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Diffstat (limited to 'src/core/CL/cl_kernels/reduction_operation.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/reduction_operation.cl | 460 |
1 files changed, 0 insertions, 460 deletions
diff --git a/src/core/CL/cl_kernels/reduction_operation.cl b/src/core/CL/cl_kernels/reduction_operation.cl deleted file mode 100644 index 9f2c6e23b5..0000000000 --- a/src/core/CL/cl_kernels/reduction_operation.cl +++ /dev/null @@ -1,460 +0,0 @@ -/* - * Copyright (c) 2016-2021 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 defined(FLOAT_DATA_TYPE) -#define ISGREATER(x, y) (SELECT_VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE))(isgreater(x, y)) -#define ISLESS(x, y) (SELECT_VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE))(isless(x, y)) -#define ISGREATER_SCALAR(x, y) (SELECT_DATA_TYPE(DATA_TYPE_PROMOTED))(isgreater(x, y)) -#define ISLESS_SCALAR(x, y) (SELECT_DATA_TYPE(DATA_TYPE_PROMOTED))(isless(x, y)) -#else // !FLOAT_DATA_TYPE -#if defined(WIDTH) -#define ISGREATER(x, y) (x > y) ? 1 : 0 -#define ISLESS(x, y) (x < y) ? 1 : 0 -#define ISGREATER_SCALAR ISGREATER -#define ISLESS_SCALAR ISLESS -#else // !defined(WIDTH) -#define ISGREATER(x, y) select((VEC_DATA_TYPE(int, VEC_SIZE))0, (VEC_DATA_TYPE(int, VEC_SIZE)) - 1, x > y) -#define ISLESS(x, y) select((VEC_DATA_TYPE(int, VEC_SIZE))0, (VEC_DATA_TYPE(int, VEC_SIZE)) - 1, x < y) -#endif // defined(WIDTH) -#endif // defined(FLOAT_DATA_TYPE) - -#if defined(WIDTH) -#if defined(OPERATION) - -#define sum(in0, in1, size) (in0 + SUM_REDUCE(in1, size)) -#define square_sum(in0, in1, size) (in0 + SUM_REDUCE((in1 * in1), size)) -#define product(in0, in1, size) (in0 * PROD_REDUCE(in1, size)) - -/** This kernel performs parallel reduction given an operation on x-axis. - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The operation we want to perform must be passed at compile time using -DOPERATION e.g. -DOPERATION=square_sum - * @note The mean flag must be passed at compile time using -DMEAN if we want to compute the mean value - * @note The product flag must be passed at compile time using -DPROD if we want to compute the product, otherwise sum will be used - * @note The width size must be passed at compile time using -DWIDTH e.g. -DWIDTH=128 if we want to compute the mean value - * - * @param[in] input_ptr Pointer to the source tensor. Supported data types: F16/F32 - * @param[in] input_stride_x Stride of the source tensor 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 tensor 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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] output_ptr Pointer to the destination tensor. Supported data types: same as @p input - * @param[in] output_stride_x Stride of the destination tensor 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 tensor 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_offset_first_element_in_bytes The offset of the first element in the destination tensor - */ -__kernel void reduction_operation_x( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + y * input_stride_y + z * input_stride_z; - __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + y * output_stride_y + z * output_stride_z; - -#if defined(PROD) - DATA_TYPE res = (DATA_TYPE)1; -#else // defined(PROD) - DATA_TYPE res = (DATA_TYPE)0; -#endif // defined(PROD) - - int x = 0; - - for(; x <= (WIDTH - VEC_SIZE); x += VEC_SIZE) - { - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - vals = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + x * sizeof(DATA_TYPE))); - res = OPERATION(res, vals, VEC_SIZE); - } - -#if(WIDTH % VEC_SIZE) - _Pragma("unroll") for(; x < WIDTH; ++x) - { - DATA_TYPE val = *((__global DATA_TYPE *)(input_addr + x * sizeof(DATA_TYPE))); - res = OPERATION(res, val, 1); - } -#endif // (WIDTH % VEC_SIZE) - -#if defined(MEAN) - res /= WIDTH; -#endif // defined(MEAN) - *((__global DATA_TYPE *)output_addr) = res; -} -#endif // defined(OPERATION) -/** This kernel performs reduction on x-axis. (Non parallel) - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width size must be passed at compile time using -DWIDTH e.g. -DWIDTH=128 - * @note The product flag must be passed at compile time using -DPROD if we want to compute the product, otherwise sum will be used - * - * @param[in] input_ptr Pointer to the source tensor. Supported data types: S32/F16/F32 and QASYMM8/QASYMM8_SIGNED for operation MEAN - * @param[in] input_stride_x Stride of the source tensor 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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the output tensor 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_offset_first_element_in_bytes The offset of the first element in the source tensor - */ -__kernel void reduction_operation_non_parallel_x( - VECTOR_DECLARATION(input), - VECTOR_DECLARATION(output)) -{ - Vector input = CONVERT_TO_VECTOR_STRUCT(input); - Vector output = CONVERT_TO_VECTOR_STRUCT(output); - - DATA_TYPE_PROMOTED res = CONVERT(*((__global DATA_TYPE *)vector_offset(&input, 0)), DATA_TYPE_PROMOTED); - - // Convert input into F32 in order to perform quantized multiplication -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - float res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, 1); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - - for(unsigned int x = 1; x < WIDTH; ++x) - { - DATA_TYPE_PROMOTED in = CONVERT(*((__global DATA_TYPE *)vector_offset(&input, x)), DATA_TYPE_PROMOTED); -#if defined(MIN) - res = select(res, in, ISLESS_SCALAR(in, res)); -#elif defined(MAX) - res = select(res, in, ISGREATER_SCALAR(in, res)); -#elif defined(PROD) -#if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, 1); -#else // !(defined(OFFSET) && defined(SCALE)) - res *= in; -#endif // defined(OFFSET) && defined(SCALE) -#else // defined(SUM)) - res += in; -#endif // defined(MAX) || defined(MIN) || defined(PROD) - } - - // Store result -#if defined(MEAN) - res /= WIDTH; -#endif // defined(MEAN) - - // Subtract the offsets in case of quantized SUM -#if defined(SUM) && defined(OFFSET) && defined(SCALE) - res -= (WIDTH - 1) * OFFSET; -#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) - - // Re-quantize -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, 1); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - - *((__global DATA_TYPE *)output.ptr) = CONVERT_SAT(res, DATA_TYPE); -} -#endif // defined(WIDTH) - -#if defined(HEIGHT) -/** This kernel performs reduction on y-axis. - * - * @note The input data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The height size must be passed at compile time using -DHEIGHT e.g. -DHEIGHT=128 - * - * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32 - * @param[in] input_stride_x Stride of the source tensor 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 tensor 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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the output tensor 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 output tensor 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_offset_first_element_in_bytes The offset of the first element in the source tensor - */ -__kernel void reduction_operation_y( - IMAGE_DECLARATION(input), - IMAGE_DECLARATION(output)) -{ - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - - __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y; - __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y; - - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) - res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); - - // Convert input into F32 in order to perform quantized multiplication -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - VEC_DATA_TYPE(float, VEC_SIZE) - res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - -#if defined(SUM_SQUARE) - res *= res; -#endif // defined(SUM_SQUARE) - - for(unsigned int y = 1; y < HEIGHT; ++y) - { - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) - in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + y * input_stride_y)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); -#if defined(MIN) - res = select(res, in, ISLESS(in, res)); -#elif defined(MAX) - res = select(res, in, ISGREATER(in, res)); -#else // !(defined(MAX) || defined(MIN)) -#if defined(SUM_SQUARE) - in *= in; -#endif // defined(SUM_SQUARE) -#if defined(PROD) - -#if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#else // !(defined(OFFSET) && defined(SCALE)) - res *= in; -#endif // defined(OFFSET) && defined(SCALE) - -#else // !defined(PROD) - res += in; -#endif // defined(PROD) -#endif // defined(MAX) || defined(MIN) - } - -#if defined(MEAN) - res /= HEIGHT; -#endif // defined(MEAN) - - // Subtract the offsets in case of quantized SUM -#if defined(SUM) && defined(OFFSET) && defined(SCALE) - res -= (HEIGHT - 1) * OFFSET; -#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) - - // Re-quantize -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - - // Store result - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); - STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); -} -#endif // defined(HEIGHT) - -#if defined(DEPTH) -/** This kernel performs reduction on z-axis. - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The depth size must be passed at compile time using -DDEPTH e.g. -DDEPTH=128 - * - * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32 - * @param[in] input_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the output tensor 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 output tensor 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 output 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 source tensor - */ -__kernel void reduction_operation_z( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y + z * input_stride_z; - __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y + z * output_stride_z; - - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) - res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); - - // Convert input into F32 in order to perform quantized multiplication -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - VEC_DATA_TYPE(float, VEC_SIZE) - res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - -#if defined(SUM_SQUARE) - res *= res; -#endif // defined(SUM_SQUARE) - - for(unsigned int z = 1; z < DEPTH; ++z) - { - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) - in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + z * input_stride_z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); - -#if defined(MIN) - res = select(res, in, ISLESS(in, res)); -#elif defined(MAX) - res = select(res, in, ISGREATER(in, res)); -#else // !(defined(MAX) || defined(MIN)) -#if defined(SUM_SQUARE) - in *= in; -#endif // defined(SUM_SQUARE) -#if defined(PROD) - -#if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#else // !(defined(OFFSET) && defined(SCALE)) - res *= in; -#endif // defined(OFFSET) && defined(SCALE) - -#else // !defined(PROD) - res += in; -#endif // defined(PROD) -#endif // defined(MAX) || defined(MIN) - } - -#if defined(MEAN) - res /= DEPTH; -#endif // defined(MEAN) - - // Subtract the offsets in case of quantized SUM -#if defined(SUM) && defined(OFFSET) && defined(SCALE) - res -= (DEPTH - 1) * OFFSET; -#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) - - // Re-quantize -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - - // Store result - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); - - STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); -} -#endif /* defined(DEPTH) */ - -#if defined(BATCH) && defined(DEPTH) -/** This kernel performs reduction on w-axis. - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The batch size must be passed at compile time using -DBATCH e.g. -DBATCH=128 - * @note The depth size must be passed at compile time using -DBATCH e.g. -DDEPTH=128 - * - * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32 - * @param[in] input_stride_x Stride of the source tensor 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 tensor 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_stride_w Stride of the source tensor in W dimension (in bytes) - * @param[in] input_step_w input_stride_w * number of elements along W processed per workitem(in bytes) - * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr - * @param[in] output_stride_x Stride of the output tensor 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 output tensor 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 output 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_stride_w Stride of the output tensor in W dimension (in bytes) - * @param[in] output_step_w output_stride_w * number of elements along W processed per workitem(in bytes) - * @param[in] output_offset_first_element_in_bytes The offset of the first element in the source tensor - */ -__kernel void reduction_operation_w( - TENSOR4D_DECLARATION(input), - TENSOR4D_DECLARATION(output)) -{ - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y + (z % DEPTH) * input_stride_z + (z / DEPTH) * input_stride_w; - __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y + (z % DEPTH) * output_stride_z + (z / DEPTH) * output_stride_z; - - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) - res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); - - // Convert input into F32 in order to perform quantized multiplication -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - VEC_DATA_TYPE(float, VEC_SIZE) - res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - -#if defined(SUM_SQUARE) - res *= res; -#endif // defined(SUM_SQUARE) - - for(unsigned int w = 1; w < BATCH; ++w) - { - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) - in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + w * input_stride_w)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); - -#if defined(MIN) - res = select(res, in, ISLESS(in, res)); -#elif defined(MAX) - res = select(res, in, ISGREATER(in, res)); -#else // !(defined(MAX) || defined(MIN)) -#if defined(SUM_SQUARE) - in *= in; -#endif // defined(SUM_SQUARE) -#if defined(PROD) - -#if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#else // !(defined(OFFSET) && defined(SCALE)) - res *= in; -#endif // defined(OFFSET) && defined(SCALE) - -#else // !defined(PROD) - res += in; -#endif //defined(PROD) -#endif // defined(MAX) || defined(MIN) - } - -#if defined(MEAN) - res /= BATCH; -#endif // defined(MEAN) - - // Subtract the offsets in case of quantized SUM -#if defined(SUM) && defined(OFFSET) && defined(SCALE) - res -= (BATCH - 1) * OFFSET; -#endif // defined(OFFSET) && defined(OFFSET) && defined(SCALE) - - // Re-quantize -#if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); -#endif // defined(PROD) && defined(OFFSET) && defined(SCALE) - - // Store result - VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); - STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); -} -#endif /* defined(BATCH) && defined(DEPTH) */ |