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Diffstat (limited to 'libs/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl')
| -rw-r--r-- | libs/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl | 152 |
1 files changed, 152 insertions, 0 deletions
diff --git a/libs/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl b/libs/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl new file mode 100644 index 000000000..8bef49363 --- /dev/null +++ b/libs/ARMComputeEx/src/core/CL/cl_kernels/reduce_operation.cl @@ -0,0 +1,152 @@ +/* + * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved + * Copyright (c) 2016, 2017 ARM Limited. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +#include "helpers.h" + +#if defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(OP_CODE) +/** Perform reduce max/min + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * @attention Output tensor depth should be given as a preprocessor argument using -DDEPTH_OUT=size. e.g. -DDEPTH_OUT=16 + * @attention Operation type(code) specifying which operation to perform should be passed as preprocessor argument using + * -DOP_CODE = number. e.g. -DOP_CODE=1 + * + * @param[in] input_ptr Pointer to the source image. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32 + * @param[in] input_stride_x Stride of the source image 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 image 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 image + * @param[in] input_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] input_step_w output_stride_w * number of elements along W processed per workitem(in bytes) + * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination image 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 image 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 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_stride_w Stride of the source 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 destination image + * @param[in] axis Axis through which reduction occurs + * @param[in] dim Dimension across the axis to be reduced. + */ +__kernel void reduce_min_max(TENSOR4D_DECLARATION(input), + TENSOR4D_DECLARATION(output), + const int axis, + const int dim) +{ + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT(input, 0); + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT); + + int indices[4] = + { + get_global_id(0), + get_global_id(1), + get_global_id(2) % DEPTH_OUT, + get_global_id(2) / DEPTH_OUT, + }; + + DATA_TYPE value = *((__global DATA_TYPE *)tensor4D_offset(&in, indices[0], indices[1], indices[2], indices[3])); + for(int i = 1; i < dim; ++i) + { + indices[axis] = i; + + #if OP_CODE == 1 // REDUCE_MAX + value = max(value, *((__global DATA_TYPE *) + tensor4D_offset(&in, indices[0], indices[1], indices[2], indices[3]))); + + #elif OP_CODE == 2 // REDUCE_MIN + value = min(value, *((__global DATA_TYPE *) + tensor4D_offset(&in, indices[0], indices[1], indices[2], indices[3]))); + + #else // OP NOT SUPPORTED + return; + + #endif + } + + *((__global DATA_TYPE *)out.ptr) = value; +} + +/** Perform reduce sum/mean + * + * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * @attention Output tensor depth should be given as a preprocessor argument using -DDEPTH_OUT=size. e.g. -DDEPTH_OUT=16 + * @attention Operation type(code) specifying which operation to perform should be passed as preprocessor argument using + * -DOP_CODE = number. e.g. -DOP_CODE=1 + * + * @param[in] input_ptr Pointer to the source image. Supported data types: U8/S8/U16/S16/F16/U32/S32/F32 + * @param[in] input_stride_x Stride of the source image 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 image 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 image + * @param[in] input_stride_w Stride of the source tensor in W dimension (in bytes) + * @param[in] input_step_w output_stride_w * number of elements along W processed per workitem(in bytes) + * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr + * @param[in] output_stride_x Stride of the destination image 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 image 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 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_stride_w Stride of the source 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 destination image + * @param[in] axis Axis through which reduction occurs + * @param[in] dim Dimension across the axis to be reduced. + */ +__kernel void reduce_sum_mean(TENSOR4D_DECLARATION(input), + TENSOR4D_DECLARATION(output), + const int axis, + const int dim) +{ + Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT(input, 0); + Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT); + + int indices[4] = + { + get_global_id(0), + get_global_id(1), + get_global_id(2) % DEPTH_OUT, + get_global_id(2) / DEPTH_OUT, + }; + + DATA_TYPE sum_value = (DATA_TYPE)0; + for(int i = 0; i < dim; ++i) + { + indices[axis] = i; + sum_value += *((__global DATA_TYPE *)tensor4D_offset(&in, indices[0], indices[1], indices[2], indices[3])); + } + + #if OP_CODE == 3 // REDUCE_SUM + *((__global DATA_TYPE *)out.ptr) = sum_value; + + #elif OP_CODE == 4 // REDUCE_MEAN + *((__global DATA_TYPE *)out.ptr) = sum_value / CONVERT(dim, DATA_TYPE); + + #else // OP NOT SUPPORTED + return; + + #endif +} +#endif // defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(OP_CODE) |