 6])
input_x.stop_gradient = False
origin_result = interpolate(
x=input_x, size=[12, 12], mode="bilinear", align_corners=False
)

output_size = [
paddle.full([], 12, dtype="int32"),
paddle.full([], 12, dtype="int32"),
]
out1 = interpolate(
x=input_x, size=output_size, mode="bilinear", align_corners=False
)
out1.backward()

self.assertEqual(out1.shape, [2, 3, 12, 12])
self.assertEqual(input_x.grad.shape, [2, 3, 6, 6])

scale_1 = [paddle.full([], 2), paddle.full([], 2)]
out2 = interpolate(
x=input_x,
scale_factor=scale_1,
mode="bilinear",
align_corners=False,
)
out2.backward()

self.assertEqual(out2.shape, [2, 3, 12, 12])
self.assertEqual(input_x.grad.shape, [2, 3, 6, 6])

scale_2 = paddle.full([], 2)
out3 = interpolate(
x=input_x,
scale_factor=scale_2,
mode="bilinear",
align_corners=False,
)
out3.backward()

# for coverage
scale_3 = paddle.full([1], 2)
input_3d = paddle.rand([2, 3, 6])
out4 = interpolate(
x=input_3d,
scale_factor=scale_3,
mode="LINEAR",
align_corners=False,
data_format="NCW",
)

self.assertEqual(out3.shape, [2, 3, 12, 12])
self.assertEqual(input_x.grad.shape, [2, 3, 6, 6])

np.testing.assert_allclose(
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origin_result.numpy(), out1.numpy(), rtol=1e-05
)
np.testing.assert_allclose(
origin_result.numpy(), out2.numpy(), rtol=1e-05
)
np.testing.assert_allclose(
origin_result.numpy(), out3.numpy(), rtol=1e-05
)

def test_maseked_select(self):
x = paddle.rand([])
x.stop_gradient = False
Expand Down Expand Up @@ -2223,6 +2289,41 @@ def test_atan2(self):

self.assertEqual(res[0].shape, ())

@prog_scope()
def test_interpolate(self):
from paddle.nn.functional import interpolate

input_x = paddle.rand([2, 3, 6, 6])
input_x.stop_gradient = False

output_size = [
paddle.full([], 12, dtype="int32"),
paddle.full([], 12, dtype="int32"),
]

out1 = interpolate(
x=input_x, size=output_size, mode="bilinear", align_corners=False
)
paddle.static.append_backward(out1.sum())
prog = paddle.static.default_main_program()
res1 = self.exe.run(prog, feed={}, fetch_list=[out1, input_x.grad_name])

scale_1 = paddle.full([], 2)
out2 = interpolate(
x=input_x,
scale_factor=scale_1,
mode="bilinear",
align_corners=False,
)
paddle.static.append_backward(out2.sum())
prog = paddle.static.default_main_program()
res2 = self.exe.run(prog, feed={}, fetch_list=[out2, input_x.grad_name])

self.assertEqual(res1[0].shape, (2, 3, 12, 12))
self.assertEqual(res1[1].shape, (2, 3, 6, 6))
self.assertEqual(res2[0].shape, (2, 3, 12, 12))
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self.assertEqual(res2[1].shape, (2, 3, 6, 6))

@prog_scope()
def test_maseked_select(self):
x = paddle.rand([])
Expand Down
55 changes: 55 additions & 0 deletions python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -835,6 +835,61 @@ def test_allclose(self):
y = paddle.full([], 0.6)
self.assertFalse(paddle.allclose(x, y))

def test_interpolate(self):
from paddle.nn.functional import interpolate

input_x = paddle.rand([2, 3, 6, 6])
input_x.stop_gradient = False
origin_result = interpolate(
x=input_x, size=[12, 12], mode="bilinear", align_corners=False
)

output_size = [
paddle.full([], 12, dtype="int32"),
paddle.full([], 12, dtype="int32"),
]
out1 = interpolate(
x=input_x, size=output_size, mode="bilinear", align_corners=False
)
out1.backward()

self.assertEqual(out1.shape, [2, 3, 12, 12])
self.assertEqual(input_x.grad.shape, [2, 3, 6, 6])

scale_1 = [paddle.full([], 2), paddle.full([], 2)]
out2 = interpolate(
x=input_x,
scale_factor=scale_1,
mode="bilinear",
align_corners=False,
)
out2.backward()

self.assertEqual(out2.shape, [2, 3, 12, 12])
self.assertEqual(input_x.grad.shape, [2, 3, 6, 6])

scale_2 = paddle.full([], 2)
out3 = interpolate(
x=input_x,
scale_factor=scale_2,
mode="bilinear",
align_corners=False,
)
out3.backward()

self.assertEqual(out3.shape, [2, 3, 12, 12])
self.assertEqual(input_x.grad.shape, [2, 3, 6, 6])

np.testing.assert_allclose(
origin_result.numpy(), out1.numpy(), rtol=1e-05
)
np.testing.assert_allclose(
origin_result.numpy(), out2.numpy(), rtol=1e-05
)
np.testing.assert_allclose(
origin_result.numpy(), out3.numpy(), rtol=1e-05
)

def test_equalall(self):
x = paddle.full([], 0.5)
y = paddle.full([], 0.6)
Expand Down
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