/* * Copyright (c) 2017-2018 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" #define MUL_OP(x, y) ((x) * (y)) #define ADD_OP(x, y) ((x) + (y)) #define DIV_OP(x, y) ((x) / (y)) #define POW_OP(x, y) pow((x), (y)) #define SQCVT_SAT(a) (a) #define LOAD_OP(offset, ptr) vload4(offset, ptr) #define STORE_OP(data, offset, ptr) vstore4(data, offset, ptr) #if defined(NUM_SLICES) /** Apply cross-map normalization. * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16 * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5 * @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192 * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA * * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/F32 * @param[in] input_stride_x Stride of the first 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 first 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 first 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 first source tensor * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr * @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_stride_z Stride of the destination 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 destination tensor */ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0; const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA); const int current_slice = get_global_id(2); const int left_slice = max(-(int)RADIUS, -current_slice); const int right_slice = min((int)RADIUS, (int)NUM_SLICES - 1 - current_slice); for(int i = left_slice; i <= right_slice; i++) { VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, 0, i)); acc = ADD_OP(acc, MUL_OP(values, values)); } acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) normalized = POW_OP(acc, beta_v); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized); STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr); } #endif /* defined(NUM_SLICES) */ #if defined(WIDTH_SIZE) /** Apply in-map normalization when tensors are in the NCHW data layout format. * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16 * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5 * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA * * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/F32 * @param[in] input_stride_x Stride of the first 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 first 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 first 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 first source tensor * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr * @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 first 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_stride_z Stride of the first source 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 destination tensor */ __kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0; const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA); const int current_col = get_global_id(0) << 2; const int left_pos = max(-(int)RADIUS, -3 - current_col); const int right_pos = min((int)RADIUS, (int)WIDTH_SIZE - 1 - current_col); #if defined(IN_MAP_2D) const int current_row = get_global_id(1); const int first_row = max(-(int)RADIUS, -current_row); const int last_row = min((int)RADIUS, (int)get_global_size(1) - 1 - current_row); #endif /* defined(IN_MAP_2D) */ #if defined(IN_MAP_2D) for(int j = first_row; j <= last_row; ++j) { #endif /* defined(IN_MAP_2D) */ for(int i = left_pos; i <= right_pos; ++i) { #if defined(IN_MAP_2D) VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, j, 0)); #else /* defined(IN_MAP_2D) */ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, 0, 0)); #endif /* defined(IN_MAP_2D) */ acc = ADD_OP(acc, MUL_OP(values, values)); } #if defined(IN_MAP_2D) } #endif /* defined(IN_MAP_2D) */ acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) normalized = POW_OP(acc, beta_v); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized); STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr); } #endif // defined(WIDTH_SIZE) #if defined(NUM_SLICES) /** Apply in-map normalization when tensors are in the NHWC data layout format. * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16 * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5 * @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192 * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA * * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/F32 * @param[in] input_stride_x Stride of the first 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 first 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 first 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 first source tensor * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr * @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 first 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_stride_z Stride of the first source 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 destination tensor */ __kernel void normalization_layer_in_map_nhwc(TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0; const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA); const int current_cols = get_global_id(1); const int first_col = max(-(int)RADIUS, -current_cols); const int last_col = min((int)RADIUS, (int)get_global_size(1) - 1 - current_cols); #if defined(IN_MAP_2D) const int current_rows = get_global_id(2); const int first_row = max(-(int)RADIUS, -current_rows); const int last_row = min((int)RADIUS, (int)NUM_SLICES - 1 - current_rows); #endif /* defined(IN_MAP_2D) */ #if defined(IN_MAP_2D) for(int j = first_row; j <= last_row; ++j) { #endif /* defined(IN_MAP_2D) */ for(int i = first_col; i <= last_col; ++i) { #if defined(IN_MAP_2D) VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, j)); #else /* defined(IN_MAP_2D) */ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, 0)); #endif /* defined(IN_MAP_2D) */ acc = ADD_OP(acc, MUL_OP(values, values)); } #if defined(IN_MAP_2D) } #endif /* defined(IN_MAP_2D) */ acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) normalized = POW_OP(acc, beta_v); const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized); STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr); } #endif /* defined(NUM_SLICES) */