| /* |
| * Copyright (c) 2017-2018 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 |
| |
| #if defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) |
| |
| #if 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_PIXEL extract_input_stride3 |
| #elif STRIDE_X == 2 |
| #define INPUT_PIXEL extract_input_stride2 |
| #elif STRIDE_X == 1 |
| #define INPUT_PIXEL 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_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline uchar8 extract_input_stride1(__global const uchar *input_pixel) |
| { |
| return vload8(0, input_pixel); |
| } |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 2. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline uchar8 extract_input_stride2(__global const uchar *input_pixel) |
| { |
| uchar16 temp = vload16(0, input_pixel); |
| return temp.s02468ace; |
| } |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline uchar8 extract_input_stride3(__global const uchar *input_pixel) |
| { |
| uchar16 temp1 = vload16(0, input_pixel); |
| uchar16 temp2 = vload16(0, input_pixel + 12); |
| return (uchar8)(temp1.s0369, temp2.s0369); |
| } |
| |
| #else /* KERNEL_SIZE not equals 1, 3 or 5 */ |
| #error "Only kernel sizes 1, 3 and 5 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 |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8 |
| * @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 weights_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 |
| * @param[in] output_multiplier Output integer multiplier quantization parameter |
| * @param[in] output_shift Output integer shift quantization parameter |
| */ |
| __kernel void direct_convolution_1x1_3x3_5x5_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, |
| int output_multiplier, |
| int output_shift) |
| { |
| Image src = CONVERT_TO_IMAGE_STRUCT(src); |
| Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights); |
| Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); |
| |
| int8 pixels0 = 0; |
| |
| __global uchar *weights_addr = (__global uchar *)tensor3D_offset(&weights, 0, 0, 0); |
| __global uchar *src_addr = (__global uchar *)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 == 5 |
| CONVOLUTION1x5(pixels0, (__global uchar *)src_addr, (__global uchar *)weights_addr); |
| CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 1 * src_stride_y), (__global uchar *)(weights_addr + 1 * weights_stride_y)); |
| CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 2 * src_stride_y), (__global uchar *)(weights_addr + 2 * weights_stride_y)); |
| CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 3 * src_stride_y), (__global uchar *)(weights_addr + 3 * weights_stride_y)); |
| CONVOLUTION1x5(pixels0, (__global uchar *)(src_addr + 4 * src_stride_y), (__global uchar *)(weights_addr + 4 * weights_stride_y)); |
| #elif KERNEL_SIZE == 3 |
| CONVOLUTION1x3(pixels0, (__global uchar *)(src_addr + 0 * src_stride_y), (__global uchar *)(weights_addr + 0 * weights_stride_y)); |
| CONVOLUTION1x3(pixels0, (__global uchar *)(src_addr + 1 * src_stride_y), (__global uchar *)(weights_addr + 1 * weights_stride_y)); |
| CONVOLUTION1x3(pixels0, (__global uchar *)(src_addr + 2 * src_stride_y), (__global uchar *)(weights_addr + 2 * weights_stride_y)); |
| #elif KERNEL_SIZE == 1 |
| int weight = convert_int(*(__global uchar *)weights_addr); |
| int8 input_pixel = convert_int8(INPUT_PIXEL((__global uchar *)src_addr)); |
| pixels0 += (input_pixel + 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))); |
| pixels0 += (int8)(*bias_addr); |
| #endif /* defined(HAS_BIAS) */ |
| |
| pixels0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(pixels0, output_multiplier, output_shift, 8); |
| pixels0 = pixels0 + output_offset; |
| |
| vstore8(convert_uchar8_sat(pixels0), 0, (__global uchar *)dst.ptr); |
| } |
| #endif // defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) |
| |
| /** This function computes the output stage of a depthwise convolution. |
| * |
| * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8 |
| * @param[in] src_stride_x Stride of the source image 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 image 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_offset_first_element_in_bytes The offset of the first element in the source image |
| * @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 Y processed per workitem(in bytes) |
| * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: QASYMM8 |
| * @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 Y 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 Y 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] bias_ptr (Optional) Pointer to the biases vector. Supported data types: S32 |
| * @param[in] bias_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) |
| * @param[in] bias_step_x (Optional) bias_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector |
| * @param[in] output_offset Quantized offset of zero point of the output tensor data range |
| * @param[in] output_multiplier Output scale multiplier |
| * @param[in] output_shift Output scale divisor exponent |
| */ |
| |
| __kernel void output_stage_quantized( |
| TENSOR3D_DECLARATION(src), |
| TENSOR3D_DECLARATION(dst), |
| #if defined(HAS_BIAS) |
| VECTOR_DECLARATION(bias), |
| #endif //defined(HAS_BIAS) |
| int output_offset, |
| int output_multiplier, |
| int output_shift) |
| { |
| Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src); |
| Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); |
| #if defined(HAS_BIAS) |
| Vector bias = CONVERT_TO_VECTOR_STRUCT_NO_STEP(bias); |
| #endif //defined(HAS_BIAS) |
| |
| // Load input |
| int16 vals = vload16(0, (__global int *)(src.ptr)); |
| |
| #if defined(HAS_BIAS) |
| // Load and add bias |
| #if defined(NCHW) |
| int bias_value = *((__global int *)(vector_offset(&bias, get_global_id(2)))); |
| #else // defined(NCHW) |
| int16 bias_value = vload16(0, ((__global int *)(vector_offset(&bias, get_global_id(0) * 16)))); |
| #endif // defined(NCHW) |
| |
| vals += (int16)(bias_value); |
| #endif //defined(HAS_BIAS) |
| |
| vals = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(vals, output_multiplier, output_shift, 16); |
| vals = vals + output_offset; |
| |
| // Store result in dst |
| vstore16(convert_uchar16_sat(vals), 0, (__global uchar *)dst.ptr); |
| } |