/* * Copyright (c) 2017 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" #ifdef FIXED_POINT_POSITION #include "fixed_point.h" #if defined(POOL_AVG) #define POOL_OP(x, y) add_sat(x, y) #else /* POOL_AVG */ #define POOL_OP(x, y) (max((x), (y))) #endif /* POOL_AVG */ #define DIV_OP1(x, y) DIV_SAT_OP_EXPAND((x), y, DATA_TYPE, FIXED_POINT_POSITION) #define DIV_OP(x, y) DIV_OP1(x, y << FIXED_POINT_POSITION) #else /* FIXED_POINT_POSITION */ #if defined(POOL_AVG) #define POOL_OP(x, y) ((x) + (y)) #else /* POOL_AVG */ #define POOL_OP(x, y) (fmax((x), (y))) #endif /* POOL_AVG */ #define DIV_OP(x, y) (x * (1.f / y)) #endif /* FIXED_POINT_POSITION */ #if STRIDE_X == 1 #define POOLING3x3(res, input, output) POOLING3x3_STRIDE1(res, input, output) #elif STRIDE_X == 2 /* STRIDE_X == 1 */ #define POOLING3x3(res, input, output) POOLING3x3_STRIDE2(res, input, output) #elif STRIDE_X == 3 /* STRIDE_X not equals 1 or 2 */ #define POOLING3x3(res, input, output) POOLING3x3_STRIDE3(res, input, output) #endif /* STRIDE_X == 3 */ #define POOLING3x3_STRIDE1(res, input, output) \ ({ \ VEC_DATA_TYPE(DATA_TYPE, 4) \ data00 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); \ VEC_DATA_TYPE(DATA_TYPE, 2) \ data01 = vload2(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0) + 4); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ data10 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); \ VEC_DATA_TYPE(DATA_TYPE, 2) \ data11 = vload2(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0) + 4); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ data20 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); \ VEC_DATA_TYPE(DATA_TYPE, 2) \ data21 = vload2(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0) + 4); \ \ VEC_DATA_TYPE(DATA_TYPE, 8) \ values00 = (VEC_DATA_TYPE(DATA_TYPE, 8))(data00.s01212323); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ values01 = (VEC_DATA_TYPE(DATA_TYPE, 4))(data01.s0, data00.s3, data01.s01); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ values10 = (VEC_DATA_TYPE(DATA_TYPE, 8))(data10.s01212323); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ values11 = (VEC_DATA_TYPE(DATA_TYPE, 4))(data11.s0, data10.s3, data11.s01); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ values20 = (VEC_DATA_TYPE(DATA_TYPE, 8))(data20.s01212323); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ values21 = (VEC_DATA_TYPE(DATA_TYPE, 4))(data21.s0, data20.s3, data21.s01); \ \ values00 = POOL_OP(values00, values10); \ values01 = POOL_OP(values01, values11); \ values00 = POOL_OP(values00, values20); \ values01 = POOL_OP(values01, values21); \ \ res = POOL_OP((VEC_DATA_TYPE(DATA_TYPE, 4))(values00.s036, values01.s1), (VEC_DATA_TYPE(DATA_TYPE, 4))(values00.s147, values01.s2)); \ res = POOL_OP(res, (VEC_DATA_TYPE(DATA_TYPE, 4))(values00.s25, values01.s03)); \ }) #define POOLING3x3_STRIDE2(res, input, output) \ ({ \ VEC_DATA_TYPE(DATA_TYPE, 8) \ data00 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); \ DATA_TYPE data01 = *((__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0) + 8); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ data10 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); \ DATA_TYPE data11 = *((__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0) + 8); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ data20 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); \ DATA_TYPE data21 = *((__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0) + 8); \ \ VEC_DATA_TYPE(DATA_TYPE, 8) \ values00 = (VEC_DATA_TYPE(DATA_TYPE, 8))(data00.s01223445); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ values01 = (VEC_DATA_TYPE(DATA_TYPE, 4))(data00.s667, data01); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ values10 = (VEC_DATA_TYPE(DATA_TYPE, 8))(data10.s01223445); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ values11 = (VEC_DATA_TYPE(DATA_TYPE, 4))(data10.s667, data11); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ values20 = (VEC_DATA_TYPE(DATA_TYPE, 8))(data20.s01223445); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ values21 = (VEC_DATA_TYPE(DATA_TYPE, 4))(data20.s667, data21); \ \ values00 = POOL_OP(values00, values10); \ values01 = POOL_OP(values01, values11); \ values00 = POOL_OP(values00, values20); \ values01 = POOL_OP(values01, values21); \ \ res = POOL_OP((VEC_DATA_TYPE(DATA_TYPE, 4))(values00.s036, values01.s1), (VEC_DATA_TYPE(DATA_TYPE, 4))(values00.s147, values01.s2)); \ res = POOL_OP(res, (VEC_DATA_TYPE(DATA_TYPE, 4))(values00.s25, values01.s03)); \ }) #define POOLING3x3_STRIDE3(res, input, output) \ ({ \ VEC_DATA_TYPE(DATA_TYPE, 8) \ data00 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ data01 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0) + 8); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ data10 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ data11 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0) + 8); \ VEC_DATA_TYPE(DATA_TYPE, 8) \ data20 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); \ VEC_DATA_TYPE(DATA_TYPE, 4) \ data21 = vload4(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0) + 8); \ \ data00 = POOL_OP(data00, data10); \ data01 = POOL_OP(data01, data11); \ data00 = POOL_OP(data00, data20); \ data01 = POOL_OP(data01, data21); \ \ res = POOL_OP((VEC_DATA_TYPE(DATA_TYPE, 4))(data00.s036, data01.s1), (VEC_DATA_TYPE(DATA_TYPE, 4))(data00.s147, data01.s2)); \ res = POOL_OP(res, (VEC_DATA_TYPE(DATA_TYPE, 4))(data00.s25, data01.s03)); \ }) DATA_TYPE calculate_avg_scale(const int pool_size, const int upper_bound_w, const int upper_bound_h, const int pad_x, const int pad_y, const int stride_x, const int stride_y) { const int start_x = get_global_id(0) * stride_x - pad_x; const int start_y = get_global_id(1) * stride_y - pad_y; const int end_x = min(start_x + pool_size, upper_bound_w); const int end_y = min(start_y + pool_size, upper_bound_h); return ((end_y - start_y) * (end_x - start_x)); } /** Performs a pooling function of pool size equal to 2. * * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are QS8/QS16/F16/F32; * @note In case of average pooling the following information must be passed at compile time: * -DPOOL_AVG must be provided otherwise max pooling will be performed. * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension * * @param[in] input_ptr Pointer to the source image. Supported data types: QS8/QS16/F16/F32 * @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 source image * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr * @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 source 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 */ __kernel void pooling_layer_2( TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { // Get pixels pointer Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); // Load data VEC_DATA_TYPE(DATA_TYPE, 2) data0 = vload2(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); VEC_DATA_TYPE(DATA_TYPE, 2) data1 = vload2(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); // Perform calculations data0 = POOL_OP(data0, data1); DATA_TYPE res = POOL_OP(data0.s0, data0.s1); // Divide by pool region in case of average pooling #ifdef POOL_AVG res = DIV_OP(res, calculate_avg_scale(2, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); #endif /* POOL_AVG */ // Store result *(__global DATA_TYPE *)output.ptr = res; } /** Performs a pooling function of pool size equal to 3 * * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are QS8/QS16/F16/F32; * @note In case of average pooling the following information must be passed at compile time: * -DPOOL_AVG must be provided otherwise max pooling will be performed. * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension * * @param[in] input_ptr Pointer to the source image. Supported data types: QS8/QS16/F16/F32 * @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 source image * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr * @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 source 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 */ __kernel void pooling_layer_3( TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { // Get pixels pointer Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); // Load data VEC_DATA_TYPE(DATA_TYPE, 3) data0 = vload3(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); VEC_DATA_TYPE(DATA_TYPE, 3) data1 = vload3(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); VEC_DATA_TYPE(DATA_TYPE, 3) data2 = vload3(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); // Perform calculations data0 = POOL_OP(data0, data1); data0 = POOL_OP(data0, data2); DATA_TYPE res = POOL_OP(POOL_OP(data0.s0, data0.s1), data0.s2); // Divide by pool region in case of average pooling #ifdef POOL_AVG res = DIV_OP(res, calculate_avg_scale(3, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); #endif /* POOL_AVG */ // Store result *(__global DATA_TYPE *)output.ptr = res; } #if defined(POOLING3x3) && !defined(FIXED_POINT_POSITION) #define CONVERT_OP(data_type) convert_##data_type##4 #define CONVERT_VECTOR4(data_type) CONVERT_OP(data_type) VEC_DATA_TYPE(DATA_TYPE, 4) calculate_avg_scale4(const int pool_size, const int upper_bound_w, const int upper_bound_h, const int pad_x, const int pad_y, const int stride_x, const int stride_y) { const int4 start_x = ((int4)get_global_id(0) * 4 + (int4)(0, 1, 2, 3)) * (int4)stride_x - (int4)pad_x; const int start_y = get_global_id(1) * stride_y - pad_y; const int4 end_x = min(start_x + (int4)pool_size, (int4)upper_bound_w); const int end_y = min(start_y + pool_size, upper_bound_h); return (VEC_DATA_TYPE(DATA_TYPE, 4))(1.f) / CONVERT_VECTOR4(DATA_TYPE)(((int4)(end_y - start_y)) * (end_x - start_x)); } /** Performs an optimized pooling function of pool size equal to 3 when the stride_x is less equal than 3 * * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are QS8/QS16/F16/F32; * @note In case of average pooling the following information must be passed at compile time: * -DPOOL_AVG must be provided otherwise max pooling will be performed. * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension * * @param[in] input_ptr Pointer to the source image. Supported data types: F16/F32 * @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 source image * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr * @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 source 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 */ __kernel void pooling_layer_3_optimized( TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { // Get pixels pointer Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); VEC_DATA_TYPE(DATA_TYPE, 4) res; // Perform pooling 3x3 for 4 output elements POOLING3x3(res, input, output); // Divide by pool region in case of average pooling #ifdef POOL_AVG res *= calculate_avg_scale4(3, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y); #endif // POOL_AVG vstore4(res, 0, (__global DATA_TYPE *)output.ptr); } #endif // defined(POOLING3x3) && !defined(FIXED_POINT_POSITION) /** Performs a pooling function of pool size equal to 7. * * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are QS8/QS16/F16/F32; * @note In case of average pooling the following information must be passed at compile time: * -DPOOL_AVG must be provided otherwise max pooling will be performed. * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension * * @param[in] input_ptr Pointer to the source image. Supported data types: QS8/QS16/F16/F32 * @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 source image * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr * @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 source 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 */ __kernel void pooling_layer_7( TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { // Get pixels pointer Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); // Load data VEC_DATA_TYPE(DATA_TYPE, 8) data0 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); VEC_DATA_TYPE(DATA_TYPE, 8) data1 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); VEC_DATA_TYPE(DATA_TYPE, 8) data2 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); VEC_DATA_TYPE(DATA_TYPE, 8) data3 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 3, 0)); VEC_DATA_TYPE(DATA_TYPE, 8) data4 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 4, 0)); VEC_DATA_TYPE(DATA_TYPE, 8) data5 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 5, 0)); VEC_DATA_TYPE(DATA_TYPE, 8) data6 = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 6, 0)); // Pool operation of all rows data0 = POOL_OP(data0, data1); data2 = POOL_OP(data2, data3); data4 = POOL_OP(data4, data5); data0 = POOL_OP(data0, data2); data4 = POOL_OP(data4, data6); data0 = POOL_OP(data0, data4); // Set last element #ifdef POOL_AVG data0.s7 = 0; #else /* POOL_AVG */ data0.s7 = data0.s6; #endif /* POOL_AVG */ // Reduce result VEC_DATA_TYPE(DATA_TYPE, 4) reduce4 = POOL_OP(data0.s0123, data0.s4567); VEC_DATA_TYPE(DATA_TYPE, 2) reduce2 = POOL_OP(reduce4.s01, reduce4.s23); DATA_TYPE res = POOL_OP(reduce2.s0, reduce2.s1); // Divide by pool region in case of average pooling #ifdef POOL_AVG res = DIV_OP(res, calculate_avg_scale(7, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); #endif /* POOL_AVG */ // Store result *(__global DATA_TYPE *)output.ptr = res; }