| /* |
| * Copyright (C) 2017 The Android Open Source Project |
| * |
| * 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 "common/embedding-network.h" |
| #include "common/embedding-network-params-from-proto.h" |
| #include "common/embedding-network.pb.h" |
| #include "common/simple-adder.h" |
| |
| #include "gmock/gmock.h" |
| #include "gtest/gtest.h" |
| |
| namespace libtextclassifier { |
| namespace nlp_core { |
| namespace { |
| |
| using testing::ElementsAreArray; |
| |
| class TestingEmbeddingNetwork : public EmbeddingNetwork { |
| public: |
| using EmbeddingNetwork::EmbeddingNetwork; |
| using EmbeddingNetwork::FinishComputeFinalScoresInternal; |
| }; |
| |
| void DiagonalAndBias3x3(int diagonal_value, int bias_value, |
| MatrixParams* weights, MatrixParams* bias) { |
| weights->set_rows(3); |
| weights->set_cols(3); |
| weights->add_value(diagonal_value); |
| weights->add_value(0); |
| weights->add_value(0); |
| weights->add_value(0); |
| weights->add_value(diagonal_value); |
| weights->add_value(0); |
| weights->add_value(0); |
| weights->add_value(0); |
| weights->add_value(diagonal_value); |
| |
| bias->set_rows(3); |
| bias->set_cols(1); |
| bias->add_value(bias_value); |
| bias->add_value(bias_value); |
| bias->add_value(bias_value); |
| } |
| |
| TEST(EmbeddingNetworkTest, IdentityThroughMultipleLayers) { |
| std::unique_ptr<EmbeddingNetworkProto> proto; |
| proto.reset(new EmbeddingNetworkProto); |
| |
| // These layers should be an identity with bias. |
| DiagonalAndBias3x3(/*diagonal_value=*/1, /*bias_value=*/1, |
| proto->add_hidden(), proto->add_hidden_bias()); |
| DiagonalAndBias3x3(/*diagonal_value=*/1, /*bias_value=*/2, |
| proto->add_hidden(), proto->add_hidden_bias()); |
| DiagonalAndBias3x3(/*diagonal_value=*/1, /*bias_value=*/3, |
| proto->add_hidden(), proto->add_hidden_bias()); |
| DiagonalAndBias3x3(/*diagonal_value=*/1, /*bias_value=*/4, |
| proto->add_hidden(), proto->add_hidden_bias()); |
| DiagonalAndBias3x3(/*diagonal_value=*/1, /*bias_value=*/5, |
| proto->mutable_softmax(), proto->mutable_softmax_bias()); |
| |
| EmbeddingNetworkParamsFromProto params(std::move(proto)); |
| TestingEmbeddingNetwork network(¶ms); |
| |
| std::vector<float> input({-2, -1, 0}); |
| std::vector<float> output; |
| network.FinishComputeFinalScoresInternal<SimpleAdder>( |
| VectorSpan<float>(input), &output); |
| |
| EXPECT_THAT(output, ElementsAreArray({14, 14, 15})); |
| } |
| |
| } // namespace |
| } // namespace nlp_core |
| } // namespace libtextclassifier |