wehub-resource-sync
273 lines
9.4 KiB
C++
273 lines
9.4 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 <stdint.h>
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#include <list>
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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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#include "flatbuffers/flatbuffers.h" // from @flatbuffers
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#include "tensorflow/lite/core/c/c_api_types.h"
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#include "tensorflow/lite/kernels/test_util.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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namespace tflite {
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namespace {
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using ::testing::ElementsAreArray;
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using ::testing::Test;
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class BaseWhereOpModel : public SingleOpModel {
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public:
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BaseWhereOpModel(const TensorData& input, const TensorData& output) {
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input_ = AddInput(input);
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output_ = AddOutput(output);
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SetBuiltinOp(BuiltinOperator_WHERE, BuiltinOptions_WhereOptions,
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CreateWhereOptions(builder_).Union());
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BuildInterpreter({GetShape(input_)});
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}
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int input() { return input_; }
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protected:
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int input_;
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int output_;
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};
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class IntegerWhereOpModel : public BaseWhereOpModel {
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public:
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using BaseWhereOpModel::BaseWhereOpModel;
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std::vector<int64_t> GetOutput() { return ExtractVector<int64_t>(output_); }
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};
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template <typename T1>
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class ConstInputWhereOpModel : public SingleOpModel {
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public:
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ConstInputWhereOpModel(T1 constant_values, const TensorData& output) {
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input_ = AddConstInput(GetTensorType<T1>(), {constant_values}, {});
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output_ = AddOutput(output);
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SetBuiltinOp(BuiltinOperator_WHERE, BuiltinOptions_WhereOptions,
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CreateWhereOptions(builder_).Union());
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BuildInterpreter({{}});
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}
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int input() { return input_; }
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std::vector<int64_t> GetOutput() { return ExtractVector<int64_t>(output_); }
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protected:
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int input_;
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int output_;
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};
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// Utils which returns TensorType from primitive type.
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// Currently Where op supports only float, bool.
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template <typename T>
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TensorType GetTfLiteType();
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template <>
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TensorType GetTfLiteType<bool>() {
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return TensorType_BOOL;
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}
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template <>
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TensorType GetTfLiteType<float>() {
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return TensorType_FLOAT32;
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}
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template <>
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TensorType GetTfLiteType<int8_t>() {
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return TensorType_INT8;
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}
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template <>
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TensorType GetTfLiteType<uint8_t>() {
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return TensorType_UINT8;
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}
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template <>
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TensorType GetTfLiteType<int32_t>() {
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return TensorType_INT32;
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}
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template <>
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TensorType GetTfLiteType<uint32_t>() {
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return TensorType_UINT32;
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}
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template <>
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TensorType GetTfLiteType<int64_t>() {
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return TensorType_INT64;
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}
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// Helper function which creates std::vector from boolean type array 'data'
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// but with different type. The returned value will be in type 'T' and
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// matches the true/false criteria of where op.
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template <typename T>
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std::vector<T> GetCompatibleData(const std::initializer_list<bool>& data) {
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std::vector<T> result;
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for (auto item : data)
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if (item)
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result.push_back(T(1));
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else
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result.push_back(T(0));
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return result;
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}
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// Typed test so we can run the same set of tests with different data types.
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template <typename T>
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class WhereOpTest : public Test {
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public:
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using List = std::list<T>;
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static T shared_;
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T value_;
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};
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using MyTypes =
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::testing::Types<bool, float, int32_t, uint32_t, int64_t, int8_t, uint8_t>;
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TYPED_TEST_SUITE(WhereOpTest, MyTypes);
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TYPED_TEST(WhereOpTest, ScalarValueFail) {
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ConstInputWhereOpModel<bool> m(false, {TensorType_INT64, {}});
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EXPECT_EQ(m.Invoke(), kTfLiteError);
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}
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TYPED_TEST(WhereOpTest, SelectFromVectorNoResult) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {3}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({false, false, false}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput().size(), 0);
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}
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TYPED_TEST(WhereOpTest, SelectFromVector) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {3}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({true, false, true}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 2}));
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}
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TYPED_TEST(WhereOpTest, SelectFromMatrixNoResult) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {3, 3}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({false, false, false, //
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false, false, false, //
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false, false, false}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_EQ(m.GetOutput().size(), 0);
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}
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TYPED_TEST(WhereOpTest, SelectFromMatrix1) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {3, 1}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({true, false, true}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, //
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2, 0}));
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}
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TYPED_TEST(WhereOpTest, SelectFromMatrix2) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {3, 3}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({true, true, false, //
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true, false, false, //
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true, false, true}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, //
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0, 1, //
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1, 0, //
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2, 0, //
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2, 2}));
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}
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TYPED_TEST(WhereOpTest, SelectFromMatrix3) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {3, 5}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(),
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GetCompatibleData<TypeParam>({true, false, false, true, true, //
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false, true, true, false, false, //
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true, false, true, false, false}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, //
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0, 3, //
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0, 4, //
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1, 1, //
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1, 2, //
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2, 0, //
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2, 2}));
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}
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TYPED_TEST(WhereOpTest, SelectFromRank3TensorNoResult) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {2, 2, 2}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({false, false, false, false, //
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false, false, false, false}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_EQ(m.GetOutput().size(), 0);
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}
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TYPED_TEST(WhereOpTest, SelectFromRank3Tensor1) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {2, 1, 3}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({true, false, true, //
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false, false, true}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, //
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0, 0, 2, //
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1, 0, 2}));
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}
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TYPED_TEST(WhereOpTest, SelectFromRank3Tensor2) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {2, 2, 2}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(), GetCompatibleData<TypeParam>({true, true, false, true, //
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false, false, true, true}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, //
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0, 0, 1, //
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0, 1, 1, //
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1, 1, 0, //
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1, 1, 1}));
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}
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TYPED_TEST(WhereOpTest, SelectFromRank3Tensor3) {
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IntegerWhereOpModel m({GetTfLiteType<TypeParam>(), {2, 3, 2}},
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{TensorType_INT64, {}});
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m.PopulateTensor<TypeParam>(
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m.input(),
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GetCompatibleData<TypeParam>({true, true, false, true, false, false, //
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false, false, true, false, true, true}));
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, //
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0, 0, 1, //
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0, 1, 1, //
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1, 1, 0, //
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1, 2, 0, //
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1, 2, 1}));
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}
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} // namespace
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} // namespace tflite
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