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Add no scale check for resize and upsample #1484

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Jul 25, 2019
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Add no scale check for resize and upsample #1484

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9b9e207
Add no scale check for resize and upsample
yufenglee Jul 24, 2019
c5f8c29
refactor unit tests
yufenglee Jul 24, 2019
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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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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
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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