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Diffstat (limited to 'src/core/CL/cl_kernels/normalization_layer.cl')
-rw-r--r-- | src/core/CL/cl_kernels/normalization_layer.cl | 154 |
1 files changed, 154 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/normalization_layer.cl b/src/core/CL/cl_kernels/normalization_layer.cl new file mode 100644 index 0000000000..076b0d8909 --- /dev/null +++ b/src/core/CL/cl_kernels/normalization_layer.cl @@ -0,0 +1,154 @@ +/* + * Copyright (c) 2017 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" + +/** Apply cross map normalization. + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * + * @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[in] squared_input_ptr Pointer to the second source tensor. Supported data types: F16, F32 + * @param[in] squared_input_stride_x Stride of the second source tensor in X dimension (in bytes) + * @param[in] squared_input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] squared_input_stride_y Stride of the second source tensor in Y dimension (in bytes) + * @param[in] squared_input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] squared_input_stride_z Stride of the second source tensor in Z dimension (in bytes) + * @param[in] squared_input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] squared_input_offset_first_element_in_bytes The offset of the second element in the second source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F16, F32 + * @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 + * @param[in] coeff Alpha parameter / norm_size + * @param[in] beta Beta parameter in the normalization equation + * @param[in] kappa Kappa parameter in the normalization equation + * @param[in] radius Number of elements on the right or left side to normalize across + */ +__kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input), + TENSOR3D_DECLARATION(squared_input), + TENSOR3D_DECLARATION(output), + float coeff, + float beta, + float kappa, + uint radius) +{ + Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor3D squared_in = CONVERT_TO_TENSOR3D_STRUCT(squared_input); + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); + + DATA_TYPE acc = 0; + + const int num_of_slices = get_global_size(2); + const int current_slice = get_global_id(2); + + const int left_slice = max(current_slice - (int)radius, (int)0); + const int right_slice = min(current_slice + (int)radius, (int)(num_of_slices - 1)); + + for(int i = left_slice; i <= right_slice; i++) + { + acc += *(__global DATA_TYPE *)tensor3D_offset(&squared_in, 0, 0, i - current_slice); + } + + const float normalized = pow(kappa + coeff * (float)acc, beta); + + const float normalized_pixel = (float) * ((__global DATA_TYPE *)in.ptr) / normalized; + + *(__global DATA_TYPE *)out.ptr = CONVERT(normalized_pixel, DATA_TYPE); +} + +/** Apply in map normalization. + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * + * @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[in] squared_input_ptr Pointer to the second source tensor. Supported data types: F16, F32 + * @param[in] squared_input_stride_x Stride of the second source tensor in X dimension (in bytes) + * @param[in] squared_input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] squared_input_stride_y Stride of the second source tensor in Y dimension (in bytes) + * @param[in] squared_input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] squared_input_stride_z Stride of the second source tensor in Z dimension (in bytes) + * @param[in] squared_input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] squared_input_offset_first_element_in_bytes The offset of the second element in the second source tensor + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F16, F32 + * @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 + * @param[in] coeff Alpha parameter / norm_size + * @param[in] beta Beta parameter in the normalization equation + * @param[in] kappa Kappa parameter in the normalization equation + * @param[in] radius Number of elements on the right or left side to normalize across + */ +__kernel void normalization_layer_in_map_1D(TENSOR3D_DECLARATION(input), + TENSOR3D_DECLARATION(squared_input), + TENSOR3D_DECLARATION(output), + float coeff, + float beta, + float kappa, + uint radius) +{ + Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor3D squared_in = CONVERT_TO_TENSOR3D_STRUCT(squared_input); + Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); + + VEC_DATA_TYPE(DATA_TYPE, 4) + acc_vec = 0; + + const int current_pos = get_global_id(0) << 2; + + const int left_pos = max(current_pos - (int)radius, -3); + const int right_pos = min(current_pos + (int)radius, (int)((get_global_size(0) << 2) + 3 - 1)); + + for(int i = left_pos; i <= right_pos; i += 1) + { + acc_vec += vload4(0, (__global DATA_TYPE *)tensor3D_offset(&squared_in, i - current_pos, 0, 0)); + } + + const float4 normalized = pow((float4)kappa + coeff * (float4)acc_vec, beta); + + const float4 normalized_pixel = CONVERT(vload4(0, (__global DATA_TYPE *)in.ptr), float4) / normalized; + + vstore4(CONVERT(normalized_pixel, VEC_DATA_TYPE(DATA_TYPE, 4)), 0, (__global DATA_TYPE *)out.ptr); +} |