/////////////////////////////////////////////////////////////////////// // 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 "genericvector.h" #include "include_gunit.h" #include "intsimdmatrixavx2.h" #include "intsimdmatrixsse.h" #include "simddetect.h" #include "tprintf.h" namespace tesseract { namespace { class IntSimdMatrixTest : public ::testing::Test { protected: // 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. GenericVector RandomScales(int size) { GenericVector v(size, 0.0); for (int i = 0; i < size; ++i) { v[i] = 1.0 + random_.SignedRand(1.0); } return v; } // Tests a range of sizes and compares the results against the base_ version. void ExpectEqualResults(IntSimdMatrix* matrix) { 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); matrix->Init(w); std::vector u = RandomVector(num_in, *matrix); GenericVector scales = RandomScales(num_out); std::vector base_result(num_out); base_.MatrixDotVector(w, scales, u.data(), base_result.data()); std::vector test_result(num_out); matrix->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; } } } TRand random_; IntSimdMatrix base_; }; // Tests that the SSE implementation gets the same result as the vanilla. TEST_F(IntSimdMatrixTest, SSE) { if (SIMDDetect::IsSSEAvailable()) { tprintf("SSE found! Continuing..."); } else { tprintf("No SSE found! Not Tested!"); return; } std::unique_ptr matrix(new IntSimdMatrixSSE()); ExpectEqualResults(matrix.get()); } // Tests that the AVX2 implementation gets the same result as the vanilla. TEST_F(IntSimdMatrixTest, AVX2) { if (SIMDDetect::IsAVX2Available()) { tprintf("AVX2 found! Continuing..."); } else { tprintf("No AVX2 found! Not Tested!"); return; } std::unique_ptr matrix(new IntSimdMatrixAVX2()); ExpectEqualResults(matrix.get()); } } // namespace } // namespace tesseract