| /* |
| * Copyright (c) 2016-2019 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" |
| |
| #if FLOAT_DATA_TYPE |
| #define ISGREATER(x, y) isgreater(x, y) |
| #define ISLESS(x, y) 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 |
| #else // !defined(WIDTH) |
| #define ISGREATER(x, y) select((int16)0, (int16)-1, x > y) |
| #define ISLESS(x, y) select((int16)0, (int16)-1, x < y) |
| #endif // defined(WIDTH) |
| #endif // FLOAT_DATA_TYPE |
| |
| /** Calculate square sum of a vector |
| * |
| * @param[in] input Pointer to the first pixel. |
| * |
| * @return square sum of vector. |
| */ |
| inline DATA_TYPE square_sum(__global const DATA_TYPE *input) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = vload16(0, input); |
| |
| in *= in; |
| |
| in.s01234567 += in.s89ABCDEF; |
| in.s0123 += in.s4567; |
| in.s01 += in.s23; |
| |
| return (in.s0 + in.s1); |
| } |
| |
| /** Calculate sum of a vector |
| * |
| * @param[in] input Pointer to the first pixel. |
| * |
| * @return sum of vector. |
| */ |
| inline DATA_TYPE sum(__global const DATA_TYPE *input) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = vload16(0, input); |
| |
| in.s01234567 += in.s89ABCDEF; |
| in.s0123 += in.s4567; |
| in.s01 += in.s23; |
| |
| return (in.s0 + in.s1); |
| } |
| |
| /** Calculate product of a vector |
| * |
| * @param[in] input Pointer to the first pixel. |
| * |
| * @return product of vector. |
| */ |
| inline DATA_TYPE product(__global const DATA_TYPE *input) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = vload16(0, input); |
| |
| in.s01234567 *= in.s89ABCDEF; |
| in.s0123 *= in.s4567; |
| in.s01 *= in.s23; |
| |
| return (in.s0 * in.s1); |
| } |
| #if defined(OPERATION) |
| /** 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] src_ptr Pointer to the source tensor. Supported data types: F16/F32 |
| * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| * @param[in] partial_res_ptr The local buffer to hold partial result values. Supported data types: same as @p src_ptr |
| * @param[in] partial_res_stride_x Stride of the output tensor in X dimension (in bytes) |
| * @param[in] partial_res_step_x partial_res_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] partial_res_stride_y Stride of the output tensor in Y dimension (in bytes) |
| * @param[in] partial_res_step_y partial_res_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] partial_res_offset_first_element_in_bytes The offset of the first element in the source tensor |
| * @param[in] local_results Local buffer for storing the partial result |
| */ |
| __kernel void reduction_operation_x( |
| IMAGE_DECLARATION(src), |
| IMAGE_DECLARATION(partial_res), |
| __local DATA_TYPE *local_results) |
| { |
| Image src = CONVERT_TO_IMAGE_STRUCT(src); |
| Image partial_res = CONVERT_TO_IMAGE_STRUCT(partial_res); |
| |
| unsigned int lsize = get_local_size(0); |
| unsigned int lid = get_local_id(0); |
| |
| for(unsigned int y = 0; y < get_local_size(1); ++y) |
| { |
| local_results[lid] = OPERATION((__global DATA_TYPE *)offset(&src, 0, y)); |
| barrier(CLK_LOCAL_MEM_FENCE); |
| |
| // Perform parallel reduction |
| for(unsigned int i = lsize >> 1; i > 0; i >>= 1) |
| { |
| if(lid < i) |
| { |
| #if defined(PROD) |
| local_results[lid] *= local_results[lid + i]; |
| #else // !defined(PROD) |
| local_results[lid] += local_results[lid + i]; |
| #endif // defined(PROD) |
| } |
| barrier(CLK_LOCAL_MEM_FENCE); |
| } |
| |
| if(lid == 0) |
| { |
| #if defined(MEAN) && defined(WIDTH) |
| if(y == get_local_size(1) - 1) |
| { |
| local_results[0] /= WIDTH; |
| } |
| #endif // defined(MEAN) && defined(WIDTH) |
| ((__global DATA_TYPE *)offset(&partial_res, get_group_id(0), y))[0] = local_results[0]; |
| } |
| } |
| } |
| #endif // defined(OPERATION) |
| |
| #if defined(WIDTH) |
| /** 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 |
| * @note In case of ARG_MIN and ARG_MAX the condition data type must be passed at compile time using -DCOND_DATA_TYPE e.g. -DCOND_DATA_TYPE=short |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data types: S32/F16/F32 and QASYMM8 for operation MEAN |
| * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src_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 src_ptt |
| * @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(src), |
| VECTOR_DECLARATION(output)) |
| { |
| Vector src = CONVERT_TO_VECTOR_STRUCT(src); |
| Vector output = CONVERT_TO_VECTOR_STRUCT(output); |
| |
| DATA_TYPE_PROMOTED res = *((__global DATA_TYPE *)vector_offset(&src, 0)); |
| |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| uint indx = 0; |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| |
| for(unsigned int x = 1; x < WIDTH; ++x) |
| { |
| DATA_TYPE_PROMOTED in = *((__global DATA_TYPE *)vector_offset(&src, x)); |
| #if defined(ARG_MAX) |
| indx = select(indx, x, ISGREATER(in, res)); |
| res = select(res, in, CONVERT(ISGREATER(in, res), COND_DATA_TYPE)); |
| #elif defined(ARG_MIN) |
| indx = select(indx, x, ISLESS(in, res)); |
| res = select(res, in, CONVERT(ISLESS(in, res), COND_DATA_TYPE)); |
| #elif defined(MIN) |
| res = select(res, in, CONVERT(ISLESS(in, res), COND_DATA_TYPE)); |
| #elif defined(MAX) |
| res = select(res, in, CONVERT(ISGREATER(in, res), COND_DATA_TYPE)); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| res += in; |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| |
| // Store result |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| *((__global uint *)output.ptr) = indx; |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(MEAN) |
| res /= WIDTH; |
| #endif // defined(MEAN) |
| #if defined(MIN) || defined(MAX) |
| *((__global DATA_TYPE_PROMOTED *)output.ptr) = res; |
| #else // defined(MIN) || defined(MAX) |
| *((__global uchar *)output.ptr) = convert_uchar(res); |
| #endif // defined(MIN) || defined(MAX) |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| #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] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/S32/F16/F32 |
| * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] src_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 src_ptt |
| * @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(src), |
| IMAGE_DECLARATION(output)) |
| { |
| Image src = CONVERT_TO_IMAGE_STRUCT(src); |
| Image output = CONVERT_TO_IMAGE_STRUCT(output); |
| |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| res = CONVERT(vload16(0, (__global DATA_TYPE *)offset(&src, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| |
| #if defined(SUM_SQUARE) |
| res *= res; |
| #endif // defined(SUM_SQUARE) |
| |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| uint16 indx = 0; |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| |
| for(unsigned int y = 1; y < HEIGHT; ++y) |
| { |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| in = CONVERT(vload16(0, (__global DATA_TYPE *)offset(&src, 0, y)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| #if defined(ARG_MAX) |
| uint16 cond_conv = CONVERT(ISGREATER(in, res), uint16); |
| indx = select(indx, y, cond_conv); |
| res = select(res, in, ISGREATER(in, res)); |
| #elif defined(ARG_MIN) |
| uint16 cond_conv = CONVERT(ISLESS(in, res), uint16); |
| indx = select(indx, y, cond_conv); |
| res = select(res, in, ISLESS(in, res)); |
| #elif defined(MIN) |
| res = select(res, in, ISLESS(in, res)); |
| #elif defined(MAX) |
| res = select(res, in, ISGREATER(in, res)); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(SUM_SQUARE) |
| in *= in; |
| #endif // defined(SUM_SQUARE) |
| #if defined(PROD) |
| res *= in; |
| #else // !defined(PROD) |
| res += in; |
| #endif // defined(PROD) |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| |
| // Store result |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| vstore16(indx, 0, (__global uint *)output.ptr); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(MEAN) |
| res /= HEIGHT; |
| #endif // defined(MEAN) |
| vstore16(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| #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/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_ptt |
| * @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)) |
| { |
| Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); |
| Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); |
| |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| res = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| |
| #if defined(COMPLEX) |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| res1 = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 8, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| #endif // defined(COMPLEX) |
| #if defined(SUM_SQUARE) |
| res *= res; |
| #endif // defined(SUM_SQUARE) |
| |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| uint16 indx = 0; |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| |
| for(unsigned int z = 1; z < DEPTH; ++z) |
| { |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| in = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| |
| #if defined(COMPLEX) |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| in1 = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 8, 0, z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| #endif // defined(COMPLEX) |
| |
| #if defined(ARG_MAX) |
| uint16 cond_conv = CONVERT(ISGREATER(in, res), uint16); |
| indx = select(indx, z, cond_conv); |
| res = select(res, in, ISGREATER(in, res)); |
| #elif defined(ARG_MIN) |
| uint16 cond_conv = CONVERT(ISLESS(in, res), uint16); |
| indx = select(indx, z, cond_conv); |
| res = select(res, in, ISLESS(in, res)); |
| #elif defined(MIN) |
| res = select(res, in, ISLESS(in, res)); |
| #elif defined(MAX) |
| res = select(res, in, ISGREATER(in, res)); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(SUM_SQUARE) |
| in *= in; |
| #endif // defined(SUM_SQUARE) |
| #if defined(PROD) |
| res *= in; |
| #else //!defined(PROD) |
| res += in; |
| #if defined(COMPLEX) |
| res1 += in1; |
| #endif // defined(COMPLEX) |
| #endif //defined(PROD) |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| |
| // Store result |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| vstore16(indx, 0, (__global uint *)output.ptr); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(MEAN) |
| res /= DEPTH; |
| #endif // defined(MEAN) |
| vstore16(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); |
| #if defined(COMPLEX) |
| vstore16(CONVERT(res1, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)tensor3D_offset(&output, 8, 0, 0)); |
| #endif // defined(COMPLEX) |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| #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/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_ptt |
| * @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)) |
| { |
| Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT(input, DEPTH); |
| Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH); |
| |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| res = CONVERT(vload16(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, 0, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| |
| #if defined(SUM_SQUARE) |
| res *= res; |
| #endif // defined(SUM_SQUARE) |
| |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| uint16 indx = 0; |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| |
| for(unsigned int w = 1; w < BATCH; ++w) |
| { |
| VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) |
| in = CONVERT(vload16(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, 0, 0, w)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); |
| |
| #if defined(ARG_MAX) |
| uint16 cond_conv = CONVERT(ISGREATER(in, res), uint16); |
| indx = select(indx, w, cond_conv); |
| res = select(res, in, ISGREATER(in, res)); |
| #elif defined(ARG_MIN) |
| uint16 cond_conv = CONVERT(ISLESS(in, res), uint16); |
| indx = select(indx, w, cond_conv); |
| res = select(res, in, ISLESS(in, res)); |
| #elif defined(MIN) |
| res = select(res, in, ISLESS(in, res)); |
| #elif defined(MAX) |
| res = select(res, in, ISGREATER(in, res)); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(SUM_SQUARE) |
| in *= in; |
| #endif // defined(SUM_SQUARE) |
| #if defined(PROD) |
| res *= in; |
| #else //!defined(PROD) |
| res += in; |
| #endif //defined(PROD) |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| |
| // Store result |
| #if defined(ARG_MAX) || defined(ARG_MIN) |
| vstore16(indx, 0, (__global uint *)output.ptr); |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #if defined(MEAN) |
| res /= BATCH; |
| #endif // defined(MEAN) |
| vstore16(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| #endif /* defined(BATCH) && defined(DEPTH) */ |