| /* |
| * Copyright (c) 2019-2020 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 defined(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((VEC_DATA_TYPE(DATA_TYPE_SELECT, 16))0, (VEC_DATA_TYPE(DATA_TYPE_SELECT, 16)) - 1, x > y) |
| #define ISLESS(x, y) select((VEC_DATA_TYPE(DATA_TYPE_SELECT, 16))0, (VEC_DATA_TYPE(DATA_TYPE_SELECT, 16)) - 1, x < y) |
| #endif // defined(WIDTH) |
| #endif // defined(FLOAT_DATA_TYPE) |
| |
| #if defined(ARG_MAX) |
| #define CONDITION_TO_USE(x, y) ISGREATER(x, y) |
| #elif defined(ARG_MIN) |
| #define CONDITION_TO_USE(x, y) ISLESS(x, y) |
| #else // !(defined(ARG_MAX) || defined(ARG_MIN)) |
| #error "Unsupported reduction operation!" |
| #endif // defined(ARG_MAX) |
| |
| #if defined(DATA_TYPE_OUTPUT) && defined(DATA_TYPE_SELECT) |
| #if defined(WIDTH) |
| #if defined(ARG_MIN) |
| #if defined(PREV_OUTPUT) |
| /** Find index minimum value of a vector |
| * |
| * @param[in] input Pointer to the first value. |
| * |
| * @return index of the vector. |
| */ |
| inline DATA_TYPE_OUTPUT arg_idx_min_prev_out(__global const DATA_TYPE *input, __global const DATA_TYPE_OUTPUT *prev_res, const int x_idx) |
| { |
| int end_elem = (x_idx + 1) * 16; |
| if(end_elem > WIDTH) |
| { |
| end_elem = WIDTH - x_idx * 16; |
| } |
| DATA_TYPE_OUTPUT res = prev_res[0]; |
| for(int x_v = 1; x_v < end_elem; ++x_v) |
| { |
| res = select(res, prev_res[x_v], *(input + prev_res[x_v]) < * (input + res)); |
| } |
| return res; |
| } |
| #else // !defined(PREV_OUTPUT) |
| /** Find index minimum value of a vector |
| * |
| * @param[in] input Pointer to the first value. |
| * |
| * @return index of the vector. |
| */ |
| inline DATA_TYPE_OUTPUT arg_idx_min(__global const DATA_TYPE *input, const int x_idx) |
| { |
| #if WIDTH < 16 |
| DATA_TYPE_OUTPUT res = 0; |
| for(DATA_TYPE_OUTPUT x_v = res + 1; x_v < WIDTH; ++x_v) |
| { |
| res = select(res, x_v, *(input + x_v) < * (input + res)); |
| } |
| return res; |
| #else // WIDTH >= 16 |
| int x_elem = x_idx * 16; |
| const int x_goback = select(0, 16 - WIDTH % 16, x_elem + 16 > WIDTH); |
| x_elem -= x_goback; |
| |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = vload16(0, input - x_goback); |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| res = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 }; |
| |
| VEC_DATA_TYPE(DATA_TYPE_SELECT, 8) |
| idx_sel = (in.s01234567 <= in.s89abcdef); |
| in.s01234567 = select(in.s89abcdef, in.s01234567, idx_sel); |
| res.s01234567 = select(res.s89abcdef, res.s01234567, CONVERT(idx_sel, int8)); |
| |
| idx_sel.s0123 = (in.s0123 < in.s4567) || (in.s0123 == in.s4567 && CONVERT((res.s0123 < res.s4567), VEC_DATA_TYPE(DATA_TYPE_SELECT, 4))); |
| in.s0123 = select(in.s4567, in.s0123, idx_sel.s0123); |
| res.s0123 = select(res.s4567, res.s0123, CONVERT(idx_sel.s0123, int4)); |
| |
| idx_sel.s01 = (in.s01 < in.s23) || (in.s01 == in.s23 && CONVERT((res.s01 < res.s23), VEC_DATA_TYPE(DATA_TYPE_SELECT, 2))); |
| in.s01 = select(in.s23, in.s01, idx_sel.s01); |
| res.s01 = select(res.s23, res.s01, CONVERT(idx_sel.s01, int2)); |
| |
| idx_sel.s0 = (in.s0 < in.s1) || (in.s0 == in.s1 && CONVERT((res.s0 < res.s1), DATA_TYPE_SELECT)); |
| res.s0 = select(res.s1, res.s0, CONVERT(idx_sel.s0, int)); |
| |
| return res.s0 + x_elem; |
| #endif // WIDTH < 16 |
| } |
| #endif // defined(PREV_OUTPUT) |
| #endif // defined(ARG_MIN) |
| #if defined(ARG_MAX) |
| #if defined(PREV_OUTPUT) |
| /** Find index maximum value of a vector |
| * |
| * @param[in] input Pointer to the first value. |
| * |
| * @return index of the vector. |
| */ |
| inline DATA_TYPE_OUTPUT arg_idx_max_prev_out(__global const DATA_TYPE *input, __global const DATA_TYPE_OUTPUT *prev_res, const int x_idx) |
| { |
| int end_elem = (x_idx + 1) * 16; |
| if(end_elem > WIDTH) |
| { |
| end_elem = WIDTH - x_idx * 16; |
| } |
| DATA_TYPE_OUTPUT res = prev_res[0]; |
| for(int x_v = 1; x_v < end_elem; ++x_v) |
| { |
| res = select(res, prev_res[x_v], *(input + prev_res[x_v]) > *(input + res)); |
| } |
| return res; |
| } |
| #else // !defined(PREV_OUTPUT) |
| /** Find index maximum value of a vector |
| * |
| * @param[in] input Pointer to the first value. |
| * |
| * @return index of the vector. |
| */ |
| inline DATA_TYPE_OUTPUT arg_idx_max(__global const DATA_TYPE *input, const int x_idx) |
| { |
| #if WIDTH < 16 |
| DATA_TYPE_OUTPUT res = 0; |
| for(DATA_TYPE_OUTPUT x_v = res + 1; x_v < WIDTH; ++x_v) |
| { |
| res = select(res, x_v, *(input + x_v) > *(input + res)); |
| } |
| return res; |
| #else // WIDTH >= 16 |
| int x_elem = x_idx * 16; |
| const int x_goback = select(0, 16 - WIDTH % 16, x_elem + 16 > WIDTH); |
| x_elem -= x_goback; |
| |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = vload16(0, input - x_goback); |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| res = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 }; |
| |
| VEC_DATA_TYPE(DATA_TYPE_SELECT, 8) |
| idx_sel = (in.s01234567 >= in.s89abcdef); |
| in.s01234567 = select(in.s89abcdef, in.s01234567, idx_sel); |
| res.s01234567 = select(res.s89abcdef, res.s01234567, CONVERT(idx_sel, int8)); |
| |
| idx_sel.s0123 = (in.s0123 > in.s4567) || (in.s0123 == in.s4567 && CONVERT((res.s0123 < res.s4567), VEC_DATA_TYPE(DATA_TYPE_SELECT, 4))); |
| in.s0123 = select(in.s4567, in.s0123, idx_sel.s0123); |
| res.s0123 = select(res.s4567, res.s0123, CONVERT(idx_sel.s0123, int4)); |
| |
| idx_sel.s01 = (in.s01 > in.s23) || (in.s01 == in.s23 && CONVERT((res.s01 < res.s23), VEC_DATA_TYPE(DATA_TYPE_SELECT, 2))); |
| in.s01 = select(in.s23, in.s01, idx_sel.s01); |
| res.s01 = select(res.s23, res.s01, CONVERT(idx_sel.s01, int2)); |
| |
| idx_sel.s0 = (in.s0 > in.s1) || (in.s0 == in.s1 && CONVERT((res.s0 < res.s1), DATA_TYPE_SELECT)); |
| res.s0 = select(res.s1, res.s0, CONVERT(idx_sel.s0, int)); |
| |
| return res.s0 + x_elem; |
| #endif // WIDTH < 16 |
| } |
| #endif // defined(PREV_OUTPUT) |
| #endif // defined(ARG_MAX) |
| |
| /** This kernel performs parallel reduction given an operation on x-axis. |
| * |
| * @note In case the results of previous stages are passed the flag PREV_OUTPUT has to be passed using -DPREV_OUTPUT |
| * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| * @note The data type of the output must be passed at compile time using -DDATA_TYPE_OUTPUT: e.g. -DDATA_TYPE_OUTPUT=uint |
| * @note The arg_max flag must be passed at compile time using -DARG_MAX if we want to compute the ArgMax |
| * @note The arg_min flag must be passed at compile time using -DARG_MIN if we want to compute the ArgMin |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/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] prev_res_ptr (Optional) Pointer to previous results tensor. Supported data types: U32/S32 |
| * @param[in] prev_res_stride_x (Optional) Stride of the output tensor in X dimension (in bytes) |
| * @param[in] prev_res_step_x (Optional) prev_res_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] prev_res_stride_y (Optional) Stride of the output tensor in Y dimension (in bytes) |
| * @param[in] prev_res_step_y (Optional) prev_res_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] prev_res_offset_first_element_in_bytes (Optional) The offset of the first element in the previous results tensor |
| * @param[in] partial_res_ptr The local buffer to hold partial result values. Supported data types: U32/S32 |
| * @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 arg_min_max_x( |
| IMAGE_DECLARATION(src), |
| #if defined(PREV_OUTPUT) |
| IMAGE_DECLARATION(prev_res), |
| #endif // defined(PREV_OUTPUT) |
| IMAGE_DECLARATION(partial_res), |
| __local DATA_TYPE_OUTPUT *local_results) |
| { |
| #if defined(PREV_OUTPUT) |
| Image src = CONVERT_TO_IMAGE_STRUCT_NO_STEP(src); |
| Image prev_res = CONVERT_TO_IMAGE_STRUCT(prev_res); |
| #else // !defined(PREV_OUTPUT) |
| Image src = CONVERT_TO_IMAGE_STRUCT(src); |
| #endif // defined(PREV_OUTPUT) |
| Image partial_res = CONVERT_TO_IMAGE_STRUCT(partial_res); |
| |
| unsigned int lsize = get_local_size(0); |
| unsigned int lid = get_local_id(0); |
| |
| const uint x_idx = get_global_id(0); |
| const uint y_idx = get_global_id(1); |
| const __global DATA_TYPE *src_in_row = (const __global DATA_TYPE *)(src_ptr + src_offset_first_element_in_bytes + y_idx * src_step_y); |
| |
| for(unsigned int y = 0; y < get_local_size(1); ++y) |
| { |
| #if defined(ARG_MAX) |
| #if defined(PREV_OUTPUT) |
| local_results[lid] = arg_idx_max_prev_out(src_in_row, (__global DATA_TYPE_OUTPUT *)offset(&prev_res, 0, y), x_idx); |
| #else // !defined(PREV_OUTPUT) |
| local_results[lid] = arg_idx_max((__global DATA_TYPE *)offset(&src, 0, y), x_idx); |
| #endif // defined(PREV_OUTPUT) |
| #else // defined(ARG_MIN) |
| #if defined(PREV_OUTPUT) |
| local_results[lid] = arg_idx_min_prev_out(src_in_row, (__global DATA_TYPE_OUTPUT *)offset(&prev_res, 0, y), x_idx); |
| #else // !defined(PREV_OUTPUT) |
| local_results[lid] = arg_idx_min((__global DATA_TYPE *)offset(&src, 0, y), x_idx); |
| #endif // defined(PREV_OUTPUT) |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| |
| barrier(CLK_LOCAL_MEM_FENCE); |
| |
| // Looking for the next highest power of 2 (maximum value of lsize is 8) |
| unsigned int middle = lsize - 1; |
| middle |= middle >> 1; |
| middle |= middle >> 2; |
| middle += 1; |
| // Perform parallel reduction |
| for(unsigned int i = middle; i > 0; i >>= 1) |
| { |
| if(lid < i && lid + i < lsize) |
| { |
| DATA_TYPE tmp0 = *(src_in_row + local_results[lid]); |
| DATA_TYPE tmp1 = *(src_in_row + local_results[lid + i]); |
| #if defined(ARG_MAX) |
| local_results[lid] = select( |
| local_results[lid], |
| local_results[lid + i], |
| ((tmp0 == tmp1) && (local_results[lid + i] < local_results[lid])) || (tmp0 < tmp1)); |
| #else // defined(ARG_MIN) |
| local_results[lid] = select( |
| local_results[lid], |
| local_results[lid + i], |
| ((tmp0 == tmp1) && (local_results[lid + i] < local_results[lid])) || (tmp0 > tmp1)); |
| #endif // defined(ARG_MAX) || defined(ARG_MIN) |
| } |
| barrier(CLK_LOCAL_MEM_FENCE); |
| } |
| |
| if(lid == 0) |
| { |
| ((__global DATA_TYPE_OUTPUT *)offset(&partial_res, get_group_id(0), y))[0] = local_results[0]; |
| } |
| } |
| } |
| #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 data type of the output must be passed at compile time using -DDATA_TYPE_OUTPUT: e.g. -DDATA_TYPE_OUTPUT=uint |
| * @note The data type of the select results must be passed at compile time using -DDATA_TYPE_SELECT: e.g. -DDATA_TYPE_SELECT=int |
| * @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/QASYMM8_SIGNED/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: U32/S32 |
| * @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 arg_min_max_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, 16) |
| res = CONVERT(vload16(0, (__global DATA_TYPE *)offset(&src, 0, 0)), VEC_DATA_TYPE(DATA_TYPE, 16)); |
| |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| indx = 0; |
| for(unsigned int y = 1; y < HEIGHT; ++y) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = CONVERT(vload16(0, (__global DATA_TYPE *)offset(&src, 0, y)), VEC_DATA_TYPE(DATA_TYPE, 16)); |
| |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| cond_conv = CONVERT(CONDITION_TO_USE(in, res), VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16)); |
| indx = select(indx, y, cond_conv); |
| res = select(res, in, CONDITION_TO_USE(in, res)); |
| } |
| |
| // Store result |
| vstore16(indx, 0, (__global DATA_TYPE_OUTPUT *)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 data type of the select results must be passed at compile time using -DDATA_TYPE_SELECT: e.g. -DDATA_TYPE_SELECT=int |
| * @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: U32/S32 |
| * @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 arg_min_max_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, 16) |
| res = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)), VEC_DATA_TYPE(DATA_TYPE, 16)); |
| |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| indx = 0; |
| for(DATA_TYPE_OUTPUT z = 1; z < DEPTH; ++z) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, z)), VEC_DATA_TYPE(DATA_TYPE, 16)); |
| |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| cond_conv = CONVERT(CONDITION_TO_USE(in, res), VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16)); |
| indx = select(indx, z, cond_conv); |
| res = select(res, in, CONDITION_TO_USE(in, res)); |
| } |
| |
| // Store result |
| vstore16(indx, 0, (__global DATA_TYPE_OUTPUT *)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 data type of the select results must be passed at compile time using -DDATA_TYPE_SELECT: e.g. -DDATA_TYPE_SELECT=int |
| * @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: U32/S32 |
| * @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 arg_min_max_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, 16) |
| res = CONVERT(vload16(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, 0, 0, 0)), VEC_DATA_TYPE(DATA_TYPE, 16)); |
| |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| indx = 0; |
| for(DATA_TYPE_OUTPUT w = 1; w < BATCH; ++w) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| in = CONVERT(vload16(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, 0, 0, w)), VEC_DATA_TYPE(DATA_TYPE, 16)); |
| |
| VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16) |
| cond_conv = CONVERT(CONDITION_TO_USE(in, res), VEC_DATA_TYPE(DATA_TYPE_OUTPUT, 16)); |
| indx = select(indx, w, cond_conv); |
| res = select(res, in, CONDITION_TO_USE(in, res)); |
| } |
| |
| // Store result |
| vstore16(indx, 0, (__global DATA_TYPE_OUTPUT *)output.ptr); |
| } |
| #endif /* defined(BATCH) && defined(DEPTH) */ |
| #endif /* defined(DATA_TYPE_OUTPUT) && defined(DATA_TYPE_SELECT) */ |