| /* |
| * 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) |
| } |