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Diffstat (limited to 'src/core/CL/cl_kernels/nchw/pooling_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/nchw/pooling_layer.cl | 331 |
1 files changed, 331 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nchw/pooling_layer.cl b/src/core/CL/cl_kernels/nchw/pooling_layer.cl new file mode 100644 index 0000000000..790ddb381a --- /dev/null +++ b/src/core/CL/cl_kernels/nchw/pooling_layer.cl @@ -0,0 +1,331 @@ +/* + * 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 "repeat.h" +#include "tile_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)) + +#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) */ + +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)); +} + +#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 tensor. Supported data types: F16/F32 + * @param[in] input_stride_x Stride of the 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 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 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 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 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 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) + +#if defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM) + +inline void offset_no_padding_nchw(const Tensor3D *input, uint *offset_top, uint *offset_bottom) +{ + const int pad_horiz = PAD_TENSOR_LEFT + PAD_TENSOR_RIGHT; + const int pad_vert = PAD_TENSOR_TOP + PAD_TENSOR_BOTTOM; + + const int x = get_global_id(0) * STRIDE_X; + const int y = get_global_id(1) * STRIDE_Y; + const int z = get_global_id(2); + + //x axis: width, y axis: height, z axis: component + const uint padded_offset = input->offset_first_element_in_bytes + + x * input->stride_x + + y * input->stride_y + + z * input->stride_z; + + const uint offset_base = padded_offset + - y * pad_horiz * sizeof(DATA_TYPE) /* Horizontal padding for each row */ + - PAD_TENSOR_TOP * input->stride_y /* top padding */ + - z * MAX_HEIGHT * pad_horiz * sizeof(DATA_TYPE) - z * pad_vert * input->stride_y /* Z plane padding */ + - PAD_TENSOR_LEFT * sizeof(DATA_TYPE); + +#if defined(TENSOR_CHANNEL) && defined(TENSOR_WIDTH) && defined(TENSOR_HEIGHT) + *offset_top = (uint)((offset_base / sizeof(DATA_TYPE)) % (TENSOR_CHANNEL * TENSOR_WIDTH * TENSOR_HEIGHT)); +#else /* defined(TENSOR_CHANNEL) && defined(TENSOR_WIDTH) && defined(TENSOR_HEIGHT) */ + *offset_top = (uint)(offset_base / sizeof(DATA_TYPE)); +#endif /* defined(TENSOR_CHANNEL) && defined(TENSOR_WIDTH) && defined(TENSOR_HEIGHT) */ + + *offset_bottom = *offset_top + input->stride_y / sizeof(DATA_TYPE) - pad_horiz; + + return; +} + +#endif //defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM) + +/** Performs a MAX pooling of pool size equal to 2, and record max value indices for NCHW. + * + * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=half. Supported data types are 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 Pool 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 Tensor padding values must be passed at compile time using PAD_TENSOR_LEFT, PAD_TENSOR_RIGHT, PAD_TENSOR_TOP and PAD_TENSOR_BOTTOM + * + * @param[in] input_ptr Pointer to the source tensor. Supported data types: F32 + * @param[in] input_stride_x Stride of the 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 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 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 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 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] indices_ptr Pointer to the indices tensor. Supported data types: U32 + * @param[in] indices_stride_x Stride of the indices tensor in X dimension (in bytes) + * @param[in] indices_step_x indices_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] indices_stride_y Stride of the indices tensor in Y dimension (in bytes) + * @param[in] indices_step_y indices_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] indices_stride_z Stride of the indices tensor in Z dimension (in bytes) + * @param[in] indices_step_z indices_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] indices_offset_first_element_in_bytes The offset of the first element in the indices tensor + */ +__kernel void pooling_layer_2_nchw_indices_fp32( + TENSOR3D_DECLARATION(input), + TENSOR3D_DECLARATION(output), + TENSOR3D_DECLARATION(indices)) +{ + // Get pixels pointer + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); + Tensor3D indices = CONVERT_TO_TENSOR3D_STRUCT(indices); + + // Load data + float2 data0 = VLOAD(2)(0, (__global float *)tensor3D_offset(&input, 0, 0, 0)); + float2 data1 = VLOAD(2)(0, (__global float *)tensor3D_offset(&input, 0, 1, 0)); + + // Perform calculations + float data0_max = POOL_OP(data0.s0, data0.s1); + float data1_max = POOL_OP(data1.s0, data1.s1); + float res = POOL_OP(data0_max, data1_max); + // Store result + *(__global float *)output.ptr = res; + +#if defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM) + + uint offset_top = 0; + uint offset_bottom = 0; + + offset_no_padding_nchw(&input, &offset_top, &offset_bottom); + + uint index0 = select(offset_top + 1, offset_top, isgreaterequal(data0.s0, data0.s1)); + uint index1 = select(offset_bottom + 1, offset_bottom, isgreaterequal(data1.s0, data1.s1)); + uint index = select(index1, index0, isgreaterequal(data0_max, data1_max)); + + *(__global uint *)indices.ptr = index; + +#endif //defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM) +} + +/** Performs a MAX pooling of pool size equal to 2, and record max value indices for NCHW. + * + * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=half. Supported data types are F16 + * @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 Pool 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 Tensor padding values must be passed at compile time using PAD_TENSOR_LEFT, PAD_TENSOR_RIGHT, PAD_TENSOR_TOP and PAD_TENSOR_BOTTOM + * + * @param[in] input_ptr Pointer to the source tensor. Supported data types: F16 + * @param[in] input_stride_x Stride of the 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 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 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 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 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] indices_ptr Pointer to the indices tensor. Supported data types: U32 + * @param[in] indices_stride_x Stride of the indices tensor in X dimension (in bytes) + * @param[in] indices_step_x indices_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] indices_stride_y Stride of the indices tensor in Y dimension (in bytes) + * @param[in] indices_step_y indices_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] indices_stride_z Stride of the indices tensor in Z dimension (in bytes) + * @param[in] indices_step_z indices_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] indices_offset_first_element_in_bytes The offset of the first element in the indices tensor + */ +__kernel void pooling_layer_2_nchw_indices_fp16( + TENSOR3D_DECLARATION(input), + TENSOR3D_DECLARATION(output), + TENSOR3D_DECLARATION(indices)) +{ + // Get pixels pointer + Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); + Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); + Tensor3D indices = CONVERT_TO_TENSOR3D_STRUCT(indices); + + // Load data + half2 data0 = VLOAD(2)(0, (__global half *)tensor3D_offset(&input, 0, 0, 0)); + half2 data1 = VLOAD(2)(0, (__global half *)tensor3D_offset(&input, 0, 1, 0)); + + // Perform calculations + half data0_max = POOL_OP(data0.s0, data0.s1); + half data1_max = POOL_OP(data1.s0, data1.s1); + half res = POOL_OP(data0_max, data1_max); + // Store result + *(__global half *)output.ptr = res; + +#if defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM) + + uint offset_top = 0; + uint offset_bottom = 0; + + offset_no_padding_nchw(&input, &offset_top, &offset_bottom); + + uint index0 = select(offset_top + 1, offset_top, isgreaterequal(data0.s0, data0.s1)); + uint index1 = select(offset_bottom + 1, offset_bottom, isgreaterequal(data1.s0, data1.s1)); + uint index = select(index1, index0, isgreaterequal(data0_max, data1_max)); + + *(__global uint *)indices.ptr = index; + +#endif //defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM) +}
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