/* * 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_asymm.h" #undef CONVERT_SAT_STR #undef CONVERT_SAT #if defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT) #define CONVERT_SAT_STR(x, type) (convert_##type##8_sat((x))) #define CONVERT_SAT(x, type) CONVERT_SAT_STR(x, type) #if defined(DATA_LAYOUT_NHWC) #if KERNEL_SIZE == 5 #if STRIDE_X == 1 #define CONVOLUTION1x5(acc, src_ptr, weights_ptr) CONVOLUTION1x5_STRIDE1(acc, src_ptr, weights_ptr) #elif STRIDE_X == 2 #define CONVOLUTION1x5(acc, src_ptr, weights_ptr) CONVOLUTION1x5_STRIDE2(acc, src_ptr, weights_ptr) #else /* STRIDE_X not equals 1 or 2 */ #error "STRIDE_X larger than 2 is not supported" #endif /* STRIDE_X */ #define CONVOLUTION1x5_STRIDE1(acc, src_ptr, weights_ptr) \ ({ \ int4 weights_values0 = 0; \ int weights_value1 = 0; \ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \ weights_values0.s3 = convert_int(*(weights_ptr + 3 * weights_stride_y)); \ weights_value1 = convert_int(*(weights_ptr + 4 * weights_stride_y)); \ \ int8 src0 = 0; \ int4 src1 = 0; \ src0.s0 = convert_int(*(src_ptr + 0 * weights_stride_y)); \ src0.s1 = convert_int(*(src_ptr + 1 * weights_stride_y)); \ src0.s2 = convert_int(*(src_ptr + 2 * weights_stride_y)); \ src0.s3 = convert_int(*(src_ptr + 3 * weights_stride_y)); \ src0.s4 = convert_int(*(src_ptr + 4 * weights_stride_y)); \ src0.s5 = convert_int(*(src_ptr + 5 * weights_stride_y)); \ src0.s6 = convert_int(*(src_ptr + 6 * weights_stride_y)); \ src0.s7 = convert_int(*(src_ptr + 7 * weights_stride_y)); \ src1.s0 = convert_int(*(src_ptr + 8 * weights_stride_y)); \ src1.s1 = convert_int(*(src_ptr + 9 * weights_stride_y)); \ src1.s2 = convert_int(*(src_ptr + 10 * weights_stride_y)); \ src1.s3 = convert_int(*(src_ptr + 11 * weights_stride_y)); \ \ acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ acc += ((int8)(src0.s345, src0.s67, src1.s012) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \ acc += ((int8)(src0.s45, src0.s67, src1.s0123) + input_offset) * ((int8)weights_value1 + weight_offset); \ }) #define CONVOLUTION1x5_STRIDE2(acc, src_ptr, weights_ptr) \ ({ \ int4 weights_values0 = 0; \ int weights_value1 = 0; \ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \ weights_values0.s3 = convert_int(*(weights_ptr + 3 * weights_stride_y)); \ weights_value1 = convert_int(*(weights_ptr + 4 * weights_stride_y)); \ \ int16 src0 = 0; \ int4 src1 = 0; \ src0.s0 = convert_int(*(src_ptr + 0 * weights_stride_y)); \ src0.s1 = convert_int(*(src_ptr + 1 * weights_stride_y)); \ src0.s2 = convert_int(*(src_ptr + 2 * weights_stride_y)); \ src0.s3 = convert_int(*(src_ptr + 3 * weights_stride_y)); \ src0.s4 = convert_int(*(src_ptr + 4 * weights_stride_y)); \ src0.s5 = convert_int(*(src_ptr + 5 * weights_stride_y)); \ src0.s6 = convert_int(*(src_ptr + 6 * weights_stride_y)); \ src0.s7 = convert_int(*(src_ptr + 7 * weights_stride_y)); \ src0.s8 = convert_int(*(src_ptr + 8 * weights_stride_y)); \ src0.s9 = convert_int(*(src_ptr + 9 * weights_stride_y)); \ src0.sa = convert_int(*(src_ptr + 10 * weights_stride_y)); \ src0.sb = convert_int(*(src_ptr + 11 * weights_stride_y)); \ src0.sc = convert_int(*(src_ptr + 12 * weights_stride_y)); \ src0.sd = convert_int(*(src_ptr + 13 * weights_stride_y)); \ src0.se = convert_int(*(src_ptr + 14 * weights_stride_y)); \ src0.sf = convert_int(*(src_ptr + 15 * weights_stride_y)); \ src1.s0 = convert_int(*(src_ptr + 16 * weights_stride_y)); \ src1.s1 = convert_int(*(src_ptr + 17 * weights_stride_y)); \ src1.s2 = convert_int(*(src_ptr + 18 * weights_stride_y)); \ src1.s3 = convert_int(*(src_ptr + 19 * weights_stride_y)); \ \ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s2468, src0.sACE, src1.s0) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ acc += ((int8)(src0.s3579, src0.sBDF, src1.s1) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \ acc += ((int8)(src0.s468a, src0.sCE, src1.s02) + input_offset) * ((int8)weights_value1 + weight_offset); \ }) #elif KERNEL_SIZE == 3 #if STRIDE_X == 1 #define CONVOLUTION1x3(acc, src_ptr, weights_ptr) CONVOLUTION1x3_STRIDE1(acc, src_ptr, weights_ptr) #elif STRIDE_X == 2 #define CONVOLUTION1x3(acc, src_ptr, weights_ptr) CONVOLUTION1x3_STRIDE2(acc, src_ptr, weights_ptr) #else /* STRIDE_X not equals 1 or 2 */ #error "STRIDE_X larger than 2 is not supported" #endif /* STRIDE_X */ #define CONVOLUTION1x3_STRIDE1(acc, src_ptr, weights_ptr) \ ({ \ int3 weights_values0 = 0; \ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \ \ int8 src0 = 0; \ int2 src1 = 0; \ src0.s0 = convert_int(*(src_ptr + 0 * weights_stride_y)); \ src0.s1 = convert_int(*(src_ptr + 1 * weights_stride_y)); \ src0.s2 = convert_int(*(src_ptr + 2 * weights_stride_y)); \ src0.s3 = convert_int(*(src_ptr + 3 * weights_stride_y)); \ src0.s4 = convert_int(*(src_ptr + 4 * weights_stride_y)); \ src0.s5 = convert_int(*(src_ptr + 5 * weights_stride_y)); \ src0.s6 = convert_int(*(src_ptr + 6 * weights_stride_y)); \ src0.s7 = convert_int(*(src_ptr + 7 * weights_stride_y)); \ src1.s0 = convert_int(*(src_ptr + 8 * weights_stride_y)); \ src1.s1 = convert_int(*(src_ptr + 9 * weights_stride_y)); \ \ acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ }) #define CONVOLUTION1x3_STRIDE2(acc, src_ptr, weights_ptr) \ ({ \ int3 weights_values0 = 0; \ weights_values0.s0 = convert_int(*(weights_ptr + 0 * weights_stride_y)); \ weights_values0.s1 = convert_int(*(weights_ptr + 1 * weights_stride_y)); \ weights_values0.s2 = convert_int(*(weights_ptr + 2 * weights_stride_y)); \ \ int16 src0 = 0; \ int src1 = 0; \ src0.s0 = convert_int(*(src_ptr + 0 * src_stride_y)); \ src0.s1 = convert_int(*(src_ptr + 1 * src_stride_y)); \ src0.s2 = convert_int(*(src_ptr + 2 * src_stride_y)); \ src0.s3 = convert_int(*(src_ptr + 3 * src_stride_y)); \ src0.s4 = convert_int(*(src_ptr + 4 * src_stride_y)); \ src0.s5 = convert_int(*(src_ptr + 5 * src_stride_y)); \ src0.s6 = convert_int(*(src_ptr + 6 * src_stride_y)); \ src0.s7 = convert_int(*(src_ptr + 7 * src_stride_y)); \ src0.s8 = convert_int(*(src_ptr + 8 * src_stride_y)); \ src0.s9 = convert_int(*(src_ptr + 9 * src_stride_y)); \ src0.sa = convert_int(*(src_ptr + 10 * src_stride_y)); \ src0.sb = convert_int(*(src_ptr + 11 * src_stride_y)); \ src0.sc = convert_int(*(src_ptr + 12 * src_stride_y)); \ src0.sd = convert_int(*(src_ptr + 13 * src_stride_y)); \ src0.se = convert_int(*(src_ptr + 14 * src_stride_y)); \ src0.sf = convert_int(*(src_ptr + 15 * src_stride_y)); \ src1 = convert_int(*(src_ptr + 16 * src_stride_y)); \ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s2468, src0.sACE, src1) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ }) #elif KERNEL_SIZE == 1 #if STRIDE_X == 3 #define INPUT_VALUE extract_input_stride3 #elif STRIDE_X == 2 #define INPUT_VALUE extract_input_stride2 #elif STRIDE_X == 1 #define INPUT_VALUE extract_input_stride1 #else /* STRIDE_X not equals 1, 2 or 3 */ #error "Only support strides 1, 2 and 3" #endif /* STRIDE_X */ #endif // KERNEL_SIZE == 1 /** Extracts a 1D horizontal vector from the input tensor with stride as 1. * * @param[in] input_value Pointer to the first value. * * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_value, const uchar stride_y) { VEC_DATA_TYPE(DATA_TYPE, 8) vals; vals.s0 = *(input_value + 0 * stride_y); vals.s1 = *(input_value + 1 * stride_y); vals.s2 = *(input_value + 2 * stride_y); vals.s3 = *(input_value + 3 * stride_y); vals.s4 = *(input_value + 4 * stride_y); vals.s5 = *(input_value + 5 * stride_y); vals.s6 = *(input_value + 6 * stride_y); vals.s7 = *(input_value + 7 * stride_y); return vals; } /** Extracts a 1D horizontal vector from the input tensor with stride as 2. * * @param[in] input_value Pointer to the first value. * * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_value, const uchar stride_y) { VEC_DATA_TYPE(DATA_TYPE, 8) vals; vals.s0 = *(input_value + 0 * stride_y); vals.s1 = *(input_value + 2 * stride_y); vals.s2 = *(input_value + 4 * stride_y); vals.s3 = *(input_value + 6 * stride_y); vals.s4 = *(input_value + 8 * stride_y); vals.s5 = *(input_value + 10 * stride_y); vals.s6 = *(input_value + 12 * stride_y); vals.s7 = *(input_value + 14 * stride_y); return vals; } /** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size. * * @param[in] input_value Pointer to the first value. * * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3(__global const DATA_TYPE *input_value, const uchar stride_y) { VEC_DATA_TYPE(DATA_TYPE, 8) vals; vals.s0 = *(input_value + 0 * stride_y); vals.s1 = *(input_value + 3 * stride_y); vals.s2 = *(input_value + 6 * stride_y); vals.s3 = *(input_value + 9 * stride_y); vals.s4 = *(input_value + 12 * stride_y); vals.s5 = *(input_value + 15 * stride_y); vals.s6 = *(input_value + 18 * stride_y); vals.s7 = *(input_value + 21 * stride_y); return vals; } /** This kernel performs a direct convolution to convolve the low three dimensions. * * @note The convolution stride x must be passed at compile time using -DSTRIDE_X e.g. -DSTRIDE_X=1 * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH * @note If biases are used then -DHAS_BIAS has to be passed at compile time * @note The output quantization multiplier must be passed at compile time using -DOUTPUT_MULTIPLIER e.g. -DOUTPUT_MULTIPLIER=1234 * @note The output quantization shift must be passed at compile time using -DOUTPUT_SHIFT e.g. -DOUTPUT_SHIFT=4 * * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED * @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_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] src_step_z src_stride_z * number of elements along Z 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. Supported data types: same as @p src_ptr * @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 Z processed per workitem(in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_step_z dst_stride_z * number of elements along Z 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] weights_ptr Pointer to the weights tensor. Supported data types: same as @p src_ptr * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) * @param[in] weights_step_y weights_stride_y * number of elements along y processed per workitem(in bytes) * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) * @param[in] weights_step_z weights_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor * @param[in] biases_ptr Pointer to the biases tensor. Supported data types: S32 * @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes) * @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor * @param[in] weights_stride_w Stride of the weights tensor in the 4th dimension * @param[in] input_offset Input offset quantization parameter * @param[in] weight_offset Weights offset quantization parameter * @param[in] output_offset Output offset quantization parameter */ __kernel void direct_convolution_quantized( TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst), TENSOR3D_DECLARATION(weights), #ifdef HAS_BIAS VECTOR_DECLARATION(biases), #endif /* defined(HAS_BIAS) */ unsigned int weights_stride_w, int input_offset, int weight_offset, int output_offset) { Image src = CONVERT_TO_IMAGE_STRUCT(src); Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); int8 values0 = 0; const int id0 = get_global_id(0); const int y_coord = (get_global_id(2) * STRIDE_Y) - PAD_TOP; __global DATA_TYPE *weights_addr = (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 0, 0); __global DATA_TYPE *src_addr = (__global DATA_TYPE *)offset(&src, 0, 0) - src_stride_x * id0 + y_coord * (int)src_stride_z; weights_addr += id0 * weights_stride_w; for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d) { #if KERNEL_SIZE == 5 #if(PAD_TOP == 1) || (PAD_BOTTM == 1) if(y_coord < 0) // special case Z = -1 doesn't exists { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z)); } else if(get_global_id(2) == (DST_HEIGHT - 1)) { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); } else { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z)); } #elif(PAD_TOP == 2) || (PAD_BOTTM == 2) if(y_coord < -1) { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z)); } else if(y_coord == -1) { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z)); } else if(y_coord == (SRC_HEIGHT - 3)) { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); } else if(y_coord >= (SRC_HEIGHT - 4)) { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); } else { CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z)); } #else /* PAD_TOP == 2 || || PAD_BOTTM == 2 */ CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_z)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_z)); #endif /* PAD_TOP == 1 || || PAD_BOTTM == 1 */ #elif KERNEL_SIZE == 3 #if(PAD_TOP > 0) || (PAD_BOTTOM > 0) if(y_coord < 0) // special case Z = -1 doesn't exists { //skip first row and load the two next ones CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); } else if(y_coord == (SRC_HEIGHT - PAD_BOTTOM - 1)) { // special case when computing the last row of the output we must read the last three rows from the input buffer (including padding) but the // Z axis has no padding at all. CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); } else { CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); } #else // PAD_TOP > 0 || PAD_BOTTOM > 0 CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_z)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_z)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_z), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_z)); #endif // PAD_TOP > 0 || PAD_BOTTOM > 0 #elif KERNEL_SIZE == 1 int weight = convert_int(*(__global DATA_TYPE *)weights_addr); int8 input_value = convert_int8(INPUT_VALUE((__global DATA_TYPE *)src_addr, src_stride_y)); values0 += (input_value + input_offset) * ((int8)weight + weight_offset); #endif /* (KERNEL_SIZE == 1) || (KERNEL_SIZE == 3) || (KERNEL_SIZE == 5) */ src_addr += src_stride_x; weights_addr += weights_stride_x; } #ifdef HAS_BIAS Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); __global int *bias_addr = ((__global int *)(vector_offset(&biases, id0))); values0 += (int8)(*bias_addr); #endif /* defined(HAS_BIAS) */ #if OUTPUT_SHIFT < 0 values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8); #else // OUTPUT_SHIFT < 0 values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8); #endif // OUTPUT_SHIFT < 0 values0 = values0 + output_offset; VEC_DATA_TYPE(DATA_TYPE, 8) values = CONVERT_SAT(values0, DATA_TYPE); *(dst.ptr + 0 * dst_stride_y) = values.s0; *(dst.ptr + 1 * dst_stride_y) = values.s1; *(dst.ptr + 2 * dst_stride_y) = values.s2; *(dst.ptr + 3 * dst_stride_y) = values.s3; *(dst.ptr + 4 * dst_stride_y) = values.s4; *(dst.ptr + 5 * dst_stride_y) = values.s5; *(dst.ptr + 6 * dst_stride_y) = values.s6; *(dst.ptr + 7 * dst_stride_y) = values.s7; } #else // defined(DATA_LAYOUT_NHWC) #if KERNEL_SIZE == 9 #if STRIDE_X == 1 #define CONVOLUTION1x9(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x9_STRIDE1(acc, src_row_ptr, weights_row_ptr) #elif STRIDE_X == 2 #define CONVOLUTION1x9(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x9_STRIDE2(acc, src_row_ptr, weights_row_ptr) #else /* STRIDE_X not equals 1 or 2 */ #error "STRIDE_X larger than 2 is not supported" #endif /* STRIDE_X */ #define CONVOLUTION1x9_STRIDE1(acc, src_row_ptr, weights_row_ptr) \ ({ \ int8 weights_values0 = convert_int8(vload8(0, weights_row_ptr)); \ int weights_value1 = convert_int(*(weights_row_ptr + 8)); \ int16 src0 = convert_int16(vload16(0, src_row_ptr)); \ acc += (src0.lo + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1234, src0.s5678) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s2345, src0.s6789) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ acc += ((int8)(src0.s3456, src0.s789A) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \ acc += ((int8)(src0.s4567, src0.s89AB) + input_offset) * ((int8)weights_values0.s4 + weight_offset); \ acc += ((int8)(src0.s5678, src0.s9ABC) + input_offset) * ((int8)weights_values0.s5 + weight_offset); \ acc += ((int8)(src0.s6789, src0.sABCD) + input_offset) * ((int8)weights_values0.s6 + weight_offset); \ acc += ((int8)(src0.s789A, src0.sBCDE) + input_offset) * ((int8)weights_values0.s7 + weight_offset); \ acc += ((int8)(src0.s89AB, src0.sCDEF) + input_offset) * ((int8)weights_value1 + weight_offset); \ }) #define CONVOLUTION1x9_STRIDE2(acc, src_row_ptr, weights_row_ptr) \ ({ \ int8 weights_values0 = convert_int8(vload8(0, weights_row_ptr)); \ int weights_value1 = convert_int(*(weights_row_ptr + 8)); \ int16 src0 = convert_int16(vload16(0, src_row_ptr)); \ int8 src1 = convert_int8(vload8(0, src_row_ptr + 16)); \ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s2468, src0.sACE, src1.s0) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ acc += ((int8)(src0.s3579, src0.sBDF, src1.s1) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \ acc += ((int8)(src0.s468A, src0.sCE, src1.s02) + input_offset) * ((int8)weights_values0.s4 + weight_offset); \ acc += ((int8)(src0.s579B, src0.sDF, src1.s13) + input_offset) * ((int8)weights_values0.s5 + weight_offset); \ acc += ((int8)(src0.s68AC, src0.sE, src1.s024) + input_offset) * ((int8)weights_values0.s6 + weight_offset); \ acc += ((int8)(src0.s79BD, src0.sF, src1.s135) + input_offset) * ((int8)weights_values0.s7 + weight_offset); \ acc += ((int8)(src0.s8ACE, src1.s0246) + input_offset) * ((int8)weights_value1 + weight_offset); \ }) #elif KERNEL_SIZE == 5 #if STRIDE_X == 1 #define CONVOLUTION1x5(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x5_STRIDE1(acc, src_row_ptr, weights_row_ptr) #elif STRIDE_X == 2 #define CONVOLUTION1x5(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x5_STRIDE2(acc, src_row_ptr, weights_row_ptr) #else /* STRIDE_X not equals 1 or 2 */ #error "STRIDE_X larger than 2 is not supported" #endif /* STRIDE_X */ #define CONVOLUTION1x5_STRIDE1(acc, src_row_ptr, weights_row_ptr) \ ({ \ int4 weights_values0 = convert_int4(vload4(0, weights_row_ptr)); \ int weights_value1 = convert_int(*(weights_row_ptr + 4)); \ int8 src0 = convert_int8(vload8(0, src_row_ptr)); \ int4 src1 = convert_int4(vload4(0, src_row_ptr + 8)); \ acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ acc += ((int8)(src0.s345, src0.s67, src1.s012) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \ acc += ((int8)(src0.s45, src0.s67, src1.s0123) + input_offset) * ((int8)weights_value1 + weight_offset); \ }) #define CONVOLUTION1x5_STRIDE2(acc, src_row_ptr, weights_row_ptr) \ ({ \ int4 weights_values0 = convert_int4(vload4(0, weights_row_ptr)); \ int weights_value1 = convert_int(*(weights_row_ptr + 4)); \ int16 src0 = convert_int16(vload16(0, src_row_ptr)); \ int4 src1 = convert_int4(vload4(0, src_row_ptr + 16)); \ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s2468, src0.sACE, src1.s0) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ acc += ((int8)(src0.s3579, src0.sBDF, src1.s1) + input_offset) * ((int8)weights_values0.s3 + weight_offset); \ acc += ((int8)(src0.s468a, src0.sCE, src1.s02) + input_offset) * ((int8)weights_value1 + weight_offset); \ }) #elif KERNEL_SIZE == 3 #if STRIDE_X == 1 #define CONVOLUTION1x3(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x3_STRIDE1(acc, src_row_ptr, weights_row_ptr) #elif STRIDE_X == 2 #define CONVOLUTION1x3(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x3_STRIDE2(acc, src_row_ptr, weights_row_ptr) #else /* STRIDE_X not equals 1 or 2 */ #error "STRIDE_X larger than 2 is not supported" #endif /* STRIDE_X */ #define CONVOLUTION1x3_STRIDE1(acc, src_row_ptr, weights_row_ptr) \ ({ \ int3 weights_values0 = convert_int3(vload3(0, weights_row_ptr)); \ int8 src0 = convert_int8(vload8(0, src_row_ptr)); \ int2 src1 = convert_int2(vload2(0, src_row_ptr + 8)); \ acc += (src0 + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1234, src0.s567, src1.s0) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s234, src0.s567, src1.s01) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ }) #define CONVOLUTION1x3_STRIDE2(acc, src_row_ptr, weights_row_ptr) \ ({ \ int3 weights_values0 = convert_int3(vload3(0, weights_row_ptr)); \ int16 src0 = convert_int16(vload16(0, src_row_ptr)); \ int src1 = convert_int(*(src_row_ptr + 16)); \ acc += (src0.even + input_offset) * ((int8)weights_values0.s0 + weight_offset); \ acc += ((int8)(src0.s1357, src0.s9BDF) + input_offset) * ((int8)weights_values0.s1 + weight_offset); \ acc += ((int8)(src0.s2468, src0.sACE, src1) + input_offset) * ((int8)weights_values0.s2 + weight_offset); \ }) #elif KERNEL_SIZE == 1 #if STRIDE_X == 3 #define INPUT_VALUE extract_input_stride3 #elif STRIDE_X == 2 #define INPUT_VALUE extract_input_stride2 #elif STRIDE_X == 1 #define INPUT_VALUE extract_input_stride1 #else /* STRIDE_X not equals 1, 2 or 3 */ #error "Only support strides 1, 2 and 3" #endif /* STRIDE_X */ /** Extracts a 1D horizontal vector from the input tensor with stride as 1. * * @param[in] input_value Pointer to the first value. * * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_value) { return vload8(0, input_value); } /** Extracts a 1D horizontal vector from the input tensor with stride as 2. * * @param[in] input_value Pointer to the first value. * * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_value) { VEC_DATA_TYPE(DATA_TYPE, 16) temp = vload16(0, input_value); return temp.s02468ace; } /** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size. * * @param[in] input_value Pointer to the first value. * * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3(__global const DATA_TYPE *input_value) { VEC_DATA_TYPE(DATA_TYPE, 16) temp1 = vload16(0, input_value); VEC_DATA_TYPE(DATA_TYPE, 16) temp2 = vload16(0, input_value + 12); return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s0369, temp2.s0369); } #else /* KERNEL_SIZE not equals 1, 3 , 5, 9 */ #error "Only kernel sizes 1, 3, 5 and 9 are supported" #endif /* KERNEL_SIZE */ /** This kernel performs a direct convolution to convolve the low three dimensions. * * @note The convolution stride x must be passed at compile time using -DSTRIDE_X e.g. -DSTRIDE_X=1 * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH * @note If biases are used then -DHAS_BIAS has to be passed at compile time * @note The output quantization multiplier must be passed at compile time using -DOUTPUT_MULTIPLIER e.g. -DOUTPUT_MULTIPLIER=1234 * @note The output quantization shift must be passed at compile time using -DOUTPUT_SHIFT e.g. -DOUTPUT_SHIFT=4 * * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED * @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_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] src_step_z src_stride_z * number of elements along Z 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. Supported data types: same as @p src_ptr * @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 Z processed per workitem(in bytes) * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] dst_step_z dst_stride_z * number of elements along Z 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] weights_ptr Pointer to the weights tensor. Supported data types: same as @p src_ptr * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) * @param[in] weights_step_y weights_stride_y * number of elements along y processed per workitem(in bytes) * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) * @param[in] weights_step_z weights_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor * @param[in] biases_ptr Pointer to the biases tensor. Supported data types: S32 * @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes) * @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor * @param[in] weights_stride_w Stride of the weights tensor in the 4th dimension * @param[in] input_offset Input offset quantization parameter * @param[in] weight_offset Weights offset quantization parameter * @param[in] output_offset Output offset quantization parameter */ __kernel void direct_convolution_quantized( TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst), TENSOR3D_DECLARATION(weights), #ifdef HAS_BIAS VECTOR_DECLARATION(biases), #endif /* defined(HAS_BIAS) */ unsigned int weights_stride_w, int input_offset, int weight_offset, int output_offset) { Image src = CONVERT_TO_IMAGE_STRUCT(src); Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); int8 values0 = 0; __global DATA_TYPE *weights_addr = (__global DATA_TYPE *)tensor3D_offset(&weights, 0, 0, 0); __global DATA_TYPE *src_addr = (__global DATA_TYPE *)offset(&src, 0, 0); const int kernel_index = get_global_id(2); weights_addr += kernel_index * weights_stride_w; for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d) { #if KERNEL_SIZE == 9 CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 5 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 5 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 6 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 6 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 7 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 7 * weights_stride_y)); CONVOLUTION1x9(values0, (__global DATA_TYPE *)(src_addr + 8 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 8 * weights_stride_y)); #elif KERNEL_SIZE == 5 CONVOLUTION1x5(values0, (__global DATA_TYPE *)src_addr, (__global DATA_TYPE *)weights_addr); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 3 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 3 * weights_stride_y)); CONVOLUTION1x5(values0, (__global DATA_TYPE *)(src_addr + 4 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 4 * weights_stride_y)); #elif KERNEL_SIZE == 3 CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y)); CONVOLUTION1x3(values0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y)); #elif KERNEL_SIZE == 1 int weight = convert_int(*(__global DATA_TYPE *)weights_addr); int8 input_value = convert_int8(INPUT_VALUE((__global DATA_TYPE *)src_addr)); values0 += (input_value + input_offset) * ((int8)weight + weight_offset); #endif /* (KERNEL_SIZE == 1) || (KERNEL_SIZE == 3) || (KERNEL_SIZE == 5) */ src_addr += src_stride_z; weights_addr += weights_stride_z; } #ifdef HAS_BIAS Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); __global int *bias_addr = ((__global int *)(vector_offset(&biases, kernel_index))); values0 += (int8)(*bias_addr); #endif /* defined(HAS_BIAS) */ #if OUTPUT_SHIFT < 0 values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8); #else // OUTPUT_SHIFT < 0 values0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(values0, OUTPUT_MULTIPLIER, OUTPUT_SHIFT, 8); #endif // OUTPUT_SHIFT < 0 values0 = values0 + output_offset; vstore8(CONVERT_SAT(values0, DATA_TYPE), 0, (__global DATA_TYPE *)dst.ptr); } #endif // defined(DATA_LAYOUT_NHWC) #endif // defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) && defined(OUTPUT_MULTIPLIER) && defined(OUTPUT_SHIFT)