From 7075fe2c5ee6f7cfe7cfd9454d905235e70b9ac4 Mon Sep 17 00:00:00 2001 From: Adnan AlSinan Date: Mon, 5 Jul 2021 13:12:52 +0100 Subject: Reorganize the kernels into nhwc, nchw and common folders The Following kernels have been split into nchw/nhwc kernels files: - batchnormalization_layer - batch_to_space - channel_shuffle - depth_to_space - dequantization_layer - im2col - normalization_layer - normalize_planar_yuv_layer - normalize_planar_yuv_layer_quantized - pooling_layer - pooling_layer_quantized - remap - reorg_layer - scale - scale_quantized - space_to_batch - space_to_depth - upsample_layer - winograd_filter_transform - winograd_input_transform - winograd_output_transform The following kernels have been moved to nchw folder: - direct_convolution1x1 - direct_convolution3x3 - direct_convolution5x5 - direct_convolution_quantized - prior_box_layer The following kernels have been moved to nhwc folder: - direct_convolution - dwc_native_fp_nhwc - dwc_native_quantized_nhwc The following kernels have been removed: - sobel_filter While the rest kerenls have been moved to the common folder. Partially resolves COMPMID-4453 Signed-off-by: Adnan AlSinan Change-Id: Ic327ac935687ec351c610c65a3c6357f364a5a58 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5919 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins --- src/core/CL/cl_kernels/common/roi_pooling_layer.cl | 196 +++++++++++++++++++++ 1 file changed, 196 insertions(+) create mode 100644 src/core/CL/cl_kernels/common/roi_pooling_layer.cl (limited to 'src/core/CL/cl_kernels/common/roi_pooling_layer.cl') diff --git a/src/core/CL/cl_kernels/common/roi_pooling_layer.cl b/src/core/CL/cl_kernels/common/roi_pooling_layer.cl new file mode 100644 index 0000000000..6899b952e0 --- /dev/null +++ b/src/core/CL/cl_kernels/common/roi_pooling_layer.cl @@ -0,0 +1,196 @@ +/* + * Copyright (c) 2017-2021 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 "helpers.h" +#include "helpers_asymm.h" + +#if DATA_SIZE == 32 +#define VEC_SIZE 4 +#define VEC_MAX vec4_max +#elif DATA_SIZE == 16 +#define VEC_SIZE 8 +#define VEC_MAX vec8_max +#elif DATA_SIZE == 8 +#define VEC_SIZE 16 +#define VEC_MAX vec16_max +#else /* DATA_SIZE not equals 8, 16, 32 */ +#error "Unsupported data size" +#endif /* DATA_SIZE == 32 */ + +// Define whether to use max (Quantized datatype) or fmax (Float) functions +#if defined(OFFSET_OUT) && defined(SCALE_OUT) +#define MAX(x, y) max(x, y) +#else // !(defined(OFFSET_OUT) && defined(SCALE_OUT) +#define MAX(x, y) fmax(x, y) +#endif // defined(OFFSET_OUT) && defined(SCALE_OUT) + +inline DATA_TYPE vec4_max(VEC_DATA_TYPE(DATA_TYPE, 4) vec) +{ + VEC_DATA_TYPE(DATA_TYPE, 2) + temp = MAX(vec.lo, vec.hi); + return MAX(temp.x, temp.y); +} + +inline DATA_TYPE vec8_max(VEC_DATA_TYPE(DATA_TYPE, 8) vec) +{ + VEC_DATA_TYPE(DATA_TYPE, 4) + temp = MAX(vec.lo, vec.hi); + return vec4_max(temp); +} + +inline DATA_TYPE vec16_max(VEC_DATA_TYPE(DATA_TYPE, 16) vec) +{ + VEC_DATA_TYPE(DATA_TYPE, 8) + temp = MAX(vec.lo, vec.hi); + return vec8_max(temp); +} + +/** Performs a roi pooling on a single output pixel. + * + * @param[in] input Pointer to input Tensor3D struct. + * @param[in] region_start_x Start x index projected onto the input tensor. + * @param[in] region_end_x End x index projected onto the input tensor. + * @param[in] region_start_y Start y index projected onto the input tensor. + * @param[in] region_end_y End y index projected onto the input tensor. + * @param[in] pz z index of the input tensor. + * + * @return A max pooled value from the region specified in the input tensor. + */ +inline DATA_TYPE roi_pool_1x1(const Tensor3D *input, int region_start_x, int region_end_x, int region_start_y, int region_end_y, int pz) +{ + // Iterate through the pooling region + if((region_end_x <= region_start_x) || (region_end_y <= region_start_y)) + { + return (DATA_TYPE)0; + } + else + { + int num_iter = (int)((region_end_x - region_start_x) / VEC_SIZE); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + curr_max = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))(MIN_VALUE); + + for(int j = region_start_y; j < region_end_y; ++j) + { + int i = region_start_x; + for(; i < region_start_x + num_iter * VEC_SIZE; i += VEC_SIZE) + { + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + val = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(input, i, j, pz)); + curr_max = MAX(val, curr_max); + } + for(; i < region_end_x; ++i) + { + DATA_TYPE val = *(__global DATA_TYPE *)tensor3D_offset(input, i, j, pz); + curr_max = MAX(curr_max, val); + } + } + + const DATA_TYPE temp = (DATA_TYPE)VEC_MAX(curr_max); + +#if defined(OFFSET_OUT) && defined(SCALE_OUT) + return QUANTIZE(temp, OFFSET_OUT, SCALE_OUT, DATA_TYPE, 1); +#endif /* if quantized, requantize and return */ + + return temp; + } +} + +/** Performs a roi pooling function. + * + * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32, QASYMM8; + * @note Datasize must be passed using -DDATA_SIZE e.g. -DDATA_SIZE=32; + * @note Input dimensions must be passed using -DMAX_DIM_X, -DMAX_DIM_Y and -DMAX_DIM_Z; + * @note Pooled region dimensions must be passed using -DPOOLED_DIM_X and -DPOOLED_DIM_Y; + * @note Spatial scale must be passed using -DSPATIAL_SCALE; + * + * @param[in] input_ptr Pointer to the source image. Supported data types: F16, F32, QASYMM8 + * @param[in] input_stride_x Stride of the source image in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the pooled region of the source image as specifed by ROI + * @param[in] rois_ptr Pointer to the ROIs tensor. Layout: { batch_index, x1, y1, x2, y2 }. Supported data types: same as @p input_ptr + * @param[in] rois_stride_x Stride of the ROIs tensor in X dimension (in bytes) + * @param[in] rois_step_x Step of the ROIs tensor in X dimension (in bytes) + * @param[in] rois_stride_y Stride of the ROIs tensor in Y dimension (in bytes) + * @param[in] rois_step_y Step of the ROIs tensor in Y dimension (in bytes) + * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the ROIs tensor + * @param[out] output_ptr Pointer to the destination image. Supported data types: same as input + * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes) + * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes) + * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image + * @param[in] input_stride_w Stride of the source image in W dimension (in bytes) + * @param[in] output_stride_w Stride of the destination image in W dimension (in bytes) + */ +__kernel void roi_pooling_layer( + TENSOR3D_DECLARATION(input), + IMAGE_DECLARATION(rois), + TENSOR3D_DECLARATION(output), + unsigned int input_stride_w, unsigned int output_stride_w) +{ + // Get pixels pointer + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(input); + Image rois = CONVERT_TO_IMAGE_STRUCT_NO_STEP(rois); + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output); + + const int px = get_global_id(0); + const int py = get_global_id(1); + const int pw = get_global_id(2); + + // Load roi parameters + // roi is laid out as follows { batch_index, x1, y1, x2, y2 } + const ushort roi_batch = (ushort) * ((__global ushort *)offset(&rois, 0, pw)); + const VEC_DATA_TYPE(ushort, 4) + roi = vload4(0, (__global ushort *)offset(&rois, 1, pw)); + const int2 roi_anchor = convert_int2_sat(round(convert_float2(roi.s01) * (float)SPATIAL_SCALE)); + const int2 roi_dims = convert_int2_sat(fmax(round(convert_float2(roi.s23 - roi.s01) * (float)SPATIAL_SCALE), 1.f)); + + // Calculate pooled region start and end + const float2 spatial_indx = (float2)(px, py); + const float2 pooled_dims = (float2)(POOLED_DIM_X, POOLED_DIM_Y); + const int2 max_spatial_dims = (int2)(MAX_DIM_X, MAX_DIM_Y); + int2 region_start = convert_int2_sat(floor(spatial_indx / pooled_dims * convert_float2(roi_dims))) + roi_anchor; + int2 region_end = convert_int2_sat(floor((spatial_indx + 1) / pooled_dims * convert_float2(roi_dims))) + roi_anchor; + + region_start = clamp(region_start, 0, max_spatial_dims); + region_end = clamp(region_end, 0, max_spatial_dims); + + // Move input and output pointer across the fourth dimension + input.ptr += roi_batch * input_stride_w; + output.ptr += pw * output_stride_w; + + for(int pz = 0; pz < MAX_DIM_Z; ++pz) + { + *(__global DATA_TYPE *)tensor3D_offset(&output, px, py, pz) = (__global DATA_TYPE)roi_pool_1x1(&input, + region_start.x, + region_end.x, + region_start.y, + region_end.y, pz); + } +} -- cgit v1.2.1