fix pclint
This commit is contained in:
parent
11694db238
commit
ca517e4573
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@ -71,7 +71,7 @@ PYBIND_REGISTER(
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AutoContrastOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::AutoContrastOperation, TensorOperation, std::shared_ptr<vision::AutoContrastOperation>>(
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*m, "AutoContrastOperation")
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.def(py::init([](float cutoff, std::vector<uint32_t> ignore) {
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.def(py::init([](float cutoff, const std::vector<uint32_t> &ignore) {
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auto auto_contrast = std::make_shared<vision::AutoContrastOperation>(cutoff, ignore);
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THROW_IF_ERROR(auto_contrast->ValidateParams());
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return auto_contrast;
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@ -82,7 +82,7 @@ PYBIND_REGISTER(BoundingBoxAugmentOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::BoundingBoxAugmentOperation, TensorOperation,
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std::shared_ptr<vision::BoundingBoxAugmentOperation>>(*m,
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"BoundingBoxAugmentOperation")
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.def(py::init([](py::object transform, float ratio) {
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.def(py::init([](const py::object transform, float ratio) {
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auto bounding_box_augment = std::make_shared<vision::BoundingBoxAugmentOperation>(
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std::move(toTensorOperation(transform)), ratio);
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THROW_IF_ERROR(bounding_box_augment->ValidateParams());
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@ -94,7 +94,7 @@ PYBIND_REGISTER(
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CenterCropOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::CenterCropOperation, TensorOperation, std::shared_ptr<vision::CenterCropOperation>>(
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*m, "CenterCropOperation", "Tensor operation to crop and image in the middle. Takes height and width (optional)")
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.def(py::init([](std::vector<int32_t> size) {
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.def(py::init([](const std::vector<int32_t> &size) {
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auto center_crop = std::make_shared<vision::CenterCropOperation>(size);
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THROW_IF_ERROR(center_crop->ValidateParams());
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return center_crop;
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@ -104,7 +104,7 @@ PYBIND_REGISTER(
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PYBIND_REGISTER(CropOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::CropOperation, TensorOperation, std::shared_ptr<vision::CropOperation>>(
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*m, "CropOperation", "Tensor operation to crop images")
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.def(py::init([](std::vector<int32_t> coordinates, std::vector<int32_t> size) {
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.def(py::init([](std::vector<int32_t> coordinates, const std::vector<int32_t> &size) {
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// In Python API, the order of coordinates is first top then left, which is different from
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// those in CropOperation. So we need to swap the coordinates.
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std::swap(coordinates[0], coordinates[1]);
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@ -219,7 +219,7 @@ PYBIND_REGISTER(
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NormalizeOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::NormalizeOperation, TensorOperation, std::shared_ptr<vision::NormalizeOperation>>(
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*m, "NormalizeOperation")
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.def(py::init([](std::vector<float> mean, std::vector<float> std) {
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.def(py::init([](const std::vector<float> &mean, const std::vector<float> &std) {
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auto normalize = std::make_shared<vision::NormalizeOperation>(mean, std);
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THROW_IF_ERROR(normalize->ValidateParams());
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return normalize;
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@ -240,8 +240,8 @@ PYBIND_REGISTER(
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PYBIND_REGISTER(PadOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::PadOperation, TensorOperation, std::shared_ptr<vision::PadOperation>>(
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*m, "PadOperation")
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.def(py::init(
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[](std::vector<int32_t> padding, std::vector<uint8_t> fill_value, BorderType padding_mode) {
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.def(py::init([](const std::vector<int32_t> &padding, const std::vector<uint8_t> &fill_value,
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BorderType padding_mode) {
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auto pad = std::make_shared<vision::PadOperation>(padding, fill_value, padding_mode);
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THROW_IF_ERROR(pad->ValidateParams());
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return pad;
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@ -266,8 +266,8 @@ PYBIND_REGISTER(RandomColorAdjustOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomColorAdjustOperation, TensorOperation,
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std::shared_ptr<vision::RandomColorAdjustOperation>>(*m,
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"RandomColorAdjustOperation")
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.def(py::init([](std::vector<float> brightness, std::vector<float> contrast,
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std::vector<float> saturation, std::vector<float> hue) {
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.def(py::init([](const std::vector<float> &brightness, const std::vector<float> &contrast,
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const std::vector<float> &saturation, const std::vector<float> &hue) {
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auto random_color_adjust =
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std::make_shared<vision::RandomColorAdjustOperation>(brightness, contrast, saturation, hue);
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THROW_IF_ERROR(random_color_adjust->ValidateParams());
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@ -286,14 +286,14 @@ PYBIND_REGISTER(
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}));
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}));
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PYBIND_REGISTER(RandomCropDecodeResizeOperation, 1, ([](const py::module *m) {
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PYBIND_REGISTER(
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RandomCropDecodeResizeOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomCropDecodeResizeOperation, TensorOperation,
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std::shared_ptr<vision::RandomCropDecodeResizeOperation>>(
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*m, "RandomCropDecodeResizeOperation")
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.def(py::init([](std::vector<int32_t> size, std::vector<float> scale, std::vector<float> ratio,
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InterpolationMode interpolation, int32_t max_attempts) {
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auto random_crop_decode_resize = std::make_shared<vision::RandomCropDecodeResizeOperation>(
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size, scale, ratio, interpolation, max_attempts);
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std::shared_ptr<vision::RandomCropDecodeResizeOperation>>(*m, "RandomCropDecodeResizeOperation")
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.def(py::init([](const std::vector<int32_t> &size, const std::vector<float> &scale,
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const std::vector<float> &ratio, InterpolationMode interpolation, int32_t max_attempts) {
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auto random_crop_decode_resize =
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std::make_shared<vision::RandomCropDecodeResizeOperation>(size, scale, ratio, interpolation, max_attempts);
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THROW_IF_ERROR(random_crop_decode_resize->ValidateParams());
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return random_crop_decode_resize;
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}));
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@ -303,8 +303,8 @@ PYBIND_REGISTER(
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RandomCropOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomCropOperation, TensorOperation, std::shared_ptr<vision::RandomCropOperation>>(
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*m, "RandomCropOperation")
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.def(py::init([](std::vector<int32_t> size, std::vector<int32_t> padding, bool pad_if_needed,
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std::vector<uint8_t> fill_value, BorderType padding_mode) {
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.def(py::init([](const std::vector<int32_t> &size, const std::vector<int32_t> &padding, bool pad_if_needed,
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const std::vector<uint8_t> &fill_value, BorderType padding_mode) {
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auto random_crop =
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std::make_shared<vision::RandomCropOperation>(size, padding, pad_if_needed, fill_value, padding_mode);
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THROW_IF_ERROR(random_crop->ValidateParams());
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@ -316,8 +316,9 @@ PYBIND_REGISTER(RandomCropWithBBoxOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomCropWithBBoxOperation, TensorOperation,
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std::shared_ptr<vision::RandomCropWithBBoxOperation>>(*m,
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"RandomCropWithBBoxOperation")
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.def(py::init([](std::vector<int32_t> size, std::vector<int32_t> padding, bool pad_if_needed,
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std::vector<uint8_t> fill_value, BorderType padding_mode) {
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.def(
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py::init([](const std::vector<int32_t> &size, const std::vector<int32_t> &padding,
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bool pad_if_needed, const std::vector<uint8_t> &fill_value, BorderType padding_mode) {
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auto random_crop_with_bbox = std::make_shared<vision::RandomCropWithBBoxOperation>(
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size, padding, pad_if_needed, fill_value, padding_mode);
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THROW_IF_ERROR(random_crop_with_bbox->ValidateParams());
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@ -358,14 +359,14 @@ PYBIND_REGISTER(RandomPosterizeOperation, 1, ([](const py::module *m) {
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}));
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}));
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PYBIND_REGISTER(RandomResizedCropOperation, 1, ([](const py::module *m) {
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PYBIND_REGISTER(
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RandomResizedCropOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomResizedCropOperation, TensorOperation,
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std::shared_ptr<vision::RandomResizedCropOperation>>(*m,
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"RandomResizedCropOperation")
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.def(py::init([](std::vector<int32_t> size, std::vector<float> scale, std::vector<float> ratio,
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InterpolationMode interpolation, int32_t max_attempts) {
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auto random_resized_crop = std::make_shared<vision::RandomResizedCropOperation>(
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size, scale, ratio, interpolation, max_attempts);
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std::shared_ptr<vision::RandomResizedCropOperation>>(*m, "RandomResizedCropOperation")
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.def(py::init([](const std::vector<int32_t> &size, const std::vector<float> &scale,
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const std::vector<float> &ratio, InterpolationMode interpolation, int32_t max_attempts) {
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auto random_resized_crop =
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std::make_shared<vision::RandomResizedCropOperation>(size, scale, ratio, interpolation, max_attempts);
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THROW_IF_ERROR(random_resized_crop->ValidateParams());
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return random_resized_crop;
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}));
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@ -375,8 +376,9 @@ PYBIND_REGISTER(RandomResizedCropWithBBoxOperation, 1, ([](const py::module *m)
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(void)py::class_<vision::RandomResizedCropWithBBoxOperation, TensorOperation,
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std::shared_ptr<vision::RandomResizedCropWithBBoxOperation>>(
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*m, "RandomResizedCropWithBBoxOperation")
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.def(py::init([](std::vector<int32_t> size, std::vector<float> scale, std::vector<float> ratio,
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InterpolationMode interpolation, int32_t max_attempts) {
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.def(py::init([](const std::vector<int32_t> &size, const std::vector<float> &scale,
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const std::vector<float> &ratio, InterpolationMode interpolation,
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int32_t max_attempts) {
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auto random_resized_crop_with_bbox = std::make_shared<vision::RandomResizedCropWithBBoxOperation>(
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size, scale, ratio, interpolation, max_attempts);
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THROW_IF_ERROR(random_resized_crop_with_bbox->ValidateParams());
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@ -388,7 +390,7 @@ PYBIND_REGISTER(
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RandomResizeOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomResizeOperation, TensorOperation, std::shared_ptr<vision::RandomResizeOperation>>(
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*m, "RandomResizeOperation")
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.def(py::init([](std::vector<int32_t> size) {
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.def(py::init([](const std::vector<int32_t> &size) {
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auto random_resize = std::make_shared<vision::RandomResizeOperation>(size);
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THROW_IF_ERROR(random_resize->ValidateParams());
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return random_resize;
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@ -399,7 +401,7 @@ PYBIND_REGISTER(RandomResizeWithBBoxOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomResizeWithBBoxOperation, TensorOperation,
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std::shared_ptr<vision::RandomResizeWithBBoxOperation>>(
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*m, "RandomResizeWithBBoxOperation")
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.def(py::init([](std::vector<int32_t> size) {
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.def(py::init([](const std::vector<int32_t> &size) {
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auto random_resize_with_bbox = std::make_shared<vision::RandomResizeWithBBoxOperation>(size);
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THROW_IF_ERROR(random_resize_with_bbox->ValidateParams());
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return random_resize_with_bbox;
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@ -422,7 +424,7 @@ PYBIND_REGISTER(
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RandomSelectSubpolicyOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomSelectSubpolicyOperation, TensorOperation,
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std::shared_ptr<vision::RandomSelectSubpolicyOperation>>(*m, "RandomSelectSubpolicyOperation")
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.def(py::init([](const py::list &py_policy) {
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.def(py::init([](const py::list py_policy) {
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std::vector<std::vector<std::pair<std::shared_ptr<TensorOperation>, double>>> cpp_policy;
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for (auto &py_sub : py_policy) {
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cpp_policy.push_back({});
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@ -459,7 +461,7 @@ PYBIND_REGISTER(
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PYBIND_REGISTER(RandomSharpnessOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomSharpnessOperation, TensorOperation,
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std::shared_ptr<vision::RandomSharpnessOperation>>(*m, "RandomSharpnessOperation")
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.def(py::init([](std::vector<float> degrees) {
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.def(py::init([](const std::vector<float> °rees) {
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auto random_sharpness = std::make_shared<vision::RandomSharpnessOperation>(degrees);
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THROW_IF_ERROR(random_sharpness->ValidateParams());
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return random_sharpness;
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@ -469,7 +471,7 @@ PYBIND_REGISTER(RandomSharpnessOperation, 1, ([](const py::module *m) {
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PYBIND_REGISTER(RandomSolarizeOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::RandomSolarizeOperation, TensorOperation,
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std::shared_ptr<vision::RandomSolarizeOperation>>(*m, "RandomSolarizeOperation")
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.def(py::init([](std::vector<uint8_t> threshold) {
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.def(py::init([](const std::vector<uint8_t> &threshold) {
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auto random_solarize = std::make_shared<vision::RandomSolarizeOperation>(threshold);
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THROW_IF_ERROR(random_solarize->ValidateParams());
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return random_solarize;
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@ -513,7 +515,7 @@ PYBIND_REGISTER(RescaleOperation, 1, ([](const py::module *m) {
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PYBIND_REGISTER(ResizeOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::ResizeOperation, TensorOperation, std::shared_ptr<vision::ResizeOperation>>(
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*m, "ResizeOperation")
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.def(py::init([](std::vector<int32_t> size, InterpolationMode interpolation_mode) {
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.def(py::init([](const std::vector<int32_t> &size, InterpolationMode interpolation_mode) {
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auto resize = std::make_shared<vision::ResizeOperation>(size, interpolation_mode);
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THROW_IF_ERROR(resize->ValidateParams());
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return resize;
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@ -523,7 +525,7 @@ PYBIND_REGISTER(ResizeOperation, 1, ([](const py::module *m) {
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PYBIND_REGISTER(ResizeWithBBoxOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::ResizeWithBBoxOperation, TensorOperation,
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std::shared_ptr<vision::ResizeWithBBoxOperation>>(*m, "ResizeWithBBoxOperation")
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.def(py::init([](std::vector<int32_t> size, InterpolationMode interpolation_mode) {
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.def(py::init([](const std::vector<int32_t> &size, InterpolationMode interpolation_mode) {
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auto resize_with_bbox =
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std::make_shared<vision::ResizeWithBBoxOperation>(size, interpolation_mode);
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THROW_IF_ERROR(resize_with_bbox->ValidateParams());
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@ -570,8 +572,8 @@ PYBIND_REGISTER(SoftDvppDecodeRandomCropResizeJpegOperation, 1, ([](const py::mo
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(void)py::class_<vision::SoftDvppDecodeRandomCropResizeJpegOperation, TensorOperation,
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std::shared_ptr<vision::SoftDvppDecodeRandomCropResizeJpegOperation>>(
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*m, "SoftDvppDecodeRandomCropResizeJpegOperation")
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.def(py::init([](std::vector<int32_t> size, std::vector<float> scale, std::vector<float> ratio,
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int32_t max_attempts) {
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.def(py::init([](const std::vector<int32_t> &size, const std::vector<float> &scale,
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const std::vector<float> &ratio, int32_t max_attempts) {
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auto soft_dvpp_decode_random_crop_resize_jpeg =
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std::make_shared<vision::SoftDvppDecodeRandomCropResizeJpegOperation>(size, scale, ratio,
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max_attempts);
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@ -584,7 +586,7 @@ PYBIND_REGISTER(SoftDvppDecodeResizeJpegOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::SoftDvppDecodeResizeJpegOperation, TensorOperation,
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std::shared_ptr<vision::SoftDvppDecodeResizeJpegOperation>>(
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*m, "SoftDvppDecodeResizeJpegOperation")
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.def(py::init([](std::vector<int32_t> size) {
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.def(py::init([](const std::vector<int32_t> &size) {
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auto soft_dvpp_decode_resize_jpeg =
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std::make_shared<vision::SoftDvppDecodeResizeJpegOperation>(size);
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THROW_IF_ERROR(soft_dvpp_decode_resize_jpeg->ValidateParams());
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@ -596,7 +598,7 @@ PYBIND_REGISTER(
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UniformAugOperation, 1, ([](const py::module *m) {
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(void)py::class_<vision::UniformAugOperation, TensorOperation, std::shared_ptr<vision::UniformAugOperation>>(
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*m, "UniformAugOperation")
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.def(py::init([](py::list transforms, int32_t num_ops) {
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.def(py::init([](const py::list transforms, int32_t num_ops) {
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auto uniform_aug =
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std::make_shared<vision::UniformAugOperation>(std::move(toTensorOperations(transforms)), num_ops);
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THROW_IF_ERROR(uniform_aug->ValidateParams());
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@ -28,7 +28,7 @@ namespace dataset {
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namespace vision {
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#ifndef ENABLE_ANDROID
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// AutoContrastOperation
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AutoContrastOperation::AutoContrastOperation(float cutoff, std::vector<uint32_t> ignore)
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AutoContrastOperation::AutoContrastOperation(float cutoff, const std::vector<uint32_t> &ignore)
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: cutoff_(cutoff), ignore_(ignore) {}
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AutoContrastOperation::~AutoContrastOperation() = default;
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@ -37,7 +37,7 @@ constexpr char kAutoContrastOperation[] = "AutoContrast";
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class AutoContrastOperation : public TensorOperation {
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public:
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explicit AutoContrastOperation(float cutoff, std::vector<uint32_t> ignore);
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explicit AutoContrastOperation(float cutoff, const std::vector<uint32_t> &ignore);
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~AutoContrastOperation();
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@ -27,7 +27,7 @@ namespace mindspore {
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namespace dataset {
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namespace vision {
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#ifndef ENABLE_ANDROID
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BoundingBoxAugmentOperation::BoundingBoxAugmentOperation(std::shared_ptr<TensorOperation> transform, float ratio)
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BoundingBoxAugmentOperation::BoundingBoxAugmentOperation(const std::shared_ptr<TensorOperation> &transform, float ratio)
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: transform_(transform), ratio_(ratio) {}
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BoundingBoxAugmentOperation::~BoundingBoxAugmentOperation() = default;
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@ -37,7 +37,7 @@ constexpr char kBoundingBoxAugmentOperation[] = "BoundingBoxAugment";
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class BoundingBoxAugmentOperation : public TensorOperation {
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public:
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explicit BoundingBoxAugmentOperation(std::shared_ptr<TensorOperation> transform, float ratio);
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explicit BoundingBoxAugmentOperation(const std::shared_ptr<TensorOperation> &transform, float ratio);
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~BoundingBoxAugmentOperation();
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@ -24,7 +24,7 @@
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namespace mindspore {
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namespace dataset {
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namespace vision {
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CenterCropOperation::CenterCropOperation(std::vector<int32_t> size) : size_(size) {}
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CenterCropOperation::CenterCropOperation(const std::vector<int32_t> &size) : size_(size) {}
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CenterCropOperation::~CenterCropOperation() = default;
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@ -39,7 +39,7 @@ constexpr char kCenterCropOperation[] = "CenterCrop";
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class CenterCropOperation : public TensorOperation {
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public:
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explicit CenterCropOperation(std::vector<int32_t> size);
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explicit CenterCropOperation(const std::vector<int32_t> &size);
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~CenterCropOperation();
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@ -24,7 +24,7 @@
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namespace mindspore {
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namespace dataset {
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namespace vision {
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CropOperation::CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size)
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CropOperation::CropOperation(const std::vector<int32_t> &coordinates, const std::vector<int32_t> &size)
|
||||
: coordinates_(coordinates), size_(size) {}
|
||||
|
||||
CropOperation::~CropOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kCropOperation[] = "Crop";
|
|||
|
||||
class CropOperation : public TensorOperation {
|
||||
public:
|
||||
CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size);
|
||||
CropOperation(const std::vector<int32_t> &coordinates, const std::vector<int32_t> &size);
|
||||
|
||||
~CropOperation();
|
||||
|
||||
|
|
|
@ -25,7 +25,8 @@ namespace mindspore {
|
|||
namespace dataset {
|
||||
namespace vision {
|
||||
// NormalizeOperation
|
||||
NormalizeOperation::NormalizeOperation(std::vector<float> mean, std::vector<float> std) : mean_(mean), std_(std) {}
|
||||
NormalizeOperation::NormalizeOperation(const std::vector<float> &mean, const std::vector<float> &std)
|
||||
: mean_(mean), std_(std) {}
|
||||
|
||||
NormalizeOperation::~NormalizeOperation() = default;
|
||||
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kNormalizeOperation[] = "Normalize";
|
|||
|
||||
class NormalizeOperation : public TensorOperation {
|
||||
public:
|
||||
NormalizeOperation(std::vector<float> mean, std::vector<float> std);
|
||||
NormalizeOperation(const std::vector<float> &mean, const std::vector<float> &std);
|
||||
|
||||
~NormalizeOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,8 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// PadOperation
|
||||
PadOperation::PadOperation(std::vector<int32_t> padding, std::vector<uint8_t> fill_value, BorderType padding_mode)
|
||||
PadOperation::PadOperation(const std::vector<int32_t> &padding, const std::vector<uint8_t> &fill_value,
|
||||
BorderType padding_mode)
|
||||
: padding_(padding), fill_value_(fill_value), padding_mode_(padding_mode) {}
|
||||
|
||||
PadOperation::~PadOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kPadOperation[] = "Pad";
|
|||
|
||||
class PadOperation : public TensorOperation {
|
||||
public:
|
||||
PadOperation(std::vector<int32_t> padding, std::vector<uint8_t> fill_value, BorderType padding_mode);
|
||||
PadOperation(const std::vector<int32_t> &padding, const std::vector<uint8_t> &fill_value, BorderType padding_mode);
|
||||
|
||||
~PadOperation();
|
||||
|
||||
|
|
|
@ -33,8 +33,10 @@ constexpr size_t size_two = 2;
|
|||
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomColorAdjustOperation.
|
||||
RandomColorAdjustOperation::RandomColorAdjustOperation(std::vector<float> brightness, std::vector<float> contrast,
|
||||
std::vector<float> saturation, std::vector<float> hue)
|
||||
RandomColorAdjustOperation::RandomColorAdjustOperation(const std::vector<float> &brightness,
|
||||
const std::vector<float> &contrast,
|
||||
const std::vector<float> &saturation,
|
||||
const std::vector<float> &hue)
|
||||
: brightness_(brightness), contrast_(contrast), saturation_(saturation), hue_(hue) {
|
||||
random_op_ = true;
|
||||
}
|
||||
|
|
|
@ -37,8 +37,8 @@ constexpr char kRandomColorAdjustOperation[] = "RandomColorAdjust";
|
|||
|
||||
class RandomColorAdjustOperation : public TensorOperation {
|
||||
public:
|
||||
RandomColorAdjustOperation(std::vector<float> brightness, std::vector<float> contrast, std::vector<float> saturation,
|
||||
std::vector<float> hue);
|
||||
RandomColorAdjustOperation(const std::vector<float> &brightness, const std::vector<float> &contrast,
|
||||
const std::vector<float> &saturation, const std::vector<float> &hue);
|
||||
|
||||
~RandomColorAdjustOperation();
|
||||
|
||||
|
|
|
@ -28,8 +28,9 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomCropDecodeResizeOperation
|
||||
RandomCropDecodeResizeOperation::RandomCropDecodeResizeOperation(std::vector<int32_t> size, std::vector<float> scale,
|
||||
std::vector<float> ratio,
|
||||
RandomCropDecodeResizeOperation::RandomCropDecodeResizeOperation(const std::vector<int32_t> &size,
|
||||
const std::vector<float> &scale,
|
||||
const std::vector<float> &ratio,
|
||||
InterpolationMode interpolation, int32_t max_attempts)
|
||||
: RandomResizedCropOperation(size, scale, ratio, interpolation, max_attempts) {}
|
||||
|
||||
|
|
|
@ -38,8 +38,9 @@ constexpr char kRandomCropDecodeResizeOperation[] = "RandomCropDecodeResize";
|
|||
|
||||
class RandomCropDecodeResizeOperation : public RandomResizedCropOperation {
|
||||
public:
|
||||
RandomCropDecodeResizeOperation(std::vector<int32_t> size, std::vector<float> scale, std::vector<float> ratio,
|
||||
InterpolationMode interpolation, int32_t max_attempts);
|
||||
RandomCropDecodeResizeOperation(const std::vector<int32_t> &size, const std::vector<float> &scale,
|
||||
const std::vector<float> &ratio, InterpolationMode interpolation,
|
||||
int32_t max_attempts);
|
||||
|
||||
explicit RandomCropDecodeResizeOperation(const RandomResizedCropOperation &base);
|
||||
|
||||
|
|
|
@ -22,14 +22,14 @@
|
|||
#endif
|
||||
|
||||
#include "minddata/dataset/kernels/ir/validators.h"
|
||||
|
||||
namespace mindspore {
|
||||
namespace dataset {
|
||||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomCropOperation
|
||||
RandomCropOperation::RandomCropOperation(std::vector<int32_t> size, std::vector<int32_t> padding, bool pad_if_needed,
|
||||
std::vector<uint8_t> fill_value, BorderType padding_mode)
|
||||
RandomCropOperation::RandomCropOperation(const std::vector<int32_t> &size, const std::vector<int32_t> &padding,
|
||||
bool pad_if_needed, const std::vector<uint8_t> &fill_value,
|
||||
BorderType padding_mode)
|
||||
: TensorOperation(true),
|
||||
size_(size),
|
||||
padding_(padding),
|
||||
|
|
|
@ -37,8 +37,8 @@ constexpr char kRandomCropOperation[] = "RandomCrop";
|
|||
|
||||
class RandomCropOperation : public TensorOperation {
|
||||
public:
|
||||
RandomCropOperation(std::vector<int32_t> size, std::vector<int32_t> padding, bool pad_if_needed,
|
||||
std::vector<uint8_t> fill_value, BorderType padding_mode);
|
||||
RandomCropOperation(const std::vector<int32_t> &size, const std::vector<int32_t> &padding, bool pad_if_needed,
|
||||
const std::vector<uint8_t> &fill_value, BorderType padding_mode);
|
||||
|
||||
~RandomCropOperation();
|
||||
|
||||
|
|
|
@ -28,8 +28,9 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomCropWithBBoxOperation
|
||||
RandomCropWithBBoxOperation::RandomCropWithBBoxOperation(std::vector<int32_t> size, std::vector<int32_t> padding,
|
||||
bool pad_if_needed, std::vector<uint8_t> fill_value,
|
||||
RandomCropWithBBoxOperation::RandomCropWithBBoxOperation(const std::vector<int32_t> &size,
|
||||
const std::vector<int32_t> &padding, bool pad_if_needed,
|
||||
const std::vector<uint8_t> &fill_value,
|
||||
BorderType padding_mode)
|
||||
: TensorOperation(true),
|
||||
size_(size),
|
||||
|
|
|
@ -37,8 +37,8 @@ constexpr char kRandomCropWithBBoxOperation[] = "RandomCropWithBBox";
|
|||
|
||||
class RandomCropWithBBoxOperation : public TensorOperation {
|
||||
public:
|
||||
RandomCropWithBBoxOperation(std::vector<int32_t> size, std::vector<int32_t> padding, bool pad_if_needed,
|
||||
std::vector<uint8_t> fill_value, BorderType padding_mode);
|
||||
RandomCropWithBBoxOperation(const std::vector<int32_t> &size, const std::vector<int32_t> &padding, bool pad_if_needed,
|
||||
const std::vector<uint8_t> &fill_value, BorderType padding_mode);
|
||||
|
||||
~RandomCropWithBBoxOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,7 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomResizeOperation
|
||||
RandomResizeOperation::RandomResizeOperation(std::vector<int32_t> size) : TensorOperation(true), size_(size) {}
|
||||
RandomResizeOperation::RandomResizeOperation(const std::vector<int32_t> &size) : TensorOperation(true), size_(size) {}
|
||||
|
||||
RandomResizeOperation::~RandomResizeOperation() = default;
|
||||
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kRandomResizeOperation[] = "RandomResize";
|
|||
|
||||
class RandomResizeOperation : public TensorOperation {
|
||||
public:
|
||||
explicit RandomResizeOperation(std::vector<int32_t> size);
|
||||
explicit RandomResizeOperation(const std::vector<int32_t> &size);
|
||||
|
||||
~RandomResizeOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,7 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomResizeWithBBoxOperation
|
||||
RandomResizeWithBBoxOperation::RandomResizeWithBBoxOperation(std::vector<int32_t> size)
|
||||
RandomResizeWithBBoxOperation::RandomResizeWithBBoxOperation(const std::vector<int32_t> &size)
|
||||
: TensorOperation(true), size_(size) {}
|
||||
|
||||
RandomResizeWithBBoxOperation::~RandomResizeWithBBoxOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kRandomResizeWithBBoxOperation[] = "RandomResizeWithBBox";
|
|||
|
||||
class RandomResizeWithBBoxOperation : public TensorOperation {
|
||||
public:
|
||||
explicit RandomResizeWithBBoxOperation(std::vector<int32_t> size);
|
||||
explicit RandomResizeWithBBoxOperation(const std::vector<int32_t> &size);
|
||||
|
||||
~RandomResizeWithBBoxOperation();
|
||||
|
||||
|
|
|
@ -30,9 +30,9 @@ namespace vision {
|
|||
RandomResizedCropOperation::RandomResizedCropOperation(const RandomResizedCropOperation &) = default;
|
||||
|
||||
// RandomResizedCropOperation
|
||||
RandomResizedCropOperation::RandomResizedCropOperation(std::vector<int32_t> size, std::vector<float> scale,
|
||||
std::vector<float> ratio, InterpolationMode interpolation,
|
||||
int32_t max_attempts)
|
||||
RandomResizedCropOperation::RandomResizedCropOperation(const std::vector<int32_t> &size,
|
||||
const std::vector<float> &scale, const std::vector<float> &ratio,
|
||||
InterpolationMode interpolation, int32_t max_attempts)
|
||||
: TensorOperation(true),
|
||||
size_(size),
|
||||
scale_(scale),
|
||||
|
|
|
@ -37,8 +37,8 @@ constexpr char kRandomResizedCropOperation[] = "RandomResizedCrop";
|
|||
|
||||
class RandomResizedCropOperation : public TensorOperation {
|
||||
public:
|
||||
RandomResizedCropOperation(std::vector<int32_t> size, std::vector<float> scale, std::vector<float> ratio,
|
||||
InterpolationMode interpolation, int32_t max_attempts);
|
||||
RandomResizedCropOperation(const std::vector<int32_t> &size, const std::vector<float> &scale,
|
||||
const std::vector<float> &ratio, InterpolationMode interpolation, int32_t max_attempts);
|
||||
|
||||
/// \brief default copy constructor
|
||||
explicit RandomResizedCropOperation(const RandomResizedCropOperation &);
|
||||
|
|
|
@ -28,9 +28,9 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomResizedCropWithBBoxOperation
|
||||
RandomResizedCropWithBBoxOperation::RandomResizedCropWithBBoxOperation(std::vector<int32_t> size,
|
||||
std::vector<float> scale,
|
||||
std::vector<float> ratio,
|
||||
RandomResizedCropWithBBoxOperation::RandomResizedCropWithBBoxOperation(const std::vector<int32_t> &size,
|
||||
const std::vector<float> &scale,
|
||||
const std::vector<float> &ratio,
|
||||
InterpolationMode interpolation,
|
||||
int32_t max_attempts)
|
||||
: size_(size), scale_(scale), ratio_(ratio), interpolation_(interpolation), max_attempts_(max_attempts) {}
|
||||
|
|
|
@ -38,8 +38,8 @@ constexpr char kRandomResizedCropWithBBoxOperation[] = "RandomResizedCropWithBBo
|
|||
|
||||
class RandomResizedCropWithBBoxOperation : public TensorOperation {
|
||||
public:
|
||||
explicit RandomResizedCropWithBBoxOperation(std::vector<int32_t> size, std::vector<float> scale,
|
||||
std::vector<float> ratio, InterpolationMode interpolation,
|
||||
explicit RandomResizedCropWithBBoxOperation(const std::vector<int32_t> &size, const std::vector<float> &scale,
|
||||
const std::vector<float> &ratio, InterpolationMode interpolation,
|
||||
int32_t max_attempts);
|
||||
|
||||
~RandomResizedCropWithBBoxOperation();
|
||||
|
|
|
@ -29,7 +29,7 @@ namespace vision {
|
|||
#ifndef ENABLE_ANDROID
|
||||
// RandomSelectSubpolicyOperation.
|
||||
RandomSelectSubpolicyOperation::RandomSelectSubpolicyOperation(
|
||||
std::vector<std::vector<std::pair<std::shared_ptr<TensorOperation>, double>>> policy)
|
||||
const std::vector<std::vector<std::pair<std::shared_ptr<TensorOperation>, double>>> &policy)
|
||||
: TensorOperation(true), policy_(policy) {}
|
||||
|
||||
RandomSelectSubpolicyOperation::~RandomSelectSubpolicyOperation() = default;
|
||||
|
|
|
@ -38,7 +38,7 @@ constexpr char kRandomSelectSubpolicyOperation[] = "RandomSelectSubpolicy";
|
|||
class RandomSelectSubpolicyOperation : public TensorOperation {
|
||||
public:
|
||||
explicit RandomSelectSubpolicyOperation(
|
||||
std::vector<std::vector<std::pair<std::shared_ptr<TensorOperation>, double>>> policy);
|
||||
const std::vector<std::vector<std::pair<std::shared_ptr<TensorOperation>, double>>> &policy);
|
||||
|
||||
~RandomSelectSubpolicyOperation();
|
||||
|
||||
|
|
|
@ -32,7 +32,7 @@ constexpr size_t dimension_one = 1;
|
|||
constexpr size_t size_two = 2;
|
||||
|
||||
// Function to create RandomSharpness.
|
||||
RandomSharpnessOperation::RandomSharpnessOperation(std::vector<float> degrees)
|
||||
RandomSharpnessOperation::RandomSharpnessOperation(const std::vector<float> °rees)
|
||||
: TensorOperation(true), degrees_(degrees) {}
|
||||
|
||||
RandomSharpnessOperation::~RandomSharpnessOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kRandomSharpnessOperation[] = "RandomSharpness";
|
|||
|
||||
class RandomSharpnessOperation : public TensorOperation {
|
||||
public:
|
||||
explicit RandomSharpnessOperation(std::vector<float> degrees);
|
||||
explicit RandomSharpnessOperation(const std::vector<float> °rees);
|
||||
|
||||
~RandomSharpnessOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,7 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// RandomSolarizeOperation.
|
||||
RandomSolarizeOperation::RandomSolarizeOperation(std::vector<uint8_t> threshold)
|
||||
RandomSolarizeOperation::RandomSolarizeOperation(const std::vector<uint8_t> &threshold)
|
||||
: TensorOperation(true), threshold_(threshold) {}
|
||||
|
||||
RandomSolarizeOperation::~RandomSolarizeOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kRandomSolarizeOperation[] = "RandomSolarize";
|
|||
|
||||
class RandomSolarizeOperation : public TensorOperation {
|
||||
public:
|
||||
explicit RandomSolarizeOperation(std::vector<uint8_t> threshold);
|
||||
explicit RandomSolarizeOperation(const std::vector<uint8_t> &threshold);
|
||||
|
||||
~RandomSolarizeOperation();
|
||||
|
||||
|
|
|
@ -25,7 +25,7 @@ namespace mindspore {
|
|||
namespace dataset {
|
||||
namespace vision {
|
||||
// ResizeOperation
|
||||
ResizeOperation::ResizeOperation(std::vector<int32_t> size, InterpolationMode interpolation)
|
||||
ResizeOperation::ResizeOperation(const std::vector<int32_t> &size, InterpolationMode interpolation)
|
||||
: size_(size), interpolation_(interpolation) {}
|
||||
|
||||
ResizeOperation::~ResizeOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kResizeOperation[] = "Resize";
|
|||
|
||||
class ResizeOperation : public TensorOperation {
|
||||
public:
|
||||
explicit ResizeOperation(std::vector<int32_t> size, InterpolationMode interpolation);
|
||||
explicit ResizeOperation(const std::vector<int32_t> &size, InterpolationMode interpolation);
|
||||
|
||||
~ResizeOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,7 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// ResizeWithBBoxOperation
|
||||
ResizeWithBBoxOperation::ResizeWithBBoxOperation(std::vector<int32_t> size, InterpolationMode interpolation)
|
||||
ResizeWithBBoxOperation::ResizeWithBBoxOperation(const std::vector<int32_t> &size, InterpolationMode interpolation)
|
||||
: size_(size), interpolation_(interpolation) {}
|
||||
|
||||
ResizeWithBBoxOperation::~ResizeWithBBoxOperation() = default;
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kResizeWithBBoxOperation[] = "ResizeWithBBox";
|
|||
|
||||
class ResizeWithBBoxOperation : public TensorOperation {
|
||||
public:
|
||||
explicit ResizeWithBBoxOperation(std::vector<int32_t> size, InterpolationMode interpolation_mode);
|
||||
explicit ResizeWithBBoxOperation(const std::vector<int32_t> &size, InterpolationMode interpolation_mode);
|
||||
|
||||
~ResizeWithBBoxOperation();
|
||||
|
||||
|
|
|
@ -28,9 +28,8 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// SoftDvppDecodeRandomCropResizeJpegOperation
|
||||
SoftDvppDecodeRandomCropResizeJpegOperation::SoftDvppDecodeRandomCropResizeJpegOperation(std::vector<int32_t> size,
|
||||
std::vector<float> scale,
|
||||
std::vector<float> ratio,
|
||||
SoftDvppDecodeRandomCropResizeJpegOperation::SoftDvppDecodeRandomCropResizeJpegOperation(
|
||||
const std::vector<int32_t> &size, const std::vector<float> &scale, const std::vector<float> &ratio,
|
||||
int32_t max_attempts)
|
||||
: size_(size), scale_(scale), ratio_(ratio), max_attempts_(max_attempts) {}
|
||||
|
||||
|
|
|
@ -37,8 +37,9 @@ constexpr char kSoftDvppDecodeRandomCropResizeJpegOperation[] = "SoftDvppDecodeR
|
|||
|
||||
class SoftDvppDecodeRandomCropResizeJpegOperation : public TensorOperation {
|
||||
public:
|
||||
explicit SoftDvppDecodeRandomCropResizeJpegOperation(std::vector<int32_t> size, std::vector<float> scale,
|
||||
std::vector<float> ratio, int32_t max_attempts);
|
||||
explicit SoftDvppDecodeRandomCropResizeJpegOperation(const std::vector<int32_t> &size,
|
||||
const std::vector<float> &scale, const std::vector<float> &ratio,
|
||||
int32_t max_attempts);
|
||||
|
||||
~SoftDvppDecodeRandomCropResizeJpegOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,7 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// SoftDvppDecodeResizeJpegOperation
|
||||
SoftDvppDecodeResizeJpegOperation::SoftDvppDecodeResizeJpegOperation(std::vector<int32_t> size) : size_(size) {}
|
||||
SoftDvppDecodeResizeJpegOperation::SoftDvppDecodeResizeJpegOperation(const std::vector<int32_t> &size) : size_(size) {}
|
||||
|
||||
SoftDvppDecodeResizeJpegOperation::~SoftDvppDecodeResizeJpegOperation() = default;
|
||||
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kSoftDvppDecodeResizeJpegOperation[] = "SoftDvppDecodeResizeJpeg"
|
|||
|
||||
class SoftDvppDecodeResizeJpegOperation : public TensorOperation {
|
||||
public:
|
||||
explicit SoftDvppDecodeResizeJpegOperation(std::vector<int32_t> size);
|
||||
explicit SoftDvppDecodeResizeJpegOperation(const std::vector<int32_t> &size);
|
||||
|
||||
~SoftDvppDecodeResizeJpegOperation();
|
||||
|
||||
|
|
|
@ -28,7 +28,8 @@ namespace dataset {
|
|||
namespace vision {
|
||||
#ifndef ENABLE_ANDROID
|
||||
// UniformAugOperation
|
||||
UniformAugOperation::UniformAugOperation(std::vector<std::shared_ptr<TensorOperation>> transforms, int32_t num_ops)
|
||||
UniformAugOperation::UniformAugOperation(const std::vector<std::shared_ptr<TensorOperation>> &transforms,
|
||||
int32_t num_ops)
|
||||
: transforms_(transforms), num_ops_(num_ops) {}
|
||||
|
||||
UniformAugOperation::~UniformAugOperation() = default;
|
||||
|
@ -51,8 +52,9 @@ Status UniformAugOperation::ValidateParams() {
|
|||
|
||||
std::shared_ptr<TensorOp> UniformAugOperation::Build() {
|
||||
std::vector<std::shared_ptr<TensorOp>> tensor_ops;
|
||||
(void)std::transform(transforms_.begin(), transforms_.end(), std::back_inserter(tensor_ops),
|
||||
[](std::shared_ptr<TensorOperation> op) -> std::shared_ptr<TensorOp> { return op->Build(); });
|
||||
(void)std::transform(
|
||||
transforms_.begin(), transforms_.end(), std::back_inserter(tensor_ops),
|
||||
[](const std::shared_ptr<TensorOperation> &op) -> std::shared_ptr<TensorOp> { return op->Build(); });
|
||||
std::shared_ptr<UniformAugOp> tensor_op = std::make_shared<UniformAugOp>(tensor_ops, num_ops_);
|
||||
return tensor_op;
|
||||
}
|
||||
|
|
|
@ -37,7 +37,7 @@ constexpr char kUniformAugOperation[] = "UniformAug";
|
|||
|
||||
class UniformAugOperation : public TensorOperation {
|
||||
public:
|
||||
explicit UniformAugOperation(std::vector<std::shared_ptr<TensorOperation>> transforms, int32_t num_ops);
|
||||
explicit UniformAugOperation(const std::vector<std::shared_ptr<TensorOperation>> &transforms, int32_t num_ops);
|
||||
|
||||
~UniformAugOperation();
|
||||
|
||||
|
|
|
@ -20,18 +20,6 @@
|
|||
|
||||
namespace mindspore {
|
||||
namespace dataset {
|
||||
errno_t memcpy_s_loop(uchar *dest, size_t destMax, const uchar *src, size_t count) {
|
||||
int64_t step = 0;
|
||||
while (count >= SECUREC_MEM_MAX_LEN) {
|
||||
int ret_code = memcpy_s(dest + step * SECUREC_MEM_MAX_LEN, SECUREC_MEM_MAX_LEN, src + step * SECUREC_MEM_MAX_LEN,
|
||||
SECUREC_MEM_MAX_LEN);
|
||||
if (ret_code != 0) return ret_code;
|
||||
count -= SECUREC_MEM_MAX_LEN;
|
||||
step++;
|
||||
}
|
||||
return memcpy_s(dest + step * SECUREC_MEM_MAX_LEN, count, src + step * SECUREC_MEM_MAX_LEN, count);
|
||||
}
|
||||
|
||||
Status PluginOp::PluginToTensorRow(const std::vector<plugin::Tensor> &in_row, TensorRow *out_row) {
|
||||
CHECK_FAIL_RETURN_UNEXPECTED(out_row != nullptr && out_row->empty(), "null/empty out_row received!");
|
||||
out_row->reserve(in_row.size());
|
||||
|
@ -53,8 +41,13 @@ Status PluginOp::TensorRowToPlugin(const TensorRow &in_row, std::vector<plugin::
|
|||
if (in_row[ind]->type().IsNumeric()) {
|
||||
dsize_t buffer_size = in_row[ind]->SizeInBytes();
|
||||
tensor.buffer_.resize(buffer_size);
|
||||
int ret_code = memcpy_s_loop(tensor.buffer_.data(), buffer_size, in_row[ind]->GetBuffer(), buffer_size);
|
||||
CHECK_FAIL_RETURN_UNEXPECTED(ret_code == 0, "Failed to copy data into tensor.");
|
||||
if (buffer_size < SECUREC_MEM_MAX_LEN) {
|
||||
int ret_code = memcpy_s(tensor.buffer_.data(), tensor.buffer_.size(), in_row[ind]->GetBuffer(), buffer_size);
|
||||
CHECK_FAIL_RETURN_UNEXPECTED(ret_code == 0, "Failed to copy data into plugin tensor.");
|
||||
} else {
|
||||
auto ret_code = std::memcpy(tensor.buffer_.data(), in_row[ind]->GetBuffer(), buffer_size);
|
||||
CHECK_FAIL_RETURN_UNEXPECTED(ret_code == tensor.buffer_.data(), "Failed to copy data into plugin tensor.");
|
||||
}
|
||||
} else { // string tensor, for now, only tensor with 1 string is supported!
|
||||
CHECK_FAIL_RETURN_UNEXPECTED(in_row[ind]->shape().NumOfElements() == 1,
|
||||
"String tensor with more than 1 element is not yet supported.");
|
||||
|
|
Loading…
Reference in New Issue