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Diffstat (limited to 'src/core/CL/cl_kernels/pooling_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/pooling_layer.cl | 598 |
1 files changed, 0 insertions, 598 deletions
diff --git a/src/core/CL/cl_kernels/pooling_layer.cl b/src/core/CL/cl_kernels/pooling_layer.cl deleted file mode 100644 index 207669e43e..0000000000 --- a/src/core/CL/cl_kernels/pooling_layer.cl +++ /dev/null @@ -1,598 +0,0 @@ -/* - * Copyright (c) 2017-2020 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(POOL_AVG) || defined(POOL_L2) -#define POOL_OP(x, y) ((x) + (y)) -#else /* defined(POOL_AVG) || defined(POOL_L2) */ -#define POOL_OP(x, y) (fmax((x), (y))) -#endif /* defined(POOL_AVG) || defined(POOL_L2) */ - -#if defined(POOL_L2) -#define POW2_OP(x, vec_size) ((x) * (x)) -#else /* defined(POOL_L2) */ -#define POW2_OP(x, vec_size) (x) -#endif /* defined(POOL_L2) */ - -#define DIV_OP(x, y) (x * (1.f / y)) -#define SQRT_OP(x) sqrt((x)) - -#define DIV_OP_NHWC(x, y) (x * (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(1.f / y)) - -#if STRIDE_X == 1 -#define POOLING3x3(res, input, output) POOLING3x3_STRIDE1(res, input, output) -#elif STRIDE_X == 2 /* STRIDE_X == 1 */ -#define POOLING3x3(res, input, output) POOLING3x3_STRIDE2(res, input, output) -#elif STRIDE_X == 3 /* STRIDE_X not equals 1 or 2 */ -#define POOLING3x3(res, input, output) POOLING3x3_STRIDE3(res, input, output) -#endif /* STRIDE_X == 3 */ - -#if defined(FP_MIXED_PRECISION) -#define CONVERT_TO_ACC_DATA_TYPE(x, n) CONVERT(x, VEC_DATA_TYPE(ACC_DATA_TYPE, n)) -#define VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(n, offset, ptr) \ - CONVERT_TO_ACC_DATA_TYPE(vload##n(offset, ptr), n) -#else /* defined(FP_MIXED_PRECISION) */ -#define VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(n, offset, ptr) vload##n(offset, ptr) -#endif /* defined(FP_MIXED_PRECISION) */ - -#define POOLING3x3_STRIDE1(res, input, output) \ - ({ \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - data00 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(4, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 2) \ - data01 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(2, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0) + 4); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - data10 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(4, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 2) \ - data11 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(2, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0) + 4); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - data20 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(4, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 2) \ - data21 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(2, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0) + 4); \ - data00 = POW2_OP(data00, 4); \ - data01 = POW2_OP(data01, 2); \ - data10 = POW2_OP(data10, 4); \ - data11 = POW2_OP(data11, 2); \ - data20 = POW2_OP(data20, 4); \ - data21 = POW2_OP(data21, 2); \ - \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - values00 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(data00.s01212323); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - values01 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data01.s0, data00.s3, data01.s01); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - values10 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(data10.s01212323); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - values11 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data11.s0, data10.s3, data11.s01); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - values20 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(data20.s01212323); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - values21 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data21.s0, data20.s3, data21.s01); \ - \ - values00 = POOL_OP(values00, values10); \ - values01 = POOL_OP(values01, values11); \ - values00 = POOL_OP(values00, values20); \ - values01 = POOL_OP(values01, values21); \ - \ - res = POOL_OP((VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(values00.s036, values01.s1), (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(values00.s147, values01.s2)); \ - res = POOL_OP(res, (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(values00.s25, values01.s03)); \ - }) - -#define POOLING3x3_STRIDE2(res, input, output) \ - ({ \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - data00 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); \ - ACC_DATA_TYPE data01 = (ACC_DATA_TYPE)(*((__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0) + 8)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - data10 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); \ - ACC_DATA_TYPE data11 = (ACC_DATA_TYPE)(*((__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0) + 8)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - data20 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); \ - ACC_DATA_TYPE data21 = (ACC_DATA_TYPE)(*((__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0) + 8)); \ - data00 = POW2_OP(data00, 8); \ - data01 = POW2_OP(data01, 1); \ - data10 = POW2_OP(data10, 8); \ - data11 = POW2_OP(data11, 1); \ - data20 = POW2_OP(data20, 8); \ - data21 = POW2_OP(data21, 1); \ - \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - values00 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(data00.s01223445); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - values01 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data00.s667, data01); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - values10 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(data10.s01223445); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - values11 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data10.s667, data11); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - values20 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 8))(data20.s01223445); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - values21 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data20.s667, data21); \ - \ - values00 = POOL_OP(values00, values10); \ - values01 = POOL_OP(values01, values11); \ - values00 = POOL_OP(values00, values20); \ - values01 = POOL_OP(values01, values21); \ - \ - res = POOL_OP((VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(values00.s036, values01.s1), (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(values00.s147, values01.s2)); \ - res = POOL_OP(res, (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(values00.s25, values01.s03)); \ - }) - -#define POOLING3x3_STRIDE3(res, input, output) \ - ({ \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - data00 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - data01 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(4, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0) + 8); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - data10 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - data11 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(4, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0) + 8); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) \ - data20 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); \ - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) \ - data21 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(4, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0) + 8); \ - data00 = POW2_OP(data00, 8); \ - data01 = POW2_OP(data01, 4); \ - data10 = POW2_OP(data10, 8); \ - data11 = POW2_OP(data11, 4); \ - data20 = POW2_OP(data20, 8); \ - data21 = POW2_OP(data21, 4); \ - \ - data00 = POOL_OP(data00, data10); \ - data01 = POOL_OP(data01, data11); \ - data00 = POOL_OP(data00, data20); \ - data01 = POOL_OP(data01, data21); \ - \ - res = POOL_OP((VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data00.s036, data01.s1), (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data00.s147, data01.s2)); \ - res = POOL_OP(res, (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(data00.s25, data01.s03)); \ - }) - -ACC_DATA_TYPE calculate_avg_scale(const int pool_size_x, const int pool_size_y, const int upper_bound_w, const int upper_bound_h, - const int pad_x, const int pad_y, const int stride_x, const int stride_y) -{ - int start_x = get_global_id(0) * stride_x - pad_x; - int start_y = get_global_id(1) * stride_y - pad_y; - const int end_x = min(start_x + pool_size_x, upper_bound_w); - const int end_y = min(start_y + pool_size_y, upper_bound_h); -#if defined(EXCLUDE_PADDING) - start_x = max(0, start_x); - start_y = max(0, start_y); -#endif /* defined(EXCLUDE_PADDING) */ - return ((end_y - start_y) * (end_x - start_x)); -} - -/** Performs a pooling function of pool size equal to 2. - * - * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16/F32; - * @note In case of average pooling the following information must be passed at compile time: - * -DPOOL_AVG or -DPOOL_L2 must be provided otherwise max pooling will be performed. - * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) - * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions - * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension - * - * @param[in] input_ptr Pointer to the source image. Supported data types: F16/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[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_offset_first_element_in_bytes The offset of the first element in the destination image - */ -__kernel void pooling_layer_2( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - // Get pixels pointer - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); - - // Load data - VEC_DATA_TYPE(ACC_DATA_TYPE, 2) - data0 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(2, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); - VEC_DATA_TYPE(ACC_DATA_TYPE, 2) - data1 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(2, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); - -#if defined(POOL_L2) - // Raise to power of 2 for L2 Pooling - data0 = POW2_OP(data0, 2); - data1 = POW2_OP(data1, 2); -#endif /* defined(POOL_L2) */ - - // Perform calculations - data0 = POOL_OP(data0, data1); - ACC_DATA_TYPE res = POOL_OP(data0.s0, data0.s1); - -#if defined(POOL_AVG) || defined(POOL_L2) - // Divide by pool region in case of average or l2 pooling - res = DIV_OP(res, calculate_avg_scale(2, 2, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); -#endif /* defined(POOL_AVG) || defined(POOL_L2) */ - -#if defined(POOL_L2) - // Take square root of the result in L2 pooling - res = SQRT_OP(res); -#endif /* defined(POOL_L2) */ - - // Store result - *(__global DATA_TYPE *)output.ptr = (DATA_TYPE)res; -} - -/** Performs a pooling function of pool size equal to 3 - * - * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16/F32; - * @note In case of average pooling the following information must be passed at compile time: - * -DPOOL_AVG or -DPOOL_L2 must be provided otherwise max pooling will be performed. - * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) - * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions - * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension - * - * @param[in] input_ptr Pointer to the source image. Supported data types: F16/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[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_offset_first_element_in_bytes The offset of the first element in the destination image - */ -__kernel void pooling_layer_3( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - // Get pixels pointer - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); - - // Load data - VEC_DATA_TYPE(ACC_DATA_TYPE, 3) - data0 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(3, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)); - VEC_DATA_TYPE(ACC_DATA_TYPE, 3) - data1 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(3, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 1, 0)); - VEC_DATA_TYPE(ACC_DATA_TYPE, 3) - data2 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(3, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 2, 0)); - -#if defined(POOL_L2) - // Raise to power of 2 for L2 Pooling - data0 = POW2_OP(data0, 3); - data1 = POW2_OP(data1, 3); - data2 = POW2_OP(data2, 3); -#endif /* defined(POOL_L2) */ - - // Perform calculations - data0 = POOL_OP(data0, data1); - data0 = POOL_OP(data0, data2); - ACC_DATA_TYPE res = POOL_OP(POOL_OP(data0.s0, data0.s1), data0.s2); - -#if defined(POOL_AVG) || defined(POOL_L2) - // Divide by pool region in case of average pooling - res = DIV_OP(res, calculate_avg_scale(3, 3, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); -#endif /* defined(POOL_AVG) || defined(POOL_L2) */ - -#if defined(POOL_L2) - // Take square root of the result in L2 pooling - res = SQRT_OP(res); -#endif /* defined(POOL_L2) */ - - // Store result - *(__global DATA_TYPE *)output.ptr = (DATA_TYPE)res; -} - -#if defined(POOLING3x3) - -#define CONVERT_OP(data_type) convert_##data_type##4 -#define CONVERT_VECTOR4(data_type) CONVERT_OP(data_type) - -VEC_DATA_TYPE(ACC_DATA_TYPE, 4) -calculate_avg_scale4(const int pool_size, const int upper_bound_w, const int upper_bound_h, - const int pad_x, const int pad_y, const int stride_x, const int stride_y) -{ - int4 start_x = ((int4)get_global_id(0) * 4 + (int4)(0, 1, 2, 3)) * (int4)stride_x - (int4)pad_x; - int start_y = get_global_id(1) * stride_y - pad_y; - const int4 end_x = min(start_x + (int4)pool_size, (int4)upper_bound_w); - const int end_y = min(start_y + pool_size, upper_bound_h); -#if defined(EXCLUDE_PADDING) - start_x = max((int4)0, start_x); - start_y = max(0, start_y); -#endif /* defined(EXCLUDE_PADDING) */ - return (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))(1.f) / CONVERT_VECTOR4(ACC_DATA_TYPE)(((int4)(end_y - start_y)) * (end_x - start_x)); -} - -/** Performs an optimized pooling function of pool size equal to 3 when the stride_x is less equal than 3 - * - * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16/F32; - * @note In case of average pooling the following information must be passed at compile time: - * -DPOOL_AVG or -DPOOL_L2 must be provided otherwise max pooling will be performed. - * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) - * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions - * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension - * - * @param[in] input_ptr Pointer to the source image. Supported data types: F16/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[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_offset_first_element_in_bytes The offset of the first element in the destination image - */ -__kernel void pooling_layer_optimized_3( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - // Get pixels pointer - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); - - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) - res; - - // Perform pooling 3x3 for 4 output elements - POOLING3x3(res, input, output); - -#if defined(POOL_AVG) || defined(POOL_L2) - // Divide by pool region in case of average pooling - res *= calculate_avg_scale4(3, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y); -#endif /* defined(POOL_AVG) || defined(POOL_L2) */ - -#if defined(POOL_L2) - // Take square root of the result in L2 pooling - res = SQRT_OP(res); -#endif /* defined(POOL_L2) */ - - vstore4(CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, 4)), 0, (__global DATA_TYPE *)output.ptr); -} -#endif // defined(POOLING3x3) - -#if defined(POOL_SIZE_X) && defined(POOL_SIZE_Y) - -/** Performs a pooling function of pool size equal to N (NCHW) - * - * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16/F32; - * @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13; - * @note In case of average pooling the following information must be passed at compile time: - * -DPOOL_AVG must be provided otherwise max pooling will be performed. - * -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad) - * -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions - * -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension - * @note The initial value for the pooling operation must be passed at compile time using -DINITIAL_VALUE e.g. -DINITIAL_VALUE=0 - * - * @param[in] input_ptr Pointer to the source image. Supported data types: F16/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[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_offset_first_element_in_bytes The offset of the first element in the destination image - */ -__kernel void pooling_layer_MxN_nchw( - TENSOR3D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - // Get pixels pointer - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); - - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) - vdata = INITIAL_VALUE; - ACC_DATA_TYPE sdata = INITIAL_VALUE; - - // Load data - for(int y = 0; y < POOL_SIZE_Y; y++) - { - int x = 0; - for(; x <= ((int)POOL_SIZE_X - 8); x += 8) - { - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) - data0 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0)); -#if defined(POOL_L2) - // Raise to power of 2 for L2 Pooling - data0 *= data0; -#endif /* defined(POOL_L2) */ - vdata = POOL_OP(vdata, data0); - } - - // Leftover - for(; x < (int)POOL_SIZE_X; ++x) - { - ACC_DATA_TYPE data0 = (ACC_DATA_TYPE)(*((__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0))); -#if defined(POOL_L2) - // Raise to power of 2 for L2 Pooling - data0 *= data0; -#endif /* defined(POOL_L2) */ - sdata = POOL_OP(sdata, data0); - } - } - - // Reduce result - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) - reduce4 = POOL_OP(vdata.s0123, vdata.s4567); - VEC_DATA_TYPE(ACC_DATA_TYPE, 2) - reduce2 = POOL_OP(reduce4.s01, reduce4.s23); - ACC_DATA_TYPE res = POOL_OP(reduce2.s0, reduce2.s1); - res = POOL_OP(res, sdata); - -#if defined(POOL_AVG) || defined(POOL_L2) - // Divide by pool region in case of average pooling - res = DIV_OP(res, calculate_avg_scale(POOL_SIZE_X, POOL_SIZE_Y, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); -#endif /* defined(POOL_AVG) || defined(POOL_L2) */ - -#if defined(POOL_L2) - // Take square root of the result in L2 pooling - res = SQRT_OP(res); -#endif /* defined(POOL_L2) */ - - // Store result - *(__global DATA_TYPE *)output.ptr = (DATA_TYPE)res; -} -#endif // defined(POOL_SIZE_X) && defined(POOL_SIZE_Y) - -ACC_DATA_TYPE calculate_avg_scale_nhwc(const int pool_size_x, const int pool_size_y, int upper_bound_w, int upper_bound_h, - const int pad_x, const int pad_y, const int stride_x, const int stride_y) -{ - int start_x = get_global_id(1) * stride_x - pad_x; -#if defined(DST_DEPTH) - int start_y = (get_global_id(2) % DST_DEPTH) * stride_y - pad_y; -#else /* defined(DST_DEPTH) */ - int start_y = get_global_id(2) * stride_y - pad_y; -#endif /* defined(DST_DEPTH) */ - -#if !defined(EXCLUDE_PADDING) - upper_bound_w += pad_x; - upper_bound_h += pad_y; -#endif /* defined(EXCLUDE_PADDING) */ - const int end_x = min(start_x + pool_size_x, upper_bound_w); - const int end_y = min(start_y + pool_size_y, upper_bound_h); -#if defined(EXCLUDE_PADDING) - start_x = max(0, start_x); - start_y = max(0, start_y); -#endif /* defined(EXCLUDE_PADDING) */ - return ((end_y - start_y) * (end_x - start_x)); -} - -/** Performs a pooling function of pool size equal to N (NHWC) - * - * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16/F32 - * @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13; - * @note Tensors width and height must be passed at compile time using -DMAX_WIDTH and -DMAX_HEIGHT - * @note Strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions - * @note Pad values must be passed at compile time using -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension - * @note In case of average pooling the following information must be passed at compile time: - * -DPOOL_AVG must be provided otherwise max pooling will be performed. - * @note The initial value for the pooling operation must be passed at compile time using -DINITIAL_VALUE e.g. -DINITIAL_VALUE=0 - * - * @param[in] input_ptr Pointer to the source image. Supported data types: F16/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_stride_w Stride of the source tensor in W dimension (in bytes) - * @param[in] input_step_w input_stride_w * number of elements along W processed per workitem(in bytes) - * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source image - * @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 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_stride_w Stride of the destination 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 - */ -__kernel void pooling_layer_MxN_nhwc( - TENSOR4D_DECLARATION(input), - TENSOR4D_DECLARATION(output)) -{ - // Get pixels pointer -#if defined(DST_DEPTH) - Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT(input, DST_DEPTH); - Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, DST_DEPTH); -#else /* defined(DST_DEPTH) */ - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); -#endif /* defined(DST_DEPTH) */ - - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) - vdata = INITIAL_VALUE; - - const int idx_width = get_global_id(1) * STRIDE_X; -#if defined(DST_DEPTH) - const int idx_height = (get_global_id(2) % DST_DEPTH) * STRIDE_Y; -#else /* defined(DST_DEPTH) */ - const int idx_height = get_global_id(2) * STRIDE_Y; -#endif /* defined(DST_DEPTH) */ - - for(int y = 0; y < POOL_SIZE_Y; ++y) - { - int y1 = select(y, PAD_Y - idx_height, y + idx_height - PAD_Y < 0 || y + idx_height - PAD_Y >= MAX_HEIGHT); - for(int x = 0; x < POOL_SIZE_X; ++x) - { - int x1 = select(x, PAD_X - idx_width - 1, x + idx_width - PAD_X < 0 || x + idx_width - PAD_X >= MAX_WIDTH); - x1 = select(x1, PAD_X - idx_width - 1, y != y1); - -#if defined(DST_DEPTH) - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) - data0 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y, 0)); -#else /* defined(DST_DEPTH) */ - VEC_DATA_TYPE(ACC_DATA_TYPE, 8) - data0 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, x1 - PAD_X, y1 - PAD_Y)); -#endif /* defined(DST_DEPTH) */ - -#if defined(POOL_L2) - // Raise to power of 2 for L2 Pooling - data0 *= data0; -#endif /* defined(POOL_L2) */ - vdata = POOL_OP(vdata, CONVERT(data0, VEC_DATA_TYPE(ACC_DATA_TYPE, 8))); - } - } - -#if defined(POOL_AVG) || defined(POOL_L2) - // Divide by pool region in case of average pooling - vdata = DIV_OP_NHWC(vdata, calculate_avg_scale_nhwc(POOL_SIZE_X, POOL_SIZE_Y, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)); -#endif /* defined(POOL_AVG) || defined(POOL_L2) */ - -#if defined(POOL_L2) - // Take square root of the result in L2 pooling - vdata = SQRT_OP(vdata); -#endif /* defined(POOL_L2) */ - - // Store result - vstore8(CONVERT(vdata, VEC_DATA_TYPE(DATA_TYPE, 8)), 0, (__global DATA_TYPE *)output.ptr); -} |