| /* |
| * Copyright (c) 2016-2018 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" |
| |
| /** 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); |
| } |
| |
| /** 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 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_sum_ptr The local buffer to hold sumed values. Supported data types: same as @p src_ptt |
| * @param[in] partial_sum_stride_x Stride of the output tensor in X dimension (in bytes) |
| * @param[in] partial_sum_step_x partial_sum_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] partial_sum_stride_y Stride of the output tensor in Y dimension (in bytes) |
| * @param[in] partial_sum_step_y partial_sum_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] partial_sum_offset_first_element_in_bytes The offset of the first element in the source tensor |
| * @param[in] local_sums Local buffer for storing the partial sum |
| */ |
| __kernel void reduction_operation_x( |
| IMAGE_DECLARATION(src), |
| IMAGE_DECLARATION(partial_sum), |
| __local DATA_TYPE *local_sums) |
| { |
| Image src = CONVERT_TO_IMAGE_STRUCT(src); |
| Image partial_sum = CONVERT_TO_IMAGE_STRUCT(partial_sum); |
| |
| 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_sums[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) |
| { |
| local_sums[lid] += local_sums[lid + i]; |
| } |
| barrier(CLK_LOCAL_MEM_FENCE); |
| } |
| |
| if(lid == 0) |
| { |
| #if defined(MEAN) && defined(WIDTH) |
| if(y == get_local_size(1) - 1) |
| { |
| local_sums[0] /= WIDTH; |
| } |
| #endif /* defined(MEAN) && defined(WIDTH) */ |
| ((__global DATA_TYPE *)offset(&partial_sum, get_group_id(0), y))[0] = local_sums[0]; |
| } |
| } |
| } |
| |
| #if defined(WIDTH) |
| /** This kernel performs reduction on x-axis. (QASYMM8) |
| * |
| * @note The width size must be passed at compile time using -DWIDTH e.g. -DWIDTH=128 |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8 |
| * @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_quantized_x( |
| VECTOR_DECLARATION(src), |
| VECTOR_DECLARATION(output)) |
| { |
| Vector src = CONVERT_TO_VECTOR_STRUCT(src); |
| Vector output = CONVERT_TO_VECTOR_STRUCT(output); |
| |
| uint res = 0; |
| |
| for(unsigned int x = 0; x < WIDTH; ++x) |
| { |
| res += *((__global uchar *)vector_offset(&src, x)); |
| } |
| |
| #if defined(MEAN) |
| res /= WIDTH; |
| #endif /* defined(MEAN) */ |
| |
| // Store result |
| *((__global uchar *)output.ptr) = convert_uchar(res); |
| } |
| #endif /* defined(HEIGHT) */ |
| |
| #if defined(HEIGHT) |
| /** This kernel performs reduction on y-axis. |
| * |
| * @note The 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/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 = 0; |
| |
| for(unsigned int y = 0; 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(SUM_SQUARE) |
| in *= in; |
| #endif // SQRSUM |
| res += in; |
| } |
| |
| #if defined(MEAN) |
| res /= HEIGHT; |
| #endif /* defined(MEAN) */ |
| |
| // Store result |
| vstore16(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); |
| } |
| #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/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 = 0; |
| |
| for(unsigned int z = 0; 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(SUM_SQUARE) |
| in *= in; |
| #endif // SQRSUM |
| res += in; |
| } |
| |
| #if defined(MEAN) |
| res /= DEPTH; |
| #endif /* defined(MEAN) */ |
| |
| // Store result |
| vstore16(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); |
| } |
| #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/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 = 0; |
| |
| for(unsigned int w = 0; 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(SUM_SQUARE) |
| in *= in; |
| #endif // SQRSUM |
| res += in; |
| } |
| |
| #if defined(MEAN) |
| res /= BATCH; |
| #endif /* defined(MEAN) */ |
| |
| // Store result |
| vstore16(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); |
| } |
| #endif /* defined(BATCH) && defined(DEPTH) */ |