/* * 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(DATA_TYPE) && defined(INITIAL_VALUE) #define VEC_TYPE(VEC_SIZE) VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) #if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) #define VEC_FLOAT(VEC_SIZE) VEC_DATA_TYPE(float, VEC_SIZE) #define VEC_INT(VEC_SIZE) VEC_DATA_TYPE(int, VEC_SIZE) #define CONVERT_RTE(x, type) (convert_##type##_rte((x))) #define CONVERT_DOWN(x, type) CONVERT_RTE(x, type) #define REQUANTIZE(VEC_SIZE, input, in_offset, out_offset, in_scale, out_scale, res) \ { \ const VEC_FLOAT(VEC_SIZE) in_f32 = (CONVERT(input, VEC_FLOAT(VEC_SIZE)) - (VEC_FLOAT(VEC_SIZE))((float)in_offset)) * (VEC_FLOAT(VEC_SIZE))((float)in_scale); \ const VEC_FLOAT(VEC_SIZE) out_f32 = in_f32 / ((VEC_FLOAT(VEC_SIZE))(float)out_scale) + ((VEC_FLOAT(VEC_SIZE))((float)out_offset)); \ res = CONVERT_SAT(CONVERT_DOWN(out_f32, VEC_INT(VEC_SIZE)), VEC_TYPE(VEC_SIZE)); \ } #endif /* defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) */ #if defined(POOL_AVG) #define POOL_OP(x, y) ((x) + (y)) #else /* defined(POOL_AVG) */ #define POOL_OP(x, y) (max((x), (y))) #endif /* defined(POOL_AVG) */ #define DIV_OP(x, y) (x * (1.f / y)) #if defined(POOL_L2) #error "L2 pooling is not supported" #endif /* defined(POOL_L2) */ int 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 N (NCHW) * * @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 Input data type must be passed at compile time using -DDAT_TYPE=type, e.g. -DDATA_TYPE=uchar * @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: QASYMM8/QASYMM8_SIGNED * @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_quantized_nchw( TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { // Get pixels pointer Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); int8 vdata = INITIAL_VALUE; int 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_TYPE(8) data = vload8(0, (__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0)); int8 data0 = convert_int8(data); vdata = POOL_OP(vdata, data0); } // Leftover for(; x < (int)POOL_SIZE_X; ++x) { DATA_TYPE data = *((__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0)); int data0 = convert_int(data); sdata = POOL_OP(sdata, data0); } } // Reduce result int4 reduce4 = POOL_OP(vdata.s0123, vdata.s4567); int2 reduce2 = POOL_OP(reduce4.s01, reduce4.s23); int res = POOL_OP(reduce2.s0, reduce2.s1); res = POOL_OP(res, sdata); #if defined(POOL_AVG) res = round(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) */ DATA_TYPE result_q8 = CONVERT(res, DATA_TYPE); #if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) const float result_f32 = convert_float(result_q8); const float input_offset = (float)OFFSET_IN1; const float input_scale = (float)SCALE_IN1; const float scale_out = (float)SCALE_OUT; const float offset_out = (float)OFFSET_OUT; const float in_f32 = (result_f32 - input_offset) * input_scale; const float out_f32 = in_f32 / scale_out + offset_out; result_q8 = CONVERT_SAT(convert_int_rte(out_f32), DATA_TYPE); #endif /* defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) */ *(__global DATA_TYPE *)output.ptr = result_q8; } #if defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DST_CHANNELS) && defined(DST_HEIGHT) && defined(DST_BATCH_SIZE) && defined(ACC_DATA_TYPE) /** Performs pooling layer of size equal to MxN. This OpenCL kernel can perform the following pooling types: * -# max, -DPOOL_MAX must be passed at compile time * -# average, -DPOOL_AVG must be passed at compile time. If padding has to be expluded, -DEXCLUDE_PADDING should be passed at compile time * * @note Datatype must be passed at compile type using -DDATA_TYPE e.g. -DDATA_TYPE=uchar. Supported data types are QASYMM8/QASYMM8_SIGNED * @note Accumulation data type must be passed at compile time using -DACC_DATA_TYPE e.g. -DACC_DATA_TYPE=int * @note Pool size must be passed at compile time using -DPOOL_SIZE_X and -DPOOL_SIZE_Y. e.g. -DPOOL_SIZE_X=4, -DPOOL_SIZE_Y=4 * @note Input tensor width and height must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT * @note Output tensor height, channels and batch size must be passed at compile time using -DDST_HEIGHT, -DDST_CHANNELS and -DDST_BATCH_SIZE * @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 Pool pads must be passed at compile time using -DPAD_X and -DPAD_Y * @note Vector size must be passed at compile time using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 * @note Leftover vector size must be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE * @note The initial value for the pooling operation must be passed at compile time using -DINITIAL_VALUE e.g. -DINITIAL_VALUE=0 * @note If the output has be requantized, -DOFFSET_IN1, -DOFFSET_OUT, -DSCALE_IN1 and -DSCALE_OUT muste be passed at compile time * * @param[in] input_ptr Pointer to the source image. Supported data types: QASYMM8/QASYMM8_SIGNED * @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_quantized_nhwc( TENSOR4D_DECLARATION(input), TENSOR4D_DECLARATION(output)) { // Note: If C is not multiple of VEC_SIZE, we shift back of VEC_SIZE_LEFTOVER elements to compute the leftover elements for get_global_id(0) == 0 // Note: If C is less than VEC_SIZE, VEC_SIZE should be SHRINKED to the closest smaller VEC_SIZE. This operation is performed on the host side int offset_c = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0) * sizeof(DATA_TYPE); int idx_out_w = get_global_id(1); #if DST_BATCH_SIZE != 1 // If batch size != 1, the batch size dimension is collapsed over the height dimension int idx_out_h = get_global_id(2) % DST_HEIGHT; int idx_out_n = get_global_id(2) / DST_HEIGHT; #else //DST_BATCH_SIZE != 1 int idx_out_h = get_global_id(2); int idx_out_n = 0; #endif // DST_BATCH_SIZE != 1 int idx_in_w = idx_out_w * STRIDE_X - PAD_X; int idx_in_h = idx_out_h * STRIDE_Y - PAD_Y; __global unsigned char *in_base_ptr = input_ptr + input_offset_first_element_in_bytes + offset_c + idx_out_n * input_stride_w; __global unsigned char *out_base_ptr = output_ptr + output_offset_first_element_in_bytes + offset_c + idx_out_w * output_stride_y + idx_out_h * output_stride_z + idx_out_n * output_stride_w; int pool_x_s = max((int)0, -idx_in_w); int pool_x_e = min((int)POOL_SIZE_X, (int)SRC_WIDTH - idx_in_w); int pool_y_s = max((int)0, -idx_in_h); int pool_y_e = min((int)POOL_SIZE_Y, (int)SRC_HEIGHT - idx_in_h); #if defined(POOL_AVG) && defined(EXCLUDE_PADDING) int filter_size = 0; #elif defined(POOL_AVG) && !defined(EXCLUDE_PADDING) // defined(POOL_AVG) && defined(EXCLUDE_PADDING) int filter_size = POOL_SIZE_X * POOL_SIZE_Y; #endif // defined(POOL_AVG) && !defined(EXCLUDE_PADDING) VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) res0 = INITIAL_VALUE; for(int y = pool_y_s; y < pool_y_e; ++y) { for(int x = pool_x_s; x < pool_x_e; ++x) { VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) data; VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) data0; data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(in_base_ptr + (x + idx_in_w) * input_stride_y + (y + idx_in_h) * input_stride_z)); data0 = CONVERT(data, VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)); res0 = POOL_OP(res0, data0); #if defined(POOL_AVG) && defined(EXCLUDE_PADDING) filter_size++; #endif // defined(POOL_AVG) && defined(EXCLUDE_PADDING) } } #if defined(POOL_AVG) res0 = (res0 + (VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE))(filter_size >> 1)) / filter_size; #endif // defined(POOL_AVG) VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) out_q0 = CONVERT(res0, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); #if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) REQUANTIZE(VEC_SIZE, out_q0, OFFSET_IN1, OFFSET_OUT, SCALE_IN1, SCALE_OUT, out_q0); #endif /* defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) */ // Store result STORE_VECTOR_SELECT(out_q, DATA_TYPE, out_base_ptr, VEC_SIZE, VEC_SIZE_LEFTOVER, ((VEC_SIZE_LEFTOVER != 0) && get_global_id(0) == 0)); } #endif // defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DST_CHANNELS) && defined(DST_HEIGHT) && defined(DST_BATCH_SIZE) && defined(ACC_DATA_TYPE) #endif // defined(DATA_TYPE) && defined(INITIAL_VALUE)