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author | Anthony Barbier <anthony.barbier@arm.com> | 2017-09-04 18:44:23 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-09-17 13:03:09 +0100 |
commit | 6ff3b19ee6120edf015fad8caab2991faa3070af (patch) | |
tree | a7a6dcd16dfd56d79fa1b56a313caeebcc939b68 /src/core/CL/cl_kernels/softmax_layer.cl | |
download | ComputeLibrary-6ff3b19ee6120edf015fad8caab2991faa3070af.tar.gz |
COMPMID-344 Updated doxygen
Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae
Diffstat (limited to 'src/core/CL/cl_kernels/softmax_layer.cl')
-rw-r--r-- | src/core/CL/cl_kernels/softmax_layer.cl | 221 |
1 files changed, 221 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/softmax_layer.cl b/src/core/CL/cl_kernels/softmax_layer.cl new file mode 100644 index 0000000000..632b4a5374 --- /dev/null +++ b/src/core/CL/cl_kernels/softmax_layer.cl @@ -0,0 +1,221 @@ +/* + * 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" + +#if defined USE_F16 +#define MINVAL HALF_MIN +#define SELECT_DATA_TYPE short +#define DATA_TYPE half +#else +#define MINVAL FLT_MIN +#define SELECT_DATA_TYPE int +#define DATA_TYPE float +#endif + +__constant VEC_DATA_TYPE(DATA_TYPE, 16) type_min = (VEC_DATA_TYPE(DATA_TYPE, 16))(MINVAL); +__constant uint16 idx16 = (uint16)(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15); + +/** Identifies the maximum value across the 1st dimension. + * + * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * @note In case F16 is used -DUSE_HALF must be passed otherwise the kernel will default to used F32. + * @note In case the input is not multiple of 16 -DNON_MULTIPLE_OF_16 must be passed. + * + * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: 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[out] dst_ptr Pointer to the destination tensor slice. Supported data types: F16, F32 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] width Input image width + */ +__kernel void softmax_layer_max( + IMAGE_DECLARATION(src), + IMAGE_DECLARATION(dst), + uint width) +{ + Image src = CONVERT_TO_IMAGE_STRUCT(src); + Image dst = CONVERT_TO_IMAGE_STRUCT(dst); + + // Initialize local maximum + VEC_DATA_TYPE(DATA_TYPE, 16) + max_val = (VEC_DATA_TYPE(DATA_TYPE, 16))type_min; + + // Calculate max of row + const uint width4 = width >> 4; + for(uint i = 0; i < width4; i++) + { + VEC_DATA_TYPE(DATA_TYPE, 16) + data = vload16(0, (__global DATA_TYPE *)offset(&src, i << 4, 0)); + max_val = max(data, max_val); + } + +#if defined NON_MULTIPLE_OF_16 + // Handle non multiple of 16 + VEC_DATA_TYPE(DATA_TYPE, 16) + data = vload16(0, (__global DATA_TYPE *)offset(&src, width4 << 4, 0)); + VEC_DATA_TYPE(SELECT_DATA_TYPE, 16) + widx = CONVERT(((uint16)(width4 << 4) + idx16) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, 16)); + max_val = max(max_val, select(type_min, data, widx)); +#endif + + // Perform max reduction + max_val.s01234567 = max(max_val.s01234567, max_val.s89ABCDEF); + max_val.s0123 = max(max_val.s0123, max_val.s4567); + max_val.s01 = max(max_val.s01, max_val.s23); + max_val.s0 = max(max_val.s0, max_val.s1); + + // Store result + *((__global DATA_TYPE *)dst.ptr) = max_val.s0; +} + +/** Shifts the values of the input tensor by the max calculated in softmax_layer_max kernel, + * then gets the exponent of each element as sums all elements across each row. + * + * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * @note In case F16 is used -DUSE_HALF must be passed otherwise the kernel will default to used F32. + * @note In case the input is not multiple of 16 -DNON_MULTIPLE_OF_16 must be passed. + * + * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: 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] max_ptr Pointer to the max values tensor slice. Supported data types: F16, F32 + * @param[in] max_stride_x Stride of the max values tensor in X dimension (in bytes) + * @param[in] max_step_x max_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] max_stride_y Stride of the max values tensor in Y dimension (in bytes) + * @param[in] max_step_y max_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] max_offset_first_element_in_bytes The offset of the first element in the max values tensor + * @param[out] dst_ptr Pointer to the destination tensor slice. Supported data types: F16, F32 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[out] sum_ptr Pointer to the sum values tensor slice. Supported data types: F16, F32 + * @param[in] sum_stride_x Stride of the sum values tensor in X dimension (in bytes) + * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] sum_stride_y Stride of the sum values tensor in Y dimension (in bytes) + * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the sum values tensor + * @param[in] width Input image width + */ +__kernel void softmax_layer_shift_exp_sum( + IMAGE_DECLARATION(src), + IMAGE_DECLARATION(max), + IMAGE_DECLARATION(dst), + IMAGE_DECLARATION(sum), + uint width) +{ + Image src = CONVERT_TO_IMAGE_STRUCT(src); + Image dst = CONVERT_TO_IMAGE_STRUCT(dst); + Image max = CONVERT_TO_IMAGE_STRUCT(max); + Image sum = CONVERT_TO_IMAGE_STRUCT(sum); + + // Load max value of 1D logits vector (row) + DATA_TYPE max_val = *((__global DATA_TYPE *)offset(&max, 0, 0)); + + // Set sum vector + VEC_DATA_TYPE(DATA_TYPE, 16) + sum1D = 0; + + // Shift values, exp and sum + const uint width4 = width >> 4; + for(uint i = 0; i < width4; i++) + { + VEC_DATA_TYPE(DATA_TYPE, 16) + data = vload16(0, (__global DATA_TYPE *)offset(&src, i << 4, 0)); + data = exp(data - max_val); + vstore16(data, 0, (__global DATA_TYPE *)offset(&dst, i << 4, 0)); + sum1D += data; + } + +#if defined NON_MULTIPLE_OF_16 + // Handle non multiple of 16 + VEC_DATA_TYPE(DATA_TYPE, 16) + data = vload16(0, (__global DATA_TYPE *)offset(&src, width4 << 4, 0)); + data = exp(data - max_val); + VEC_DATA_TYPE(SELECT_DATA_TYPE, 16) + widx = CONVERT(((uint16)(width4 << 4) + idx16) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, 16)); + data = select(0, data, widx); + vstore16(data, 0, (__global DATA_TYPE *)offset(&dst, width4 << 4, 0)); + sum1D += data; +#endif + + // Perform min/max reduction + sum1D.s01234567 = sum1D.s01234567 + sum1D.s89ABCDEF; + sum1D.s0123 = sum1D.s0123 + sum1D.s4567; + sum1D.s01 = sum1D.s01 + sum1D.s23; + sum1D.s0 = sum1D.s0 + sum1D.s1; + + // Calculate and store result + *((__global DATA_TYPE *)sum.ptr) = sum1D.s0; +} + +/** Divides all the values of the input tensor by the sum calculated from softmax_layer_shift_exp_sum kernel. + * + * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short + * + * @param[in] src_ptr Pointer to the source tensor slice. Supported data types: 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] sum_ptr Pointer to the sum values tensor slice. Supported data types: F16, F32 + * @param[in] sum_stride_x Stride of the sum values tensor in X dimension (in bytes) + * @param[in] sum_step_x sum_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] sum_stride_y Stride of the sum values tensor in Y dimension (in bytes) + * @param[in] sum_step_y sum_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] sum_offset_first_element_in_bytes The offset of the first element in the sum values tensor + * @param[out] dst_ptr Pointer to the destination tensor slice. Supported data types: F16, F32 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void softmax_layer_norm( + IMAGE_DECLARATION(src), + IMAGE_DECLARATION(sum), + IMAGE_DECLARATION(dst)) +{ + Image src = CONVERT_TO_IMAGE_STRUCT(src); + Image dst = CONVERT_TO_IMAGE_STRUCT(dst); + Image sum = CONVERT_TO_IMAGE_STRUCT_NO_STEP(sum); + + // Load max value of 1D logits vector (row) + DATA_TYPE sum_val = *((__global DATA_TYPE *)offset(&sum, 0, get_global_id(1))); + VEC_DATA_TYPE(DATA_TYPE, 16) + data = vload16(0, (__global DATA_TYPE *)offset(&src, 0, 0)); + vstore16(data / sum_val, 0, (__global DATA_TYPE *)offset(&dst, 0, 0)); +} |