/*
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* Copyright (C) 2018 The Android Open Source Project
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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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*/
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#include "annotator/quantization.h"
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#include <vector>
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#include "gmock/gmock.h"
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#include "gtest/gtest.h"
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using testing::ElementsAreArray;
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using testing::FloatEq;
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using testing::Matcher;
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namespace libtextclassifier3 {
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namespace {
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Matcher<std::vector<float>> ElementsAreFloat(const std::vector<float>& values) {
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std::vector<Matcher<float>> matchers;
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for (const float value : values) {
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matchers.push_back(FloatEq(value));
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}
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return ElementsAreArray(matchers);
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}
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TEST(QuantizationTest, DequantizeAdd8bit) {
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std::vector<float> scales{{0.1, 9.0, -7.0}};
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std::vector<uint8> embeddings{{/*0: */ 0x00, 0xFF, 0x09, 0x00,
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/*1: */ 0xFF, 0x09, 0x00, 0xFF,
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/*2: */ 0x09, 0x00, 0xFF, 0x09}};
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const int quantization_bits = 8;
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const int bytes_per_embedding = 4;
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const int num_sparse_features = 7;
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{
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const int bucket_id = 0;
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std::vector<float> dest(4, 0.0);
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DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding,
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num_sparse_features, quantization_bits, bucket_id,
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dest.data(), dest.size());
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EXPECT_THAT(dest,
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ElementsAreFloat(std::vector<float>{
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// clang-format off
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{1.0 / 7 * 0.1 * (0x00 - 128),
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1.0 / 7 * 0.1 * (0xFF - 128),
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1.0 / 7 * 0.1 * (0x09 - 128),
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1.0 / 7 * 0.1 * (0x00 - 128)}
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// clang-format on
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}));
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}
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{
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const int bucket_id = 1;
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std::vector<float> dest(4, 0.0);
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DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding,
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num_sparse_features, quantization_bits, bucket_id,
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dest.data(), dest.size());
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EXPECT_THAT(dest,
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ElementsAreFloat(std::vector<float>{
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// clang-format off
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{1.0 / 7 * 9.0 * (0xFF - 128),
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1.0 / 7 * 9.0 * (0x09 - 128),
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1.0 / 7 * 9.0 * (0x00 - 128),
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1.0 / 7 * 9.0 * (0xFF - 128)}
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// clang-format on
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}));
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}
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}
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TEST(QuantizationTest, DequantizeAdd1bitZeros) {
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const int bytes_per_embedding = 4;
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const int num_buckets = 3;
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const int num_sparse_features = 7;
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const int quantization_bits = 1;
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const int bucket_id = 1;
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std::vector<float> scales(num_buckets);
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std::vector<uint8> embeddings(bytes_per_embedding * num_buckets);
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std::fill(scales.begin(), scales.end(), 1);
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std::fill(embeddings.begin(), embeddings.end(), 0);
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std::vector<float> dest(32);
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DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding,
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num_sparse_features, quantization_bits, bucket_id, dest.data(),
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dest.size());
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std::vector<float> expected(32);
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std::fill(expected.begin(), expected.end(),
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1.0 / num_sparse_features * (0 - 1));
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EXPECT_THAT(dest, ElementsAreFloat(expected));
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}
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TEST(QuantizationTest, DequantizeAdd1bitOnes) {
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const int bytes_per_embedding = 4;
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const int num_buckets = 3;
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const int num_sparse_features = 7;
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const int quantization_bits = 1;
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const int bucket_id = 1;
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std::vector<float> scales(num_buckets, 1.0);
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std::vector<uint8> embeddings(bytes_per_embedding * num_buckets, 0xFF);
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std::vector<float> dest(32);
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DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding,
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num_sparse_features, quantization_bits, bucket_id, dest.data(),
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dest.size());
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std::vector<float> expected(32);
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std::fill(expected.begin(), expected.end(),
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1.0 / num_sparse_features * (1 - 1));
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EXPECT_THAT(dest, ElementsAreFloat(expected));
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}
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TEST(QuantizationTest, DequantizeAdd3bit) {
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const int bytes_per_embedding = 4;
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const int num_buckets = 3;
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const int num_sparse_features = 7;
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const int quantization_bits = 3;
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const int bucket_id = 1;
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std::vector<float> scales(num_buckets, 1.0);
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scales[1] = 9.0;
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std::vector<uint8> embeddings(bytes_per_embedding * num_buckets, 0);
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// For bucket_id=1, the embedding has values 0..9 for indices 0..9:
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embeddings[4] = (1 << 7) | (1 << 6) | (1 << 4) | 1;
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embeddings[5] = (1 << 6) | (1 << 4) | (1 << 3);
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embeddings[6] = (1 << 4) | (1 << 3) | (1 << 2) | (1 << 1) | 1;
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std::vector<float> dest(10);
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DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding,
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num_sparse_features, quantization_bits, bucket_id, dest.data(),
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dest.size());
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std::vector<float> expected;
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expected.push_back(1.0 / num_sparse_features * (1 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (2 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (3 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (4 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (5 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (6 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (7 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (0 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (0 - 4) * scales[bucket_id]);
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expected.push_back(1.0 / num_sparse_features * (0 - 4) * scales[bucket_id]);
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EXPECT_THAT(dest, ElementsAreFloat(expected));
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}
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} // namespace
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} // namespace libtextclassifier3
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