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Add no scale check for resize and upsample (#1484)
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Description: Describe your changes.
Add no scale check for resize and upsample
Motivation and Context

Why is this change required? What problem does it solve?
If it fixes an open issue, please link to the issue here.
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@yufenglee
yufenglee authored Jul 25, 2019
1 parent 258ff06 commit a8e3ff4
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Showing 3 changed files with 129 additions and 59 deletions.
27 changes: 18 additions & 9 deletions onnxruntime/core/providers/cpu/tensor/upsample.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -256,15 +256,15 @@ void upsampleBilinear(
auto output_width = static_cast<int64_t>(input_width * width_scale);
auto output_height = static_cast<int64_t>(input_height * height_scale);

size_t inx_buffer_size = 2 * sizeof(int64_t) * (output_height + output_width);
size_t idx_buffer_size = 2 * sizeof(int64_t) * (output_height + output_width);
size_t scale_buffer_size = 2 * sizeof(float_t) * (output_height + output_width);
auto inx_scale_data_buffer = alloc->Alloc(inx_buffer_size + scale_buffer_size);
BufferUniquePtr inx_scale_data_buffer_holder(inx_scale_data_buffer, BufferDeleter(alloc));
auto* inx_data = static_cast<int64_t*>(inx_scale_data_buffer_holder.get());
int64_t* input_width_mul_y1 = inx_data;
int64_t* input_width_mul_y2 = inx_data + output_height;
int64_t* in_x1 = inx_data + 2 * output_height;
int64_t* in_x2 = inx_data + 2 * output_height + output_width;
auto inx_scale_data_buffer = alloc->Alloc(idx_buffer_size + scale_buffer_size);
BufferUniquePtr idx_scale_data_buffer_holder(inx_scale_data_buffer, BufferDeleter(alloc));
auto* idx_data = static_cast<int64_t*>(idx_scale_data_buffer_holder.get());
int64_t* input_width_mul_y1 = idx_data;
int64_t* input_width_mul_y2 = idx_data + output_height;
int64_t* in_x1 = idx_data + 2 * output_height;
int64_t* in_x2 = idx_data + 2 * output_height + output_width;

auto* scale_data = reinterpret_cast<float*>(in_x2 + output_width);
float* dy1 = scale_data;
Expand Down Expand Up @@ -331,12 +331,21 @@ Status Upsample<T>::BaseCompute(OpKernelContext* context, const std::vector<floa
return Status(ONNXRUNTIME, INVALID_ARGUMENT, "Upsample: input tensor's dimension does not match the scales.");
}

bool no_scale = true;
std::vector<int64_t> Y_dims;
Y_dims.reserve( dims.size() );
for (std::size_t i = 0; i < dims.size(); i++) {
Y_dims.push_back(static_cast<int64_t>(scales[i] * dims[i]));
int64_t dim_y = static_cast<int64_t>(scales[i] * dims[i]);
if (no_scale && dim_y != dims[i]) no_scale = false;
Y_dims.push_back(dim_y);
}
Tensor* Y = context->Output(0, Y_dims);

if (no_scale) {
memcpy(Y->MutableDataRaw(), X->DataRaw(), Y->Size() * sizeof(T));
return Status::OK();
}

switch (mode_) {
case UpsampleMode::NN:
return UpsampleNearest<T>(X->template Data<T>(), Y->template MutableData<T>(), X->Shape(), Y->Shape(), scales);
Expand Down
101 changes: 71 additions & 30 deletions onnxruntime/test/providers/cpu/tensor/resize_op_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -27,28 +27,62 @@ TEST(ResizeOpTest, ResizeOpLineartDownSampleTest) {
test.Run();
}

TEST(ResizeOpTest, ResizeOpUpsampleNearestTest) {
TEST(ResizeOpTest, ResizeOpLineartUpSampleTest) {
OpTester test("Resize", 10);
std::vector<float> scales{1.0f, 1.0f, 2.0f, 3.0f};
std::vector<float> scales{1.0f, 1.0f, 2.0f, 4.0f};
test.AddAttribute("mode", "linear");

test.AddAttribute("mode", "nearest");
const int64_t N = 2, C = 1, H = 2, W = 2;
std::vector<float> X = {1.0f, 3.0f,
4.0f, 8.0f,

const int64_t N = 1, C = 1, H = 2, W = 2;
std::vector<float> X = {1.0f, 2.0f, 3.0f, 4.0f};
6.0f, 2.0f,
7.0f, 11.0f};

test.AddInput<float>("X", {N, C, H, W}, X);
test.AddInput<float>("scales", {4}, scales);

std::vector<float> Y = {1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f};
std::vector<float> Y = {
1.0f, 1.5f, 2.0f, 2.5f, 3.0f, 3.0f, 3.0f, 3.0f,
2.5f, 3.25f, 4.0f, 4.75f, 5.5f, 5.5f, 5.5f, 5.5f,
4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 8.0f, 8.0f, 8.0f,
4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 8.0f, 8.0f, 8.0f,

6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 2.0f, 2.0f, 2.0f,
6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 11.0f, 11.0f, 11.0f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 11.0f, 11.0f, 11.0f};

test.AddOutput<float>("Y", {N, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.Run();
}

TEST(ResizeOpTest, ResizeOpNearestTest) {
TEST(ResizeOpTest, ResizeOpLineartNoScaleTest) {
OpTester test("Resize", 10);
std::vector<float> scales{1.0f, 1.0f, 1.0f, 1.0f};
test.AddAttribute("mode", "linear");

const int64_t N = 2, C = 1, H = 2, W = 2;
std::vector<float> X = {1.0f, 3.0f,
4.0f, 8.0f,

6.0f, 2.0f,
7.0f, 11.0f};

test.AddInput<float>("X", {N, C, H, W}, X);
test.AddInput<float>("scales", {4}, scales);

std::vector<float> Y = {1.0f, 3.0f,
4.0f, 8.0f,

6.0f, 2.0f,
7.0f, 11.0f};

test.AddOutput<float>("Y", {N, C, H, W}, Y);
test.Run();
}

TEST(ResizeOpTest, ResizeOpNearestDownSampleTest) {
OpTester test("Resize", 10);
std::vector<float> scales{1.0f, 1.0f, 0.6f, 0.6f};

Expand All @@ -68,37 +102,44 @@ TEST(ResizeOpTest, ResizeOpNearestTest) {
test.Run();
}

TEST(ResizeOpTest, ResizeOpBilinearTest) {
TEST(ResizeOpTest, ResizeOpNearestUpSampleTest) {
OpTester test("Resize", 10);
std::vector<float> scales{1.0f, 1.0f, 0.5f, 0.5f};

test.AddAttribute("mode", "linear");
std::vector<float> scales{1.0f, 1.0f, 2.0f, 3.0f};

const int64_t N = 2, C = 1, H = 4, W = 8;
std::vector<float> X = {
1.0f, 1.5f, 2.0f, 2.5f, 3.0f, 3.0f, 3.0f, 3.0f,
2.0f, 2.5f, 3.0f, 3.5f, 4.0f, 4.0f, 4.0f, 4.0f,
3.0f, 3.5f, 4.0f, 4.5f, 5.0f, 5.0f, 5.0f, 5.0f,
3.0f, 3.5f, 4.0f, 4.5f, 5.0f, 5.0f, 5.0f, 5.0f,
test.AddAttribute("mode", "nearest");

3.0f, 3.5f, 4.0f, 4.5f, 5.0f, 5.0f, 5.0f, 5.0f,
5.0f, 5.5f, 6.0f, 6.5f, 7.0f, 7.0f, 7.0f, 7.0f,
7.0f, 7.5f, 8.0f, 8.5f, 9.0f, 9.0f, 9.0f, 9.0f,
7.0f, 7.5f, 8.0f, 8.5f, 9.0f, 9.0f, 9.0f, 9.0f};
const int64_t N = 1, C = 1, H = 2, W = 2;
std::vector<float> X = {1.0f, 2.0f, 3.0f, 4.0f};

test.AddInput<float>("X", {N, C, H, W}, X);
test.AddInput<float>("scales", {4}, scales);

std::vector<float> Y = {
1.0f, 2.0f, 3.0f, 3.0f,
3.0f, 4.0f, 5.0f, 5.0f,

3.0f, 4.0f, 5.0f, 5.0f,
7.0f, 8.0f, 9.0f, 9.0f};
std::vector<float> Y = {1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f};

test.AddOutput<float>("Y", {N, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.Run();
}

TEST(UpsampleOpTest, ResizeOpNearestNoScaleTest) {
OpTester test("Resize", 10);
std::vector<float> scales{1.0f, 1.0f, 1.0f, 1.0f};

test.AddAttribute("mode", "nearest");

const int64_t N = 1, C = 1, H = 2, W = 2;
std::vector<float> X = {1.0f, 2.0f, 3.0f, 4.0f};

test.AddInput<float>("X", {N, C, H, W}, X);
test.AddInput<float>("scales", {4}, scales);

std::vector<float> Y = {1.0f, 2.0f, 3.0f, 4.0f};

test.AddOutput<float>("Y", {N, C, H, W}, Y);
test.Run();
}

} // namespace test
} // namespace onnxruntime
60 changes: 40 additions & 20 deletions onnxruntime/test/providers/cpu/tensor/upsample_op_test.cc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@ TEST(UpsampleOpTest, UpsampleOpNearestTest_int32) {
7, 7, 7, 9, 9, 9};

test.AddOutput<int32_t>("Y", {N, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider}); //TensorRT: nvinfer1::query::Ports<nvinfer1::query::AbstractTensor>&): Assertion `!formats.empty()' failed
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider}); //TensorRT: nvinfer1::query::Ports<nvinfer1::query::AbstractTensor>&): Assertion `!formats.empty()' failed
}

TEST(UpsampleOpTest, UpsampleOpNearestTest_uint8) {
Expand Down Expand Up @@ -170,10 +170,9 @@ TEST(UpsampleOpTest, UpsampleOpNearest222XTest) {
3.0f, 3.0f, 5.0f, 5.0f,
3.0f, 3.0f, 5.0f, 5.0f,
7.0f, 7.0f, 9.0f, 9.0f,
7.0f, 7.0f, 9.0f, 9.0f
};
7.0f, 7.0f, 9.0f, 9.0f};

test.AddOutput<float>("Y", {N*2, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.AddOutput<float>("Y", {N * 2, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.Run();
}

Expand Down Expand Up @@ -208,6 +207,32 @@ TEST(UpsampleOpTest, UpsampleOpNearest15XTest) {
test.Run();
}

TEST(UpsampleOpTest, UpsampleOpNearestTest_NoScale) {
OpTester test("Upsample");

std::vector<float> scales{1.0f, 1.0f, 1.0f, 1.0f};
test.AddAttribute("mode", "nearest");
test.AddAttribute("scales", scales);

const int64_t N = 1, C = 2, H = 2, W = 2;
std::vector<float> X = {1.0f, 3.0f,
3.0f, 5.0f,

3.0f, 5.0f,
7.0f, 9.0f};

test.AddInput<float>("X", {N, C, H, W}, X);

std::vector<float> Y = {1.0f, 3.0f,
3.0f, 5.0f,

3.0f, 5.0f,
7.0f, 9.0f};

test.AddOutput<float>("Y", {N, C, H, W}, Y);
test.Run();
}

TEST(UpsampleOpTest, UpsampleOpNearest2XTest_int32) {
OpTester test("Upsample");

Expand Down Expand Up @@ -236,7 +261,7 @@ TEST(UpsampleOpTest, UpsampleOpNearest2XTest_int32) {
7, 7, 9, 9};

test.AddOutput<int32_t>("Y", {N, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider}); //TensorRT: nvinfer1::query::Ports<nvinfer1::query::AbstractTensor>&): Assertion `!formats.empty()' failed
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider}); //TensorRT: nvinfer1::query::Ports<nvinfer1::query::AbstractTensor>&): Assertion `!formats.empty()' failed
}

TEST(UpsampleOpTest, UpsampleOpBilinearTest) {
Expand Down Expand Up @@ -270,34 +295,29 @@ TEST(UpsampleOpTest, UpsampleOpBilinearTest) {
test.Run();
}

TEST(UpsampleOpTest, UpsampleOpBilinearTest2) {
TEST(UpsampleOpTest, UpsampleOpBilinearTest_NoScale) {
OpTester test("Upsample");

std::vector<float> scales{1.0f, 1.0f, 2.0f, 4.0f};
std::vector<float> scales{1.0f, 1.0f, 1.0f, 1.0f};
test.AddAttribute("mode", "linear");
test.AddAttribute("scales", scales);

const int64_t N = 2, C = 1, H = 2, W = 2;
std::vector<float> X = {1.0f, 3.0f,
4.0f, 8.0f,
3.0f, 5.0f,

6.0f, 2.0f,
7.0f, 11.0f};
3.0f, 5.0f,
7.0f, 9.0f};

test.AddInput<float>("X", {N, C, H, W}, X);

std::vector<float> Y = {
1.0f, 1.5f, 2.0f, 2.5f, 3.0f, 3.0f, 3.0f, 3.0f,
2.5f, 3.25f, 4.0f, 4.75f, 5.5f, 5.5f, 5.5f, 5.5f,
4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 8.0f, 8.0f, 8.0f,
4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 8.0f, 8.0f, 8.0f,
std::vector<float> Y = {1.0f, 3.0f,
3.0f, 5.0f,

6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 2.0f, 2.0f, 2.0f,
6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 11.0f, 11.0f, 11.0f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 11.0f, 11.0f, 11.0f};
3.0f, 5.0f,
7.0f, 9.0f};

test.AddOutput<float>("Y", {N, C, (int64_t)(H * scales[2]), (int64_t)(W * scales[3])}, Y);
test.AddOutput<float>("Y", {N, C, H, W}, Y);
test.Run();
}

Expand Down

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