diff options
Diffstat (limited to 'src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp | 224 |
1 files changed, 81 insertions, 143 deletions
diff --git a/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp b/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp index 1e0a1742f6..cb869838e2 100644 --- a/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp +++ b/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021 Arm Limited. + * Copyright (c) 2019-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -27,9 +27,12 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Window.h" + +#include "src/core/common/Registrars.h" #include "src/core/CPP/Validate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" +#include "src/cpu/kernels/boundingboxtransform/list.h" #include <arm_neon.h> @@ -37,7 +40,63 @@ namespace arm_compute { namespace { -Status validate_arguments(const ITensorInfo *boxes, const ITensorInfo *pred_boxes, const ITensorInfo *deltas, const BoundingBoxTransformInfo &info) +struct BoundingBoxTransformSelectorData +{ + DataType dt; +}; + +using BoundingBoxTransformSelctorPtr = std::add_pointer<bool(const BoundingBoxTransformSelectorData &data)>::type; +using BoundingBoxTransformUKernelPtr = std::add_pointer<void(const ITensor *boxes, + ITensor *pred_boxes, + const ITensor *deltas, + BoundingBoxTransformInfo bbinfo, + const Window &window)>::type; + +struct BoundingBoxTransformKernel +{ + const char *name; + const BoundingBoxTransformSelctorPtr is_selected; + BoundingBoxTransformUKernelPtr ukernel; +}; + +static const BoundingBoxTransformKernel available_kernels[] = { + {"fp32_neon_boundingboxtransform", + [](const BoundingBoxTransformSelectorData &data) { return data.dt == DataType::F32; }, + REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_boundingboxtransform)}, +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + {"fp16_neon_boundingboxtransform", + [](const BoundingBoxTransformSelectorData &data) { return data.dt == DataType::F16; }, + REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_boundingboxtransform)}, +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +#if defined(ARM_COMPUTE_ENABLE_NEON) + {"qu16_neon_boundingboxtransform", + [](const BoundingBoxTransformSelectorData &data) { return data.dt == DataType::QASYMM16; }, + REGISTER_QSYMM16_NEON(arm_compute::cpu::neon_qu16_boundingboxtransform)}, +#endif //defined(ARM_COMPUTE_ENABLE_NEON) +}; + +/** Micro-kernel selector + * + * @param[in] data Selection data passed to help pick the appropriate micro-kernel + * + * @return A matching micro-kernel else nullptr + */ +const BoundingBoxTransformKernel *get_implementation(const BoundingBoxTransformSelectorData &data) +{ + for (const auto &uk : available_kernels) + { + if (uk.is_selected(data)) + { + return &uk; + } + } + return nullptr; +} + +Status validate_arguments(const ITensorInfo *boxes, + const ITensorInfo *pred_boxes, + const ITensorInfo *deltas, + const BoundingBoxTransformInfo &info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(boxes, pred_boxes, deltas); ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(boxes); @@ -50,7 +109,7 @@ Status validate_arguments(const ITensorInfo *boxes, const ITensorInfo *pred_boxe ARM_COMPUTE_RETURN_ERROR_ON(boxes->num_dimensions() > 2); ARM_COMPUTE_RETURN_ERROR_ON(info.scale() <= 0); - if(boxes->data_type() == DataType::QASYMM16) + if (boxes->data_type() == DataType::QASYMM16) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(deltas, 1, DataType::QASYMM8); const UniformQuantizationInfo deltas_qinfo = deltas->quantization_info().uniform(); @@ -62,12 +121,12 @@ Status validate_arguments(const ITensorInfo *boxes, const ITensorInfo *pred_boxe ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(boxes, deltas); } - if(pred_boxes->total_size() > 0) + if (pred_boxes->total_size() > 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(pred_boxes->tensor_shape(), deltas->tensor_shape()); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(pred_boxes, deltas); ARM_COMPUTE_RETURN_ERROR_ON(pred_boxes->num_dimensions() > 2); - if(pred_boxes->data_type() == DataType::QASYMM16) + if (pred_boxes->data_type() == DataType::QASYMM16) { const UniformQuantizationInfo pred_qinfo = pred_boxes->quantization_info().uniform(); ARM_COMPUTE_RETURN_ERROR_ON(pred_qinfo.scale != 0.125f); @@ -84,13 +143,19 @@ NEBoundingBoxTransformKernel::NEBoundingBoxTransformKernel() { } -void NEBoundingBoxTransformKernel::configure(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, const BoundingBoxTransformInfo &info) +void NEBoundingBoxTransformKernel::configure(const ITensor *boxes, + ITensor *pred_boxes, + const ITensor *deltas, + const BoundingBoxTransformInfo &info) { ARM_COMPUTE_ERROR_ON_NULLPTR(boxes, pred_boxes, deltas); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(boxes->info(), pred_boxes->info(), deltas->info(), info)); // Configure kernel window - auto_init_if_empty(*pred_boxes->info(), deltas->info()->clone()->set_data_type(boxes->info()->data_type()).set_quantization_info(boxes->info()->quantization_info())); + auto_init_if_empty(*pred_boxes->info(), deltas->info() + ->clone() + ->set_data_type(boxes->info()->data_type()) + .set_quantization_info(boxes->info()->quantization_info())); // Set instance variables _boxes = boxes; @@ -106,151 +171,24 @@ void NEBoundingBoxTransformKernel::configure(const ITensor *boxes, ITensor *pred INEKernel::configure(win); } -Status NEBoundingBoxTransformKernel::validate(const ITensorInfo *boxes, const ITensorInfo *pred_boxes, const ITensorInfo *deltas, const BoundingBoxTransformInfo &info) +Status NEBoundingBoxTransformKernel::validate(const ITensorInfo *boxes, + const ITensorInfo *pred_boxes, + const ITensorInfo *deltas, + const BoundingBoxTransformInfo &info) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(boxes, pred_boxes, deltas, info)); return Status{}; } -template <> -void NEBoundingBoxTransformKernel::internal_run<uint16_t>(const Window &window) -{ - const size_t num_classes = _deltas->info()->tensor_shape()[0] >> 2; - const size_t deltas_width = _deltas->info()->tensor_shape()[0]; - const int img_h = std::floor(_bbinfo.img_height() / _bbinfo.scale() + 0.5f); - const int img_w = std::floor(_bbinfo.img_width() / _bbinfo.scale() + 0.5f); - - const auto scale_after = (_bbinfo.apply_scale() ? _bbinfo.scale() : 1.f); - const auto scale_before = _bbinfo.scale(); - const auto offset = (_bbinfo.correct_transform_coords() ? 1.f : 0.f); - - auto pred_ptr = reinterpret_cast<uint16_t *>(_pred_boxes->buffer() + _pred_boxes->info()->offset_first_element_in_bytes()); - auto delta_ptr = reinterpret_cast<uint8_t *>(_deltas->buffer() + _deltas->info()->offset_first_element_in_bytes()); - - const auto boxes_qinfo = _boxes->info()->quantization_info().uniform(); - const auto deltas_qinfo = _deltas->info()->quantization_info().uniform(); - const auto pred_qinfo = _pred_boxes->info()->quantization_info().uniform(); - - Iterator box_it(_boxes, window); - execute_window_loop(window, [&](const Coordinates & id) - { - const auto ptr = reinterpret_cast<uint16_t *>(box_it.ptr()); - const auto b0 = dequantize_qasymm16(*ptr, boxes_qinfo); - const auto b1 = dequantize_qasymm16(*(ptr + 1), boxes_qinfo); - const auto b2 = dequantize_qasymm16(*(ptr + 2), boxes_qinfo); - const auto b3 = dequantize_qasymm16(*(ptr + 3), boxes_qinfo); - const float width = (b2 / scale_before) - (b0 / scale_before) + 1.f; - const float height = (b3 / scale_before) - (b1 / scale_before) + 1.f; - const float ctr_x = (b0 / scale_before) + 0.5f * width; - const float ctr_y = (b1 / scale_before) + 0.5f * height; - for(size_t j = 0; j < num_classes; ++j) - { - // Extract deltas - const size_t delta_id = id.y() * deltas_width + 4u * j; - const float dx = dequantize_qasymm8(delta_ptr[delta_id], deltas_qinfo) / _bbinfo.weights()[0]; - const float dy = dequantize_qasymm8(delta_ptr[delta_id + 1], deltas_qinfo) / _bbinfo.weights()[1]; - float dw = dequantize_qasymm8(delta_ptr[delta_id + 2], deltas_qinfo) / _bbinfo.weights()[2]; - float dh = dequantize_qasymm8(delta_ptr[delta_id + 3], deltas_qinfo) / _bbinfo.weights()[3]; - // Clip dw and dh - dw = std::min(dw, _bbinfo.bbox_xform_clip()); - dh = std::min(dh, _bbinfo.bbox_xform_clip()); - // Determine the predictions - const float pred_ctr_x = dx * width + ctr_x; - const float pred_ctr_y = dy * height + ctr_y; - const float pred_w = std::exp(dw) * width; - const float pred_h = std::exp(dh) * height; - // Store the prediction into the output tensor - pred_ptr[delta_id] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_x - 0.5f * pred_w, 0.f, img_w - 1.f), pred_qinfo); - pred_ptr[delta_id + 1] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_y - 0.5f * pred_h, 0.f, img_h - 1.f), pred_qinfo); - pred_ptr[delta_id + 2] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_x + 0.5f * pred_w - offset, 0.f, img_w - 1.f), pred_qinfo); - pred_ptr[delta_id + 3] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_y + 0.5f * pred_h - offset, 0.f, img_h - 1.f), pred_qinfo); - } - }, - box_it); -} - -template <typename T> -void NEBoundingBoxTransformKernel::internal_run(const Window &window) -{ - const size_t num_classes = _deltas->info()->tensor_shape()[0] >> 2; - const size_t deltas_width = _deltas->info()->tensor_shape()[0]; - const int img_h = std::floor(_bbinfo.img_height() / _bbinfo.scale() + 0.5f); - const int img_w = std::floor(_bbinfo.img_width() / _bbinfo.scale() + 0.5f); - - const auto scale_after = (_bbinfo.apply_scale() ? T(_bbinfo.scale()) : T(1)); - const auto scale_before = T(_bbinfo.scale()); - ARM_COMPUTE_ERROR_ON(scale_before <= 0); - const auto offset = (_bbinfo.correct_transform_coords() ? T(1.f) : T(0.f)); - - auto pred_ptr = reinterpret_cast<T *>(_pred_boxes->buffer() + _pred_boxes->info()->offset_first_element_in_bytes()); - auto delta_ptr = reinterpret_cast<T *>(_deltas->buffer() + _deltas->info()->offset_first_element_in_bytes()); - - Iterator box_it(_boxes, window); - execute_window_loop(window, [&](const Coordinates & id) - { - const auto ptr = reinterpret_cast<T *>(box_it.ptr()); - const auto b0 = *ptr; - const auto b1 = *(ptr + 1); - const auto b2 = *(ptr + 2); - const auto b3 = *(ptr + 3); - const T width = (b2 / scale_before) - (b0 / scale_before) + T(1.f); - const T height = (b3 / scale_before) - (b1 / scale_before) + T(1.f); - const T ctr_x = (b0 / scale_before) + T(0.5f) * width; - const T ctr_y = (b1 / scale_before) + T(0.5f) * height; - for(size_t j = 0; j < num_classes; ++j) - { - // Extract deltas - const size_t delta_id = id.y() * deltas_width + 4u * j; - const T dx = delta_ptr[delta_id] / T(_bbinfo.weights()[0]); - const T dy = delta_ptr[delta_id + 1] / T(_bbinfo.weights()[1]); - T dw = delta_ptr[delta_id + 2] / T(_bbinfo.weights()[2]); - T dh = delta_ptr[delta_id + 3] / T(_bbinfo.weights()[3]); - // Clip dw and dh - dw = std::min(dw, T(_bbinfo.bbox_xform_clip())); - dh = std::min(dh, T(_bbinfo.bbox_xform_clip())); - // Determine the predictions - const T pred_ctr_x = dx * width + ctr_x; - const T pred_ctr_y = dy * height + ctr_y; - const T pred_w = std::exp(dw) * width; - const T pred_h = std::exp(dh) * height; - // Store the prediction into the output tensor - pred_ptr[delta_id] = scale_after * utility::clamp<T>(pred_ctr_x - T(0.5f) * pred_w, T(0), T(img_w - 1)); - pred_ptr[delta_id + 1] = scale_after * utility::clamp<T>(pred_ctr_y - T(0.5f) * pred_h, T(0), T(img_h - 1)); - pred_ptr[delta_id + 2] = scale_after * utility::clamp<T>(pred_ctr_x + T(0.5f) * pred_w - offset, T(0), T(img_w - 1)); - pred_ptr[delta_id + 3] = scale_after * utility::clamp<T>(pred_ctr_y + T(0.5f) * pred_h - offset, T(0), T(img_h - 1)); - } - }, - box_it); -} - void NEBoundingBoxTransformKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - switch(_boxes->info()->data_type()) - { - case DataType::F32: - { - internal_run<float>(window); - break; - } - case DataType::QASYMM16: - { - internal_run<uint16_t>(window); - break; - } -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - case DataType::F16: - { - internal_run<float16_t>(window); - break; - } -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - default: - { - ARM_COMPUTE_ERROR("Data type not supported"); - } - } + + const auto *uk = get_implementation(BoundingBoxTransformSelectorData{_boxes->info()->data_type()}); + ARM_COMPUTE_ERROR_ON(uk == nullptr || uk->ukernel == nullptr); + + uk->ukernel(_boxes, _pred_boxes, _deltas, _bbinfo, window); } } // namespace arm_compute |