/* Copyright 2017 The TensorFlow Authors. All Rights Reserved. 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. ==============================================================================*/ // Unit test for TFLite Lookup op. #include #include #include #include #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 tflite { namespace { using ::testing::ElementsAreArray; class HashtableLookupOpModel : public SingleOpModel { public: HashtableLookupOpModel(std::initializer_list lookup_shape, std::initializer_list key_shape, std::initializer_list value_shape, TensorType type) { lookup_ = AddInput(TensorType_INT32); key_ = AddInput(TensorType_INT32); value_ = AddInput(type); output_ = AddOutput(type); hit_ = AddOutput(TensorType_UINT8); SetBuiltinOp(BuiltinOperator_HASHTABLE_LOOKUP, BuiltinOptions_NONE, 0); BuildInterpreter({lookup_shape, key_shape, value_shape}); } void SetLookup(std::initializer_list data) { PopulateTensor(lookup_, data); } void SetHashtableKey(std::initializer_list data) { PopulateTensor(key_, data); } void SetHashtableValue(const std::vector& content) { PopulateStringTensor(value_, content); } void SetHashtableValue(const std::function& function) { TfLiteTensor* tensor = interpreter_->tensor(value_); int rows = tensor->dims->data[0]; for (int i = 0; i < rows; i++) { tensor->data.f[i] = function(i); } } void SetHashtableValue(const std::function& function) { TfLiteTensor* tensor = interpreter_->tensor(value_); int rows = tensor->dims->data[0]; int features = tensor->dims->data[1]; for (int i = 0; i < rows; i++) { for (int j = 0; j < features; j++) { tensor->data.f[i * features + j] = function(i, j); } } } std::vector GetStringOutput() { TfLiteTensor* output = interpreter_->tensor(output_); int num = GetStringCount(output); std::vector result(num); for (int i = 0; i < num; i++) { auto ref = GetString(output, i); result[i] = string(ref.str, ref.len); } return result; } std::vector GetOutput() { return ExtractVector(output_); } std::vector GetHit() { return ExtractVector(hit_); } private: int lookup_; int key_; int value_; int output_; int hit_; }; // TODO(yichengfan): write more tests that exercise the details of the op, // such as lookup errors and variable input shapes. TEST(HashtableLookupOpTest, Test2DInput) { HashtableLookupOpModel m({4}, {3}, {3, 2}, TensorType_FLOAT32); m.SetLookup({1234, -292, -11, 0}); m.SetHashtableKey({-11, 0, 1234}); m.SetHashtableValue([](int i, int j) { return i + j / 10.0f; }); m.Invoke(); EXPECT_THAT(m.GetOutput(), ElementsAreArray(ArrayFloatNear({ 2.0, 2.1, // 2-nd item 0, 0, // Not found 0.0, 0.1, // 0-th item 1.0, 1.1, // 1-st item }))); EXPECT_THAT(m.GetHit(), ElementsAreArray({ 1, 0, 1, 1, })); } TEST(HashtableLookupOpTest, Test1DInput) { HashtableLookupOpModel m({4}, {3}, {3}, TensorType_FLOAT32); m.SetLookup({1234, -292, -11, 0}); m.SetHashtableKey({-11, 0, 1234}); m.SetHashtableValue([](int i) { return i * i / 10.0f; }); m.Invoke(); EXPECT_THAT(m.GetOutput(), ElementsAreArray(ArrayFloatNear({ 0.4, // 2-nd item 0, // Not found 0.0, // 0-th item 0.1, // 1-st item }))); EXPECT_THAT(m.GetHit(), ElementsAreArray({ 1, 0, 1, 1, })); } TEST(HashtableLookupOpTest, TestString) { HashtableLookupOpModel m({4}, {3}, {3}, TensorType_STRING); m.SetLookup({1234, -292, -11, 0}); m.SetHashtableKey({-11, 0, 1234}); m.SetHashtableValue({"Hello", "", "Hi"}); m.Invoke(); EXPECT_THAT(m.GetStringOutput(), ElementsAreArray({ "Hi", // 2-nd item "", // Not found "Hello", // 0-th item "", // 1-st item })); EXPECT_THAT(m.GetHit(), ElementsAreArray({ 1, 0, 1, 1, })); } } // namespace } // namespace tflite int main(int argc, char** argv) { ::tflite::LogToStderr(); ::testing::InitGoogleTest(&argc, argv); return RUN_ALL_TESTS(); }