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support 0d tensor for interpolate (PaddlePaddle#49929)
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* support 0d tensor for interpolate

* support 0d tensor for interpolate

* add xpu unittest for interp

* update unittest for interpolate

* fix coverage

* fix code style

* fix for coverage

* fix coverage
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@tink2123 @pangengzheng
tink2123 authored and pangengzheng committed Feb 2, 2023
1 parent 12cfe48 commit 8755b96
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Showing 6 changed files with 291 additions and 34 deletions.
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,
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(
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))
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
View file
Original file line number Diff line number Diff line change
Expand Up @@ -883,6 +883,61 @@ 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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