diff options
Diffstat (limited to 'src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp | 85 |
1 files changed, 58 insertions, 27 deletions
diff --git a/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp b/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp index 400e8291d6..1a3810fb56 100644 --- a/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp +++ b/src/core/NEON/kernels/NEROIPoolingLayerKernel.cpp @@ -22,9 +22,11 @@ * SOFTWARE. */ #include "src/core/NEON/kernels/NEROIPoolingLayerKernel.h" + #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" + #include "src/core/CPP/Validate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" @@ -36,7 +38,10 @@ namespace arm_compute { namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, const ITensorInfo *output, const ROIPoolingLayerInfo &pool_info) +Status validate_arguments(const ITensorInfo *input, + const ITensorInfo *rois, + const ITensorInfo *output, + const ROIPoolingLayerInfo &pool_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, rois); @@ -47,10 +52,11 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, con ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F32, DataType::QASYMM8); ARM_COMPUTE_RETURN_ERROR_ON((pool_info.pooled_width() == 0) || (pool_info.pooled_height() == 0)); - if(output->total_size() != 0) + if (output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) || (output->dimension(1) != pool_info.pooled_height())); + ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) != pool_info.pooled_width()) || + (output->dimension(1) != pool_info.pooled_height())); ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != output->dimension(2)); ARM_COMPUTE_RETURN_ERROR_ON(rois->dimension(1) != output->dimension(3)); } @@ -73,19 +79,28 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *rois, con * @param[in] roi_indx Index of image of coordinate in output Tensor to store value */ template <typename T> -void template_eval(const ITensor *input, const ITensor *output, int region_start_x, int region_start_y, - int region_end_x, int region_end_y, int fm, int px, int py, int roi_batch, int roi_indx) +void template_eval(const ITensor *input, + const ITensor *output, + int region_start_x, + int region_start_y, + int region_end_x, + int region_end_y, + int fm, + int px, + int py, + int roi_batch, + int roi_indx) { - if((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) + if ((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) { *reinterpret_cast<T *>(output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = 0; } else { T curr_max = std::numeric_limits<T>::lowest(); // Min value of typename T - for(int j = region_start_y; j < region_end_y; ++j) + for (int j = region_start_y; j < region_end_y; ++j) { - for(int i = region_start_x; i < region_end_x; ++i) + for (int i = region_start_x; i < region_end_x; ++i) { const auto val = *reinterpret_cast<const T *>(input->ptr_to_element(Coordinates(i, j, fm, roi_batch))); curr_max = std::max(val, curr_max); @@ -93,11 +108,13 @@ void template_eval(const ITensor *input, const ITensor *output, int region_start } // if quantized datatype, requantize then store in output tensor - if(is_data_type_quantized(input->info()->data_type())) + if (is_data_type_quantized(input->info()->data_type())) { // covert qasymm to new output quantization scale and offset - UniformQuantizationInfo uqinfo = compute_requantization_scale_offset(input->info()->quantization_info().uniform(), output->info()->quantization_info().uniform()); - *reinterpret_cast<T *>(output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = quantize_qasymm8(curr_max, uqinfo); + UniformQuantizationInfo uqinfo = compute_requantization_scale_offset( + input->info()->quantization_info().uniform(), output->info()->quantization_info().uniform()); + *reinterpret_cast<T *>(output->ptr_to_element(Coordinates(px, py, fm, roi_indx))) = + quantize_qasymm8(curr_max, uqinfo); } else { @@ -112,13 +129,19 @@ NEROIPoolingLayerKernel::NEROIPoolingLayerKernel() { } -Status NEROIPoolingLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *rois, const ITensorInfo *output, const ROIPoolingLayerInfo &pool_info) +Status NEROIPoolingLayerKernel::validate(const ITensorInfo *input, + const ITensorInfo *rois, + const ITensorInfo *output, + const ROIPoolingLayerInfo &pool_info) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, rois, output, pool_info)); return Status{}; } -void NEROIPoolingLayerKernel::configure(const ITensor *input, const ITensor *rois, const ITensor *output, const ROIPoolingLayerInfo &pool_info) +void NEROIPoolingLayerKernel::configure(const ITensor *input, + const ITensor *rois, + const ITensor *output, + const ROIPoolingLayerInfo &pool_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, rois); @@ -126,12 +149,15 @@ void NEROIPoolingLayerKernel::configure(const ITensor *input, const ITensor *roi ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), rois->info(), output->info(), pool_info)); // Output auto initialization if not yet initialized - TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), rois->info()->dimension(1)); + TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), input->info()->dimension(2), + rois->info()->dimension(1)); - auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), output->info()->quantization_info()); + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), + output->info()->quantization_info()); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || (output->info()->dimension(1) != pool_info.pooled_height())); + ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) != pool_info.pooled_width()) || + (output->info()->dimension(1) != pool_info.pooled_height())); // Set instance variables _input = input; @@ -167,7 +193,7 @@ void NEROIPoolingLayerKernel::run(const Window &window, const ThreadInfo &info) const auto *rois_ptr = reinterpret_cast<const uint16_t *>(_rois->buffer()); const auto data_type = _input->info()->data_type(); - for(int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx) + for (int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx) { const unsigned int roi_batch = rois_ptr[values_per_roi * roi_indx]; const auto x1 = rois_ptr[values_per_roi * roi_indx + 1]; @@ -182,30 +208,35 @@ void NEROIPoolingLayerKernel::run(const Window &window, const ThreadInfo &info) const int roi_height = std::max(support::cpp11::round((y2 - y1) * spatial_scale), 1.f); // Iterate through all feature maps - for(int fm = 0; fm < fms; ++fm) + for (int fm = 0; fm < fms; ++fm) { // Iterate through all output pixels - for(int py = 0; py < pooled_h; ++py) + for (int py = 0; py < pooled_h; ++py) { - for(int px = 0; px < pooled_w; ++px) + for (int px = 0; px < pooled_w; ++px) { auto region_start_x = static_cast<int>(std::floor((static_cast<float>(px) / pooled_w) * roi_width)); - auto region_end_x = static_cast<int>(std::floor((static_cast<float>(px + 1) / pooled_w) * roi_width)); - auto region_start_y = static_cast<int>(std::floor((static_cast<float>(py) / pooled_h) * roi_height)); - auto region_end_y = static_cast<int>(std::floor((static_cast<float>(py + 1) / pooled_h) * roi_height)); + auto region_end_x = + static_cast<int>(std::floor((static_cast<float>(px + 1) / pooled_w) * roi_width)); + auto region_start_y = + static_cast<int>(std::floor((static_cast<float>(py) / pooled_h) * roi_height)); + auto region_end_y = + static_cast<int>(std::floor((static_cast<float>(py + 1) / pooled_h) * roi_height)); region_start_x = std::min(std::max(region_start_x + roi_anchor_x, 0), width); region_end_x = std::min(std::max(region_end_x + roi_anchor_x, 0), width); region_start_y = std::min(std::max(region_start_y + roi_anchor_y, 0), height); region_end_y = std::min(std::max(region_end_y + roi_anchor_y, 0), height); - switch(data_type) + switch (data_type) { case DataType::F32: - template_eval<float>(_input, _output, region_start_x, region_start_y, region_end_x, region_end_y, fm, px, py, roi_batch, roi_indx); + template_eval<float>(_input, _output, region_start_x, region_start_y, region_end_x, + region_end_y, fm, px, py, roi_batch, roi_indx); break; case DataType::QASYMM8: - template_eval<qasymm8_t>(_input, _output, region_start_x, region_start_y, region_end_x, region_end_y, fm, px, py, roi_batch, roi_indx); + template_eval<qasymm8_t>(_input, _output, region_start_x, region_start_y, region_end_x, + region_end_y, fm, px, py, roi_batch, roi_indx); break; default: ARM_COMPUTE_ERROR("DataType not Supported"); @@ -216,4 +247,4 @@ void NEROIPoolingLayerKernel::run(const Window &window, const ThreadInfo &info) } } } -} // namespace arm_compute
\ No newline at end of file +} // namespace arm_compute |