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Diffstat (limited to 'src/cpu/kernels/roialign/generic/neon/impl.h')
| -rw-r--r-- | src/cpu/kernels/roialign/generic/neon/impl.h | 380 |
1 files changed, 380 insertions, 0 deletions
diff --git a/src/cpu/kernels/roialign/generic/neon/impl.h b/src/cpu/kernels/roialign/generic/neon/impl.h new file mode 100644 index 0000000000..db2f67705d --- /dev/null +++ b/src/cpu/kernels/roialign/generic/neon/impl.h @@ -0,0 +1,380 @@ +/* + * Copyright (c) 2019-2023 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef SRC_CORE_SVE_KERNELS_BOUNDINGBOXTRANFORM_IMPL_H +#define SRC_CORE_SVE_KERNELS_BOUNDINGBOXTRANFORM_IMPL_H +#include "arm_compute/core/CPP/CPPTypes.h" +#include "arm_compute/core/Helpers.h" + +namespace arm_compute +{ +class ITensor; +class Window; +namespace cpu +{ +/** Average pooling over an aligned window */ +template <typename input_data_type> +inline input_data_type roi_align_1x1(const ITensor *input, + unsigned int roi_batch, + float region_start_x, + float bin_size_x, + int grid_size_x, + float region_end_x, + float region_start_y, + float bin_size_y, + int grid_size_y, + float region_end_y, + int pz) +{ + if ((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) + { + return input_data_type(0); + } + else + { + const DataLayout data_layout = input->info()->data_layout(); + float avg = 0; + // Iterate through the aligned pooling region + for (int iy = 0; iy < grid_size_y; ++iy) + { + for (int ix = 0; ix < grid_size_x; ++ix) + { + // Align the window in the middle of every bin + float y = region_start_y + (iy + 0.5) * bin_size_y / float(grid_size_y); + float x = region_start_x + (ix + 0.5) * bin_size_x / float(grid_size_x); + + // Interpolation in the [0,0] [0,1] [1,0] [1,1] square + const int y_low = y; + const int x_low = x; + const int y_high = y_low + 1; + const int x_high = x_low + 1; + + const float ly = y - y_low; + const float lx = x - x_low; + const float hy = 1. - ly; + const float hx = 1. - lx; + + const float w1 = hy * hx; + const float w2 = hy * lx; + const float w3 = ly * hx; + const float w4 = ly * lx; + if (data_layout == DataLayout::NCHW) + { + const auto data1 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))); + const auto data2 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))); + const auto data3 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))); + const auto data4 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + else + { + const auto data1 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))); + const auto data2 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))); + const auto data3 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))); + const auto data4 = *reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + } + } + + avg /= grid_size_x * grid_size_y; + return input_data_type(avg); + } +} + +/** Average pooling over an aligned window */ +template <typename input_data_type> +inline input_data_type roi_align_1x1_qasymm8(const ITensor *input, + unsigned int roi_batch, + float region_start_x, + float bin_size_x, + int grid_size_x, + float region_end_x, + float region_start_y, + float bin_size_y, + int grid_size_y, + float region_end_y, + int pz, + const QuantizationInfo &out_qinfo) +{ + if ((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) + { + return input_data_type(out_qinfo.uniform().offset); + } + else + { + float avg = 0; + const UniformQuantizationInfo input_qinfo = input->info()->quantization_info().uniform(); + const bool is_qasymm_signed = is_data_type_quantized_asymmetric_signed(input->info()->data_type()); + const DataLayout data_layout = input->info()->data_layout(); + + // Iterate through the aligned pooling region + for (int iy = 0; iy < grid_size_y; ++iy) + { + for (int ix = 0; ix < grid_size_x; ++ix) + { + // Align the window in the middle of every bin + float y = region_start_y + (iy + 0.5) * bin_size_y / float(grid_size_y); + float x = region_start_x + (ix + 0.5) * bin_size_x / float(grid_size_x); + + // Interpolation in the [0,0] [0,1] [1,0] [1,1] square + const int y_low = y; + const int x_low = x; + const int y_high = y_low + 1; + const int x_high = x_low + 1; + + const float ly = y - y_low; + const float lx = x - x_low; + const float hy = 1. - ly; + const float hx = 1. - lx; + + const float w1 = hy * hx; + const float w2 = hy * lx; + const float w3 = ly * hx; + const float w4 = ly * lx; + + if (data_layout == DataLayout::NCHW) + { + if (is_qasymm_signed) + { + float data1 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(x_low, y_low, pz, roi_batch))), + input_qinfo); + float data2 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(x_high, y_low, pz, roi_batch))), + input_qinfo); + float data3 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(x_low, y_high, pz, roi_batch))), + input_qinfo); + float data4 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(x_high, y_high, pz, roi_batch))), + input_qinfo); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + else + { + float data1 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))), + input_qinfo); + float data2 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))), + input_qinfo); + float data3 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))), + input_qinfo); + float data4 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))), + input_qinfo); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + } + else + { + if (is_qasymm_signed) + { + const auto data1 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(pz, x_low, y_low, roi_batch))), + input_qinfo); + const auto data2 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(pz, x_high, y_low, roi_batch))), + input_qinfo); + const auto data3 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(pz, x_low, y_high, roi_batch))), + input_qinfo); + const auto data4 = + dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element( + Coordinates(pz, x_high, y_high, roi_batch))), + input_qinfo); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + else + { + const auto data1 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))), + input_qinfo); + const auto data2 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))), + input_qinfo); + const auto data3 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))), + input_qinfo); + const auto data4 = + dequantize_qasymm8(*reinterpret_cast<const input_data_type *>( + input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))), + input_qinfo); + avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4; + } + } + } + } + + avg /= grid_size_x * grid_size_y; + + input_data_type res = 0; + if (is_qasymm_signed) + { + res = quantize_qasymm8_signed(avg, out_qinfo); + } + else + { + res = quantize_qasymm8(avg, out_qinfo); + } + return res; + } +} +inline float compute_region_coordinate(int p, float bin_size, float roi_anchor, float max_value) +{ + const float region_start = p * bin_size + roi_anchor; + return utility::clamp(region_start, 0.0f, max_value); +} + +template <typename input_data_type, typename roi_data_type> +void roi_align(const ITensor *input, + ITensor *output, + const ITensor *rois, + ROIPoolingLayerInfo pool_info, + const Window &window, + const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + + const DataLayout data_layout = input->info()->data_layout(); + const size_t values_per_roi = rois->info()->dimension(0); + + const int roi_list_start = window.x().start(); + const int roi_list_end = window.x().end(); + + const unsigned int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const unsigned int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + const unsigned int idx_depth = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); + + const int input_width = input->info()->dimension(idx_width); + const int input_height = input->info()->dimension(idx_height); + const int input_chanels = input->info()->dimension(idx_depth); + const int pooled_w = pool_info.pooled_width(); + const int pooled_h = pool_info.pooled_height(); + + const DataType data_type = input->info()->data_type(); + const bool is_qasymm = is_data_type_quantized_asymmetric(data_type); + + const auto *rois_ptr = reinterpret_cast<const roi_data_type *>(rois->buffer()); + const QuantizationInfo &rois_qinfo = rois->info()->quantization_info(); + 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]; + + roi_data_type qx1 = rois_ptr[values_per_roi * roi_indx + 1]; + roi_data_type qy1 = rois_ptr[values_per_roi * roi_indx + 2]; + roi_data_type qx2 = rois_ptr[values_per_roi * roi_indx + 3]; + roi_data_type qy2 = rois_ptr[values_per_roi * roi_indx + 4]; + float x1(qx1); + float x2(qx2); + float y1(qy1); + float y2(qy2); + if (is_qasymm) + { + x1 = dequantize_qasymm16(qx1, rois_qinfo); + x2 = dequantize_qasymm16(qx2, rois_qinfo); + y1 = dequantize_qasymm16(qy1, rois_qinfo); + y2 = dequantize_qasymm16(qy2, rois_qinfo); + } + const float roi_anchor_x = x1 * pool_info.spatial_scale(); + const float roi_anchor_y = y1 * pool_info.spatial_scale(); + const float roi_dims_x = std::max((x2 - x1) * pool_info.spatial_scale(), 1.0f); + const float roi_dims_y = std::max((y2 - y1) * pool_info.spatial_scale(), 1.0f); + float bin_size_x = roi_dims_x / pool_info.pooled_width(); + float bin_size_y = roi_dims_y / pool_info.pooled_height(); + + // Iterate through all feature maps + for (int ch = 0; ch < input_chanels; ++ch) + { + // Iterate through all output pixels + for (int py = 0; py < pooled_h; ++py) + { + for (int px = 0; px < pooled_w; ++px) + { + const float region_start_x = compute_region_coordinate(px, bin_size_x, roi_anchor_x, input_width); + const float region_start_y = compute_region_coordinate(py, bin_size_y, roi_anchor_y, input_height); + const float region_end_x = compute_region_coordinate(px + 1, bin_size_x, roi_anchor_x, input_width); + const float region_end_y = + compute_region_coordinate(py + 1, bin_size_y, roi_anchor_y, input_height); + const int roi_bin_grid_x = + (pool_info.sampling_ratio() > 0) ? pool_info.sampling_ratio() : int(ceil(bin_size_x)); + const int roi_bin_grid_y = + (pool_info.sampling_ratio() > 0) ? pool_info.sampling_ratio() : int(ceil(bin_size_y)); + input_data_type out_val(0); + if (is_qasymm) + { + out_val = roi_align_1x1_qasymm8<input_data_type>( + input, roi_batch, region_start_x, bin_size_x, roi_bin_grid_x, region_end_x, region_start_y, + bin_size_y, roi_bin_grid_y, region_end_y, ch, output->info()->quantization_info()); + } + else + { + out_val = roi_align_1x1<input_data_type>(input, roi_batch, region_start_x, bin_size_x, + roi_bin_grid_x, region_end_x, region_start_y, + bin_size_y, roi_bin_grid_y, region_end_y, ch); + } + + if (data_layout == DataLayout::NCHW) + { + auto out_ptr = reinterpret_cast<input_data_type *>( + output->ptr_to_element(Coordinates(px, py, ch, roi_indx))); + *out_ptr = out_val; + } + else + { + auto out_ptr = reinterpret_cast<input_data_type *>( + output->ptr_to_element(Coordinates(ch, px, py, roi_indx))); + *out_ptr = out_val; + } + } + } + } + } +} +} // namespace cpu +} // namespace arm_compute +#endif //define SRC_CORE_SVE_KERNELS_BOUNDINGBOXTRANFORM_IMPL_H |