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https://github.com/tesseract-ocr/tesseract.git
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7768f9b336
The changes are based on an analysis done with include-what-you-use. Signed-off-by: Stefan Weil <sw@weilnetz.de>
107 lines
3.6 KiB
C++
107 lines
3.6 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 <memory>
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#include "genericvector.h"
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#include "include_gunit.h"
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#include "intsimdmatrixavx2.h"
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#include "intsimdmatrixsse.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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namespace {
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class IntSimdMatrixTest : public ::testing::Test {
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protected:
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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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GenericVector<double> RandomScales(int size) {
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GenericVector<double> v(size, 0.0);
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for (int i = 0; i < size; ++i) {
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v[i] = 1.0 + random_.SignedRand(1.0);
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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 base_ version.
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void ExpectEqualResults(IntSimdMatrix* matrix) {
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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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matrix->Init(w);
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std::vector<int8_t> u = RandomVector(num_in, *matrix);
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GenericVector<double> scales = RandomScales(num_out);
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std::vector<double> base_result(num_out);
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base_.MatrixDotVector(w, scales, u.data(), base_result.data());
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std::vector<double> test_result(num_out);
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matrix->MatrixDotVector(w, scales, u.data(), test_result.data());
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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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}
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}
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}
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TRand random_;
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IntSimdMatrix base_;
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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 (SIMDDetect::IsSSEAvailable()) {
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tprintf("SSE found! Continuing...");
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} else {
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tprintf("No SSE found! Not Tested!");
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return;
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}
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std::unique_ptr<IntSimdMatrix> matrix(new IntSimdMatrixSSE());
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ExpectEqualResults(matrix.get());
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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 (SIMDDetect::IsAVX2Available()) {
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tprintf("AVX2 found! Continuing...");
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} else {
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tprintf("No AVX2 found! Not Tested!");
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return;
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}
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std::unique_ptr<IntSimdMatrix> matrix(new IntSimdMatrixAVX2());
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ExpectEqualResults(matrix.get());
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}
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} // namespace
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} // namespace tesseract
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