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https://github.com/tesseract-ocr/tesseract.git
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472f5d9020
Up to now Tesseract used double for training and recognition with "best" models. This commit replaces double by a new data type TFloat which is double by default, but float if FAST_FLOAT is defined. Ideally this should allow faster training. Signed-off-by: Stefan Weil <sw@weilnetz.de>
139 lines
4.6 KiB
C++
139 lines
4.6 KiB
C++
///////////////////////////////////////////////////////////////////////
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// File: intsimdmatrix_test.cc
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// Author: rays@google.com (Ray Smith)
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//
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// Copyright 2017 Google Inc. All Rights Reserved.
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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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#include "intsimdmatrix.h"
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#include <gtest/gtest.h>
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#include <gtest/internal/gtest-port.h>
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#include <memory>
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#include <vector>
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#include "include_gunit.h"
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#include "matrix.h"
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#include "simddetect.h"
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#include "tprintf.h"
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namespace tesseract {
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class IntSimdMatrixTest : public ::testing::Test {
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protected:
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void SetUp() override {
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std::locale::global(std::locale(""));
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}
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// Makes a random weights matrix of the given size.
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GENERIC_2D_ARRAY<int8_t> InitRandom(int no, int ni) {
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GENERIC_2D_ARRAY<int8_t> a(no, ni, 0);
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for (int i = 0; i < no; ++i) {
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for (int j = 0; j < ni; ++j) {
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a(i, j) = static_cast<int8_t>(random_.SignedRand(INT8_MAX));
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}
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}
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return a;
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}
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// Makes a random input vector of the given size, with rounding up.
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std::vector<int8_t> RandomVector(int size, const IntSimdMatrix &matrix) {
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int rounded_size = matrix.RoundInputs(size);
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std::vector<int8_t> v(rounded_size, 0);
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for (int i = 0; i < size; ++i) {
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v[i] = static_cast<int8_t>(random_.SignedRand(INT8_MAX));
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}
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return v;
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}
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// Makes a random scales vector of the given size.
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std::vector<TFloat> RandomScales(int size) {
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std::vector<TFloat> v(size);
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for (int i = 0; i < size; ++i) {
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v[i] = (1.0 + random_.SignedRand(1.0)) / INT8_MAX;
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}
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return v;
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}
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// Tests a range of sizes and compares the results against the generic version.
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void ExpectEqualResults(const IntSimdMatrix &matrix) {
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TFloat total = 0.0;
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for (int num_out = 1; num_out < 130; ++num_out) {
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for (int num_in = 1; num_in < 130; ++num_in) {
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GENERIC_2D_ARRAY<int8_t> w = InitRandom(num_out, num_in + 1);
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std::vector<int8_t> u = RandomVector(num_in, matrix);
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std::vector<TFloat> scales = RandomScales(num_out);
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int ro = num_out;
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if (IntSimdMatrix::intSimdMatrix) {
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ro = IntSimdMatrix::intSimdMatrix->RoundOutputs(ro);
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}
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std::vector<TFloat> base_result(num_out);
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IntSimdMatrix::MatrixDotVector(w, scales, u.data(), base_result.data());
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std::vector<TFloat> test_result(ro);
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std::vector<int8_t> shaped_wi;
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int32_t rounded_num_out;
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matrix.Init(w, shaped_wi, rounded_num_out);
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scales.resize(rounded_num_out);
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if (matrix.matrixDotVectorFunction) {
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matrix.matrixDotVectorFunction(w.dim1(), w.dim2(), &shaped_wi[0], &scales[0], &u[0],
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&test_result[0]);
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} else {
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IntSimdMatrix::MatrixDotVector(w, scales, u.data(), test_result.data());
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}
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for (int i = 0; i < num_out; ++i) {
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EXPECT_FLOAT_EQ(base_result[i], test_result[i]) << "i=" << i;
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total += base_result[i];
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}
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}
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}
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// Compare sum of all results with expected value.
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#ifdef FAST_FLOAT
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EXPECT_FLOAT_EQ(total, 337852.16f);
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#else
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EXPECT_FLOAT_EQ(total, 337849.39354684710);
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#endif
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}
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TRand random_;
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};
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// Test the C++ implementation without SIMD.
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TEST_F(IntSimdMatrixTest, C) {
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static const IntSimdMatrix matrix = {nullptr, 1, 1, 1, 1};
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ExpectEqualResults(matrix);
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}
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// Tests that the SSE implementation gets the same result as the vanilla.
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TEST_F(IntSimdMatrixTest, SSE) {
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#if defined(HAVE_SSE4_1)
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if (!SIMDDetect::IsSSEAvailable()) {
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GTEST_LOG_(INFO) << "No SSE found! Not tested!";
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GTEST_SKIP();
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}
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ExpectEqualResults(IntSimdMatrix::intSimdMatrixSSE);
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#else
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GTEST_LOG_(INFO) << "SSE unsupported! Not tested!";
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GTEST_SKIP();
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#endif
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}
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// Tests that the AVX2 implementation gets the same result as the vanilla.
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TEST_F(IntSimdMatrixTest, AVX2) {
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#if defined(HAVE_AVX2)
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if (!SIMDDetect::IsAVX2Available()) {
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GTEST_LOG_(INFO) << "No AVX2 found! Not tested!";
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GTEST_SKIP();
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}
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ExpectEqualResults(IntSimdMatrix::intSimdMatrixAVX2);
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#else
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GTEST_LOG_(INFO) << "AVX2 unsupported! Not tested!";
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GTEST_SKIP();
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#endif
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}
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} // namespace tesseract
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