mirror of https://github.com/google/gemma.cpp.git
100 lines
3.3 KiB
C++
100 lines
3.3 KiB
C++
// Copyright 2024 Google LLC
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// SPDX-License-Identifier: Apache-2.0
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#include "compression/distortion.h"
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#include <stdio.h>
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#include "compression/test_util.h"
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#include "hwy/nanobenchmark.h"
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#include "hwy/tests/hwy_gtest.h"
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#include "hwy/tests/test_util-inl.h" // HWY_ASSERT_EQ
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namespace gcpp {
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namespace {
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#if !HWY_TEST_STANDALONE
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class DistortionTest : public testing::Test {};
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#endif
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TEST(DistortionTest, TestCascadedSummation) {
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CascadedSummation<double> cs;
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// Example from Priest92. Exact sum is 2.
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const double kHuge = 9007199254740992.0 * hwy::Unpredictable1(); // 2^53
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const double kNeg = -4503599627370495.0 * hwy::Unpredictable1(); // -(2^52-1)
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const double kIn[6] = {kHuge, kHuge - 2.0, kNeg, kNeg, kNeg, kNeg};
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for (double in : kIn) {
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cs.Notify(in);
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}
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HWY_ASSERT_EQ(2.0, cs.Total());
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}
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// Number of exact and rounded-to-zero matches expectations.
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TEST(DistortionTest, TestCounts) {
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// Arbitrary positive/negative original, zero distorted.
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DistortionStats stats;
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for (size_t i = 1; i < 10; ++i) {
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stats.Notify(i / 100.0f, 0.0f);
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stats.Notify(i / -100.0f, 0.0f);
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}
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HWY_ASSERT(stats.NumExact() == 0);
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HWY_ASSERT(stats.NumRoundedToZero() == 18);
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// Add some exact (same):
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size_t num_exact = 0;
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for (float x = 0.0f; x <= 1.5f; x += 0.25f) {
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stats.Notify(x, x);
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stats.Notify(-x, -x);
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num_exact += 2;
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}
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HWY_ASSERT_EQ(num_exact, stats.NumExact());
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HWY_ASSERT(stats.NumRoundedToZero() == 18); // unchanged
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}
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// Few large differences are diluted in SNR but not WeightedAverageL1.
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TEST(DistortionTest, TestDilution) {
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DistortionStats stats;
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for (size_t i = 0; i < 100; ++i) {
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stats.Notify(0.998f, 0.999f); // small
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}
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HWY_ASSERT(IsInside(900.0, 1000.0, stats.GeomeanValueDivL1()));
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// All-equal WeightedSum is exact.
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HWY_ASSERT(IsNear(0.001, stats.WeightedAverageL1()));
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// Now add a large difference:
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stats.Notify(1.875f - 0.0625f, 1.875f); // max magnitude, 3-bit mantissa
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// .. WeightedAverageL1 is closer to it.
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HWY_ASSERT(IsInside(0.020, 0.025, stats.WeightedAverageL1()));
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// Add a small and large difference:
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stats.Notify((1.75f - 0.125f) / 1024, 1.75f / 1024); // small, 2-bit mantissa
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stats.Notify(-1.875f + 0.0625f, -1.875f); // larger negative
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// .. SNR is still barely affected.
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HWY_ASSERT(IsInside(890.0, 900.0, stats.GeomeanValueDivL1()));
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// .. WeightedAverageL1 is higher after another large error.
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HWY_ASSERT(IsInside(0.030, 0.035, stats.WeightedAverageL1()));
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// With these inputs, none are exact nor round to zero.
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HWY_ASSERT(stats.NumExact() == 0);
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HWY_ASSERT(stats.NumRoundedToZero() == 0);
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HWY_ASSERT_EQ(0.0, stats.SumL1Rounded());
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HWY_ASSERT(IsInside(0.220, 0.23, stats.SumL1()));
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}
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} // namespace
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} // namespace gcpp
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HWY_TEST_MAIN();
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