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Diffstat (limited to 'src/core/CL/cl_kernels/nchw/normalization_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/nchw/normalization_layer.cl | 174 |
1 files changed, 174 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nchw/normalization_layer.cl b/src/core/CL/cl_kernels/nchw/normalization_layer.cl new file mode 100644 index 0000000000..deada49db5 --- /dev/null +++ b/src/core/CL/cl_kernels/nchw/normalization_layer.cl @@ -0,0 +1,174 @@ +/* + * Copyright (c) 2017-2021 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 "tile_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) + +#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_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_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 = VLOAD(VEC_SIZE)(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(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), normalized); + + VSTORE(VEC_SIZE) + (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 + * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER is; x_dimension % VEC_SIZE. e.g. -DVEC_SIZE_LEFTOVER=1 + * + * @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 = 0; + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + coeff_v = SQCVT_SAT(COEFF); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + beta_v = SQCVT_SAT(BETA); + const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + kappa_v = SQCVT_SAT(KAPPA); + + const int left_pos = -(int)RADIUS; + const int right_pos = (int)RADIUS; + +#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 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, j, 0)); +#else /* defined(IN_MAP_2D) */ + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + values = VLOAD(VEC_SIZE)(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(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr), normalized); + + VSTORE(VEC_SIZE) + (normalized_pixel, 0, (__global DATA_TYPE *)out.ptr); +} +#endif // defined(WIDTH_SIZE)
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