/* Copyright 2015 The TensorFlow Authors. 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 "tensorflow/core/util/overflow.h"
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#include <cmath>
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#include "tensorflow/core/platform/macros.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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namespace {
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TEST(OverflowTest, Nonnegative) {
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// Various interesting values
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std::vector<int64> interesting = {0, std::numeric_limits<int64>::max()};
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for (int i = 0; i < 63; i++) {
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int64 bit = static_cast<int64>(1) << i;
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interesting.push_back(bit);
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interesting.push_back(bit + 1);
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interesting.push_back(bit - 1);
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}
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for (const int64 mid : {static_cast<int64>(1) << 32,
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static_cast<int64>(std::pow(2, 63.0 / 2))}) {
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for (int i = -5; i < 5; i++) {
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interesting.push_back(mid + i);
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}
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}
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// Check all pairs
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for (auto x : interesting) {
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for (auto y : interesting) {
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int64 xy = MultiplyWithoutOverflow(x, y);
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long double dxy = static_cast<long double>(x) * y;
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if (dxy > std::numeric_limits<int64>::max()) {
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EXPECT_LT(xy, 0);
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} else {
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EXPECT_EQ(dxy, xy);
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}
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}
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}
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}
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TEST(OverflowTest, Negative) {
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const int64 negatives[] = {-1, std::numeric_limits<int64>::min()};
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for (const int64 n : negatives) {
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EXPECT_DEATH(MultiplyWithoutOverflow(n, 0), "");
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EXPECT_DEATH(MultiplyWithoutOverflow(0, n), "");
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EXPECT_DEATH(MultiplyWithoutOverflow(n, n), "");
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}
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}
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} // namespace
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} // namespace tensorflow
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