/////////////////////////////////////////////////////////////////////// // File: intsimdmatrix_test.cc // Author: rays@google.com (Ray Smith) // // Copyright 2017 Google Inc. All Rights Reserved. // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // http://www.apache.org/licenses/LICENSE-2.0 // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. /////////////////////////////////////////////////////////////////////// #include "intsimdmatrix.h" #include #include #include #include #include "include_gunit.h" #include "matrix.h" #include "simddetect.h" #include "tprintf.h" namespace tesseract { class IntSimdMatrixTest : public ::testing::Test { protected: void SetUp() { std::locale::global(std::locale("")); } // Makes a random weights matrix of the given size. GENERIC_2D_ARRAY InitRandom(int no, int ni) { GENERIC_2D_ARRAY a(no, ni, 0); for (int i = 0; i < no; ++i) { for (int j = 0; j < ni; ++j) { a(i, j) = static_cast(random_.SignedRand(INT8_MAX)); } } return a; } // Makes a random input vector of the given size, with rounding up. std::vector RandomVector(int size, const IntSimdMatrix& matrix) { int rounded_size = matrix.RoundInputs(size); std::vector v(rounded_size, 0); for (int i = 0; i < size; ++i) { v[i] = static_cast(random_.SignedRand(INT8_MAX)); } return v; } // Makes a random scales vector of the given size. std::vector RandomScales(int size) { std::vector v(size); for (int i = 0; i < size; ++i) { v[i] = (1.0 + random_.SignedRand(1.0)) / INT8_MAX; } return v; } // Tests a range of sizes and compares the results against the generic version. void ExpectEqualResults(const IntSimdMatrix& matrix) { double total = 0.0; for (int num_out = 1; num_out < 130; ++num_out) { for (int num_in = 1; num_in < 130; ++num_in) { GENERIC_2D_ARRAY w = InitRandom(num_out, num_in + 1); std::vector u = RandomVector(num_in, matrix); std::vector scales = RandomScales(num_out); int ro = num_out; if (IntSimdMatrix::intSimdMatrix) ro = IntSimdMatrix::intSimdMatrix->RoundOutputs(ro); std::vector base_result(ro); base_result.resize(num_out); IntSimdMatrix::MatrixDotVector(w, scales, u.data(), base_result.data()); std::vector test_result(ro); test_result.resize(num_out); std::vector shaped_wi; int32_t rounded_num_out; matrix.Init(w, shaped_wi, rounded_num_out); scales.reserve(rounded_num_out); if (matrix.matrixDotVectorFunction) { matrix.matrixDotVectorFunction(w.dim1(), w.dim2(), &shaped_wi[0], &scales[0], &u[0], &test_result[0]); } else { IntSimdMatrix::MatrixDotVector(w, scales, u.data(), test_result.data()); } for (int i = 0; i < num_out; ++i) { EXPECT_FLOAT_EQ(base_result[i], test_result[i]) << "i=" << i; total += base_result[i]; } } } // Compare sum of all results with expected value. EXPECT_FLOAT_EQ(total, 337849.39354684710); } TRand random_; }; // Test the C++ implementation without SIMD. TEST_F(IntSimdMatrixTest, C) { static const IntSimdMatrix matrix = {nullptr, 1, 1, 1, 1}; ExpectEqualResults(matrix); } // Tests that the SSE implementation gets the same result as the vanilla. TEST_F(IntSimdMatrixTest, SSE) { #if defined(HAVE_SSE4_1) if (!SIMDDetect::IsSSEAvailable()) { GTEST_LOG_(INFO) << "No SSE found! Not tested!"; GTEST_SKIP(); } ExpectEqualResults(IntSimdMatrix::intSimdMatrixSSE); #else GTEST_LOG_(INFO) << "SSE unsupported! Not tested!"; GTEST_SKIP(); #endif } // Tests that the AVX2 implementation gets the same result as the vanilla. TEST_F(IntSimdMatrixTest, AVX2) { #if defined(HAVE_AVX2) if (!SIMDDetect::IsAVX2Available()) { GTEST_LOG_(INFO) << "No AVX2 found! Not tested!"; GTEST_SKIP(); } ExpectEqualResults(IntSimdMatrix::intSimdMatrixAVX2); #else GTEST_LOG_(INFO) << "AVX2 unsupported! Not tested!"; GTEST_SKIP(); #endif } } // namespace tesseract