Changes in roi_align to enable fp16 in armv8a multi_isa builds
* Code guarded with __ARM_FEATURE_FP16_VECTOR_ARITHMETIC needs
to be moved to an fp16.cpp file to allow compilation with
-march=armv8.2-a+fp16
* fp16.cpp needs to use the template roi_align() so it had to be moved from
impl.cpp to impl.h
* Removed the file src/cpu/kernels/roialign/generic/neon/impl.cpp
* Partially resolves MLCE-1102
Change-Id: If78371479042725723cea6f6c65aac76d68a1c1d
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10213
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/Android.bp b/Android.bp
index 487c818..7f5d05e 100644
--- a/Android.bp
+++ b/Android.bp
@@ -563,7 +563,6 @@
"src/cpu/kernels/range/generic/neon/integer.cpp",
"src/cpu/kernels/roialign/generic/neon/fp16.cpp",
"src/cpu/kernels/roialign/generic/neon/fp32.cpp",
- "src/cpu/kernels/roialign/generic/neon/impl.cpp",
"src/cpu/kernels/roialign/generic/neon/qasymm8.cpp",
"src/cpu/kernels/roialign/generic/neon/qasymm8_signed.cpp",
"src/cpu/kernels/scale/neon/fp16.cpp",
diff --git a/filelist.json b/filelist.json
index 4c110f7..2b7793b 100644
--- a/filelist.json
+++ b/filelist.json
@@ -2118,7 +2118,6 @@
"src/runtime/NEON/functions/NEROIAlignLayer.cpp"
],
"neon":{
- "common":["src/cpu/kernels/roialign/generic/neon/impl.cpp"],
"fp32":["src/cpu/kernels/roialign/generic/neon/fp32.cpp"],
"fp16":["src/cpu/kernels/roialign/generic/neon/fp16.cpp"],
"qasymm8":["src/cpu/kernels/roialign/generic/neon/qasymm8.cpp"],
diff --git a/src/BUILD.bazel b/src/BUILD.bazel
index dbedffa..7519115 100644
--- a/src/BUILD.bazel
+++ b/src/BUILD.bazel
@@ -811,7 +811,6 @@
"cpu/kernels/range/generic/neon/integer.cpp",
"cpu/kernels/roialign/generic/neon/fp16.cpp",
"cpu/kernels/roialign/generic/neon/fp32.cpp",
- "cpu/kernels/roialign/generic/neon/impl.cpp",
"cpu/kernels/roialign/generic/neon/qasymm8.cpp",
"cpu/kernels/roialign/generic/neon/qasymm8_signed.cpp",
"cpu/kernels/scale/neon/fp16.cpp",
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
index 2a59209..62bf4f0 100644
--- a/src/CMakeLists.txt
+++ b/src/CMakeLists.txt
@@ -803,7 +803,6 @@
cpu/kernels/range/generic/neon/integer.cpp
cpu/kernels/roialign/generic/neon/fp16.cpp
cpu/kernels/roialign/generic/neon/fp32.cpp
- cpu/kernels/roialign/generic/neon/impl.cpp
cpu/kernels/roialign/generic/neon/qasymm8.cpp
cpu/kernels/roialign/generic/neon/qasymm8_signed.cpp
cpu/kernels/scale/neon/fp16.cpp
diff --git a/src/cpu/kernels/roialign/generic/neon/impl.cpp b/src/cpu/kernels/roialign/generic/neon/impl.cpp
deleted file mode 100644
index 630d649..0000000
--- a/src/cpu/kernels/roialign/generic/neon/impl.cpp
+++ /dev/null
@@ -1,319 +0,0 @@
-/*
- * 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.
- */
-#include "src/cpu/kernels/roialign/generic/neon/impl.h"
-
-#include "src/core/NEON/INEKernel.h"
-#include "src/cpu/CpuTypes.h"
-
-namespace arm_compute
-{
-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;
- }
- }
- }
- }
- }
-}
-template void roi_align<float, float>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
-template void roi_align<uint8_t, uint16_t>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
-template void roi_align<int8_t, uint16_t>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
-#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-template void roi_align<float16_t, float16_t>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
-#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
-} // namespace cpu
-} // namespace arm_compute
diff --git a/src/cpu/kernels/roialign/generic/neon/impl.h b/src/cpu/kernels/roialign/generic/neon/impl.h
index ff96b8e..e5e6043 100644
--- a/src/cpu/kernels/roialign/generic/neon/impl.h
+++ b/src/cpu/kernels/roialign/generic/neon/impl.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2022 Arm Limited.
+ * Copyright (c) 2019-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -32,9 +32,285 @@
class Window;
namespace cpu
{
-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);
+/** 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