feat: 集成Tesseract源码到项目中
Description: 由于仓库中的Tesseract不是最新版本导致产生了一个bug,因此将Tesseract源码集成到项目中 Log: no Change-Id: I088de95d6c6ab670406daa8d47ed2ed46929c2c0
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3rdparty/tesseract_ocr/tesseract/src/arch/intsimdmatrixsse.cpp
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106
3rdparty/tesseract_ocr/tesseract/src/arch/intsimdmatrixsse.cpp
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///////////////////////////////////////////////////////////////////////
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// File: intsindmatrixsse.cpp
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// Description: SSE implementation of 8-bit int SIMD matrix multiply.
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// Author: Ray Smith
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//
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// (C) Copyright 2017, Google Inc.
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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///////////////////////////////////////////////////////////////////////
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#if !defined(__SSE4_1__)
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# if defined(__i686__) || defined(__x86_64__)
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# error Implementation only for SSE 4.1 capable architectures
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# endif
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#else
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# include "intsimdmatrix.h"
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# include <emmintrin.h>
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# include <smmintrin.h>
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# include <cstdint>
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namespace tesseract {
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// Computes and returns the dot product of the n-vectors u and v.
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// Uses Intel SSE intrinsics to access the SIMD instruction set.
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static int32_t IntDotProductSSE(const int8_t *u, const int8_t *v, int n) {
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int max_offset = n - 8;
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int offset = 0;
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// Accumulate a set of 4 32-bit sums in sum, by loading 8 pairs of 8-bit
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// values, extending to 16 bit, multiplying to make 32 bit results.
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int32_t result = 0;
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if (offset <= max_offset) {
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offset = 8;
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__m128i packed1 = _mm_loadl_epi64(reinterpret_cast<const __m128i *>(u));
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__m128i packed2 = _mm_loadl_epi64(reinterpret_cast<const __m128i *>(v));
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__m128i sum = _mm_cvtepi8_epi16(packed1);
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packed2 = _mm_cvtepi8_epi16(packed2);
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// The magic _mm_add_epi16 is perfect here. It multiplies 8 pairs of 16 bit
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// ints to make 32 bit results, which are then horizontally added in pairs
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// to make 4 32 bit results that still fit in a 128 bit register.
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sum = _mm_madd_epi16(sum, packed2);
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while (offset <= max_offset) {
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packed1 = _mm_loadl_epi64(reinterpret_cast<const __m128i *>(u + offset));
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packed2 = _mm_loadl_epi64(reinterpret_cast<const __m128i *>(v + offset));
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offset += 8;
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packed1 = _mm_cvtepi8_epi16(packed1);
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packed2 = _mm_cvtepi8_epi16(packed2);
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packed1 = _mm_madd_epi16(packed1, packed2);
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sum = _mm_add_epi32(sum, packed1);
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}
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// Sum the 4 packed 32 bit sums and extract the low result.
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sum = _mm_hadd_epi32(sum, sum);
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sum = _mm_hadd_epi32(sum, sum);
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result = _mm_cvtsi128_si32(sum);
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}
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while (offset < n) {
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result += u[offset] * v[offset];
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++offset;
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}
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return result;
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}
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// Computes part of matrix.vector v = Wu. Computes 1 result.
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static void PartialMatrixDotVector1(const int8_t *wi, const double *scales, const int8_t *u,
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int num_in, double *v) {
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double total = IntDotProductSSE(u, wi, num_in);
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// Add in the bias and correct for integer values.
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*v = (total + wi[num_in] * INT8_MAX) * *scales;
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}
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static void matrixDotVector(int dim1, int dim2, const int8_t *wi, const double *scales,
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const int8_t *u, double *v) {
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const int num_out = dim1;
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const int num_in = dim2 - 1;
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int output = 0;
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for (; output < num_out; output++) {
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PartialMatrixDotVector1(wi, scales, u, num_in, v);
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wi += dim2;
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scales++;
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v++;
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}
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}
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const IntSimdMatrix IntSimdMatrix::intSimdMatrixSSE = {
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matrixDotVector,
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// Number of 32 bit outputs held in each register.
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1,
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// Maximum number of registers that we will use to hold outputs.
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1,
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// Number of 8 bit inputs in the inputs register.
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1,
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// Number of inputs in each weight group.
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1};
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} // namespace tesseract.
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#endif
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