| /* |
| * 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) */ |