| /* |
| * Copyright (C) 2018 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 <fstream> |
| #include <string> |
| #include <vector> |
| |
| #include "utils/tflite/text_encoder.h" |
| #include "gtest/gtest.h" |
| #include "third_party/absl/flags/flag.h" |
| #include "flatbuffers/flexbuffers.h" |
| #include "tensorflow/contrib/lite/interpreter.h" |
| #include "tensorflow/contrib/lite/kernels/register.h" |
| #include "tensorflow/contrib/lite/kernels/test_util.h" |
| #include "tensorflow/contrib/lite/model.h" |
| #include "tensorflow/contrib/lite/string_util.h" |
| |
| namespace libtextclassifier3 { |
| namespace { |
| |
| std::string GetTestConfigPath() { |
| return ""; |
| } |
| |
| class TextEncoderOpModel : public tflite::SingleOpModel { |
| public: |
| TextEncoderOpModel(std::initializer_list<int> input_strings_shape, |
| std::initializer_list<int> attribute_shape); |
| void SetInputText(const std::initializer_list<string>& strings) { |
| PopulateStringTensor(input_string_, strings); |
| PopulateTensor(input_length_, {static_cast<int32_t>(strings.size())}); |
| } |
| void SetMaxOutputLength(int length) { |
| PopulateTensor(input_output_maxlength_, {length}); |
| } |
| void SetInt32Attribute(const std::initializer_list<int>& attribute) { |
| PopulateTensor(input_attributes_int32_, attribute); |
| } |
| void SetFloatAttribute(const std::initializer_list<float>& attribute) { |
| PopulateTensor(input_attributes_float_, attribute); |
| } |
| |
| std::vector<int> GetOutputEncoding() { |
| return ExtractVector<int>(output_encoding_); |
| } |
| std::vector<int> GetOutputPositions() { |
| return ExtractVector<int>(output_positions_); |
| } |
| std::vector<int> GetOutputAttributeInt32() { |
| return ExtractVector<int>(output_attributes_int32_); |
| } |
| std::vector<float> GetOutputAttributeFloat() { |
| return ExtractVector<float>(output_attributes_float_); |
| } |
| int GetEncodedLength() { return ExtractVector<int>(output_length_)[0]; } |
| |
| private: |
| int input_string_; |
| int input_length_; |
| int input_output_maxlength_; |
| int input_attributes_int32_; |
| int input_attributes_float_; |
| |
| int output_encoding_; |
| int output_positions_; |
| int output_length_; |
| int output_attributes_int32_; |
| int output_attributes_float_; |
| }; |
| |
| TextEncoderOpModel::TextEncoderOpModel( |
| std::initializer_list<int> input_strings_shape, |
| std::initializer_list<int> attribute_shape) { |
| input_string_ = AddInput(tflite::TensorType_STRING); |
| input_length_ = AddInput(tflite::TensorType_INT32); |
| input_output_maxlength_ = AddInput(tflite::TensorType_INT32); |
| input_attributes_int32_ = AddInput(tflite::TensorType_INT32); |
| input_attributes_float_ = AddInput(tflite::TensorType_FLOAT32); |
| |
| output_encoding_ = AddOutput(tflite::TensorType_INT32); |
| output_positions_ = AddOutput(tflite::TensorType_INT32); |
| output_length_ = AddOutput(tflite::TensorType_INT32); |
| output_attributes_int32_ = AddOutput(tflite::TensorType_INT32); |
| output_attributes_float_ = AddOutput(tflite::TensorType_FLOAT32); |
| |
| std::ifstream test_config_stream(GetTestConfigPath()); |
| std::string config((std::istreambuf_iterator<char>(test_config_stream)), |
| (std::istreambuf_iterator<char>())); |
| flexbuffers::Builder builder; |
| builder.Map([&]() { builder.String("text_encoder_config", config); }); |
| builder.Finish(); |
| SetCustomOp("TextEncoder", builder.GetBuffer(), |
| tflite::ops::custom::Register_TEXT_ENCODER); |
| BuildInterpreter( |
| {input_strings_shape, {1}, {1}, attribute_shape, attribute_shape}); |
| } |
| |
| // Tests |
| TEST(TextEncoderTest, SimpleEncoder) { |
| TextEncoderOpModel m({1, 1}, {1, 1}); |
| m.SetInputText({"Hello"}); |
| m.SetMaxOutputLength(10); |
| m.SetInt32Attribute({7}); |
| m.SetFloatAttribute({3.f}); |
| m.Invoke(); |
| EXPECT_EQ(m.GetEncodedLength(), 5); |
| EXPECT_THAT(m.GetOutputEncoding(), |
| testing::ElementsAre(1, 90, 547, 58, 2, 2, 2, 2, 2, 2)); |
| EXPECT_THAT(m.GetOutputPositions(), |
| testing::ElementsAre(0, 1, 2, 3, 4, 10, 10, 10, 10, 10)); |
| EXPECT_THAT(m.GetOutputAttributeInt32(), |
| testing::ElementsAre(7, 7, 7, 7, 7, 7, 7, 7, 7, 7)); |
| EXPECT_THAT( |
| m.GetOutputAttributeFloat(), |
| testing::ElementsAre(3.f, 3.f, 3.f, 3.f, 3.f, 3.f, 3.f, 3.f, 3.f, 3.f)); |
| } |
| |
| TEST(TextEncoderTest, ManyStrings) { |
| TextEncoderOpModel m({1, 3}, {1, 3}); |
| m.SetInt32Attribute({1, 2, 3}); |
| m.SetFloatAttribute({5.f, 4.f, 3.f}); |
| m.SetInputText({"Hello", "Hi", "Bye"}); |
| m.SetMaxOutputLength(10); |
| m.Invoke(); |
| EXPECT_EQ(m.GetEncodedLength(), 10); |
| EXPECT_THAT(m.GetOutputEncoding(), |
| testing::ElementsAre(547, 58, 2, 1, 862, 2, 1, 1919, 19, 2)); |
| EXPECT_THAT(m.GetOutputPositions(), |
| testing::ElementsAre(2, 3, 4, 0, 1, 2, 0, 1, 2, 3)); |
| EXPECT_THAT(m.GetOutputAttributeInt32(), |
| testing::ElementsAre(1, 1, 1, 2, 2, 2, 3, 3, 3, 3)); |
| EXPECT_THAT( |
| m.GetOutputAttributeFloat(), |
| testing::ElementsAre(5.f, 5.f, 5.f, 4.f, 4.f, 4.f, 3.f, 3.f, 3.f, 3.f)); |
| } |
| |
| TEST(TextEncoderTest, LongStrings) { |
| TextEncoderOpModel m({1, 4}, {1, 4}); |
| m.SetInt32Attribute({1, 2, 3, 4}); |
| m.SetFloatAttribute({5.f, 4.f, 3.f, 2.f}); |
| m.SetInputText({"Hello", "Hi", "Bye", "Hi"}); |
| m.SetMaxOutputLength(9); |
| m.Invoke(); |
| EXPECT_EQ(m.GetEncodedLength(), 9); |
| EXPECT_THAT(m.GetOutputEncoding(), |
| testing::ElementsAre(862, 2, 1, 1919, 19, 2, 1, 862, 2)); |
| EXPECT_THAT(m.GetOutputPositions(), |
| testing::ElementsAre(1, 2, 0, 1, 2, 3, 0, 1, 2)); |
| EXPECT_THAT(m.GetOutputAttributeInt32(), |
| testing::ElementsAre(2, 2, 3, 3, 3, 3, 4, 4, 4)); |
| EXPECT_THAT( |
| m.GetOutputAttributeFloat(), |
| testing::ElementsAre(4.f, 4.f, 3.f, 3.f, 3.f, 3.f, 2.f, 2.f, 2.f)); |
| } |
| |
| } // namespace |
| } // namespace libtextclassifier3 |