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94 lines
2.6 KiB
94 lines
2.6 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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* This test is about floating point calculation exception.
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* Paddle catches FE_INVALID, FE DIVBYZERO and FE_OVERFLOW exceptions.
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*
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* Some exceptions occur in the middle of a set of formulas,
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* that can be circumvented by some tricks.
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* For example,
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* calculate tanh
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* b = 2.0 / (1.0 + exp(-2 * a)) - 1.0
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*
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* If the result of (-2 * a) is too large,
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* a FE_OVERFLOW exception occurs when calculating exp.
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* But the result of tanh is no overflow problem,
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* so we can add some tricks to prevent exp calculate an excessive value.
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*
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*/
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#include <gtest/gtest.h>
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#include "paddle/math/Matrix.h"
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#include "paddle/utils/Common.h"
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using namespace paddle; // NOLINT
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void SetTensorValue(Matrix& matrix, real value) {
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int height = matrix.getHeight();
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int width = matrix.getWidth();
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int stride = matrix.getStride();
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real* data = matrix.getData();
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for (int i = 0; i < height; i++) {
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int j = rand() % width; // NOLINT
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if (typeid(matrix) == typeid(CpuMatrix)) {
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data[i * stride + j] = value;
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} else if (typeid(matrix) == typeid(GpuMatrix)) {
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hl_memcpy(&data[i * stride + j], &value, sizeof(real));
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} else {
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LOG(FATAL) << "should not reach here";
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}
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}
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}
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template <typename Matrix>
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void testTanh(real illegal) {
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MatrixPtr A = std::make_shared<Matrix>(10, 10);
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MatrixPtr B = std::make_shared<Matrix>(10, 10);
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A->randomizeUniform();
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B->randomizeUniform();
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SetTensorValue(*A, illegal);
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A->tanh(*B);
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}
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template <typename Matrix>
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void testSigmoid(real illegal) {
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MatrixPtr A = std::make_shared<Matrix>(10, 10);
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MatrixPtr B = std::make_shared<Matrix>(10, 10);
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A->randomizeUniform();
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B->randomizeUniform();
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SetTensorValue(*A, illegal);
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A->sigmoid(*B);
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}
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TEST(fp, overflow) {
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for (auto illegal : {-90.0, 90.0}) {
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LOG(INFO) << " illegal=" << illegal;
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testTanh<CpuMatrix>(illegal);
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testSigmoid<CpuMatrix>(illegal);
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}
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}
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int main(int argc, char** argv) {
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testing::InitGoogleTest(&argc, argv);
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initMain(argc, argv);
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feenableexcept(FE_INVALID | FE_DIVBYZERO | FE_OVERFLOW);
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return RUN_ALL_TESTS();
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}
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