wehub-resource-sync
325 lines
13 KiB
C++
325 lines
13 KiB
C++
/* Copyright 2020 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 <cstdint>
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#include <vector>
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#include <gtest/gtest.h>
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#include "tensorflow/lite/core/interpreter.h"
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#include "tensorflow/lite/core/kernels/register.h"
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#include "tensorflow/lite/core/model.h"
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#include "tensorflow/lite/kernels/test_util.h"
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namespace tflite {
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namespace {
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using ::testing::ElementsAreArray;
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template <class InputType, class ShapeType = int32_t>
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class BroadcastToOpModel : public SingleOpModel {
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public:
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// BroadcastTo with dynamic shape.
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BroadcastToOpModel(std::initializer_list<int> input_shape,
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std::initializer_list<int> shape_shape) {
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input_ = AddInput({GetTensorType<InputType>(), input_shape});
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shape_ = AddInput({GetTensorType<ShapeType>(), shape_shape});
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output_ = AddOutput(GetTensorType<InputType>());
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SetBuiltinOp(BuiltinOperator_BROADCAST_TO,
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BuiltinOptions_BroadcastToOptions,
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CreateBroadcastToOptions(builder_).Union());
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BuildInterpreter({input_shape, shape_shape});
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}
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// BroadcastTo with const shape.
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BroadcastToOpModel(std::initializer_list<int> input_shape,
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std::initializer_list<int> shape_shape,
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std::initializer_list<ShapeType> shape_values) {
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input_ = AddInput({GetTensorType<InputType>(), input_shape});
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shape_ =
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AddConstInput(GetTensorType<ShapeType>(), shape_values, shape_shape);
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output_ = AddOutput(GetTensorType<InputType>());
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SetBuiltinOp(BuiltinOperator_BROADCAST_TO,
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BuiltinOptions_BroadcastToOptions,
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CreateBroadcastToOptions(builder_).Union());
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BuildInterpreter({input_shape, shape_shape});
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}
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void SetInput(std::initializer_list<InputType> data) {
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PopulateTensor(input_, data);
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}
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void SetShape(std::initializer_list<ShapeType> data) {
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PopulateTensor(shape_, data);
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}
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std::vector<InputType> GetOutput() {
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return ExtractVector<InputType>(output_);
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}
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std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
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protected:
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int input_;
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int shape_;
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int output_;
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};
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template <typename T>
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class BroadcastToOpTest : public ::testing::Test {};
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using DataTypes = ::testing::Types<float, uint8_t, int8_t, int16_t, int32_t>;
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TYPED_TEST_SUITE(BroadcastToOpTest, DataTypes);
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#if GTEST_HAS_DEATH_TEST
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TYPED_TEST(BroadcastToOpTest, ShapeMustBe1D) {
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EXPECT_DEATH(
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BroadcastToOpModel<TypeParam>({2, 3, 4, 4}, {2, 2}, {2, 3, 4, 4}), "");
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// Non-constant Shape tensor.
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BroadcastToOpModel<TypeParam> m({2, 3, 4, 4}, {2, 2});
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m.SetShape({2, 3, 4, 4});
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EXPECT_THAT(m.Invoke(), kTfLiteError);
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}
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TYPED_TEST(BroadcastToOpTest, MismatchDimension) {
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EXPECT_DEATH(BroadcastToOpModel<TypeParam>({2, 4, 1, 2}, {4}, {2, 4, 1, 3}),
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"Output shape must be broadcastable from input shape.");
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EXPECT_DEATH(
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BroadcastToOpModel<TypeParam>({2, 4, 1, 2, 3}, {4}, {2, 4, 1, 2}),
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"Output shape must be broadcastable from input shape.");
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// Non-constant Shape tensor.
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BroadcastToOpModel<TypeParam> m1({2, 4, 1, 2}, {4});
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m1.SetShape({2, 3, 4, 4});
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EXPECT_THAT(m1.Invoke(), kTfLiteError);
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BroadcastToOpModel<TypeParam> m2({2, 4, 1, 2}, {5});
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m2.SetShape({1, 2, 3, 4, 4});
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EXPECT_THAT(m2.Invoke(), kTfLiteError);
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}
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#endif
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TYPED_TEST(BroadcastToOpTest, BroadcastTo1DConstTest) {
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BroadcastToOpModel<TypeParam> m({1}, {1}, {4});
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m.SetInput({3});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 3}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo4DConstTest) {
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BroadcastToOpModel<TypeParam> m({1, 1, 1, 2}, {4}, {1, 1, 2, 2});
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m.SetInput({3, 4});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 4, 3, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo8DConstTest) {
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BroadcastToOpModel<TypeParam> m({1, 1, 1, 1, 1, 1, 2, 1}, {8},
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{1, 1, 1, 1, 1, 1, 2, 2});
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m.SetInput({3, 4});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 1, 1, 1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 4, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo9DConstTest) {
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BroadcastToOpModel<TypeParam> m({1, 1, 1, 1, 1, 1, 1, 2, 1}, {9},
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{1, 1, 1, 1, 1, 1, 1, 2, 2});
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m.SetInput({3, 4});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(),
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ElementsAreArray({1, 1, 1, 1, 1, 1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 4, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo1DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({1}, {1});
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m.SetInput({3});
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m.SetShape({4});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 3}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo4DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({1, 1, 1, 2}, {4});
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m.SetInput({3, 4});
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m.SetShape({1, 1, 2, 2});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 4, 3, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo8DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({1, 1, 1, 1, 1, 1, 2, 1}, {8});
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m.SetInput({3, 4});
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m.SetShape({1, 1, 1, 1, 1, 1, 2, 2});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 1, 1, 1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 4, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastTo9DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({1, 1, 1, 1, 1, 1, 1, 2, 1}, {9});
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m.SetInput({3, 4});
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m.SetShape({1, 1, 1, 1, 1, 1, 1, 2, 2});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(),
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ElementsAreArray({1, 1, 1, 1, 1, 1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 4, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, ComplexBroadcast4DConstTest) {
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BroadcastToOpModel<TypeParam> m({1, 3, 1, 2}, {4}, {3, 3, 2, 2});
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m.SetInput({1, 2, 3, 4, 5, 6});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 2, 2}));
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EXPECT_THAT(
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m.GetOutput(),
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ElementsAreArray({1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6, 1, 2, 1, 2, 3, 4,
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3, 4, 5, 6, 5, 6, 1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6}));
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}
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TYPED_TEST(BroadcastToOpTest, ComplexBroadcast4DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({1, 3, 1, 2}, {4});
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m.SetInput({1, 2, 3, 4, 5, 6});
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m.SetShape({3, 3, 2, 2});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 2, 2}));
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EXPECT_THAT(
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m.GetOutput(),
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ElementsAreArray({1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6, 1, 2, 1, 2, 3, 4,
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3, 4, 5, 6, 5, 6, 1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6}));
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}
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TYPED_TEST(BroadcastToOpTest, ComplexBroadcast6DConstTest) {
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BroadcastToOpModel<TypeParam> m({1, 2, 1, 3, 1, 2}, {6}, {2, 2, 1, 3, 2, 2});
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m.SetInput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 2, 1, 3, 2, 2}));
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EXPECT_THAT(m.GetOutput(),
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ElementsAreArray({1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6,
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7, 8, 7, 8, 9, 10, 9, 10, 11, 12, 11, 12,
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1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6,
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7, 8, 7, 8, 9, 10, 9, 10, 11, 12, 11, 12}));
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}
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TYPED_TEST(BroadcastToOpTest, ComplexBroadcast6DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({1, 2, 1, 3, 1, 2}, {6});
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m.SetInput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
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m.SetShape({2, 2, 1, 3, 2, 2});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 2, 1, 3, 2, 2}));
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EXPECT_THAT(m.GetOutput(),
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ElementsAreArray({1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6,
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7, 8, 7, 8, 9, 10, 9, 10, 11, 12, 11, 12,
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1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6,
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7, 8, 7, 8, 9, 10, 9, 10, 11, 12, 11, 12}));
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}
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TYPED_TEST(BroadcastToOpTest, ComplexBroadcast8DConstTest) {
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BroadcastToOpModel<TypeParam> m({1, 3, 1, 2, 1, 4, 1, 1}, {8},
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{2, 3, 1, 2, 2, 4, 1, 1});
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m.SetInput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
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13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 3, 1, 2, 2, 4, 1, 1}));
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EXPECT_THAT(
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m.GetOutput(),
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ElementsAreArray({1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6,
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7, 8, 9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16,
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13, 14, 15, 16, 17, 18, 19, 20, 17, 18, 19, 20, 21, 22,
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23, 24, 21, 22, 23, 24, 1, 2, 3, 4, 1, 2, 3, 4,
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5, 6, 7, 8, 5, 6, 7, 8, 9, 10, 11, 12, 9, 10,
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11, 12, 13, 14, 15, 16, 13, 14, 15, 16, 17, 18, 19, 20,
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17, 18, 19, 20, 21, 22, 23, 24, 21, 22, 23, 24}));
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}
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TYPED_TEST(BroadcastToOpTest, ComplexBroadcast8DDynamicTest) {
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BroadcastToOpModel<TypeParam> m({2, 1, 1, 2, 1, 4, 1, 1}, {8});
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m.SetInput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
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m.SetShape({2, 3, 2, 2, 2, 4, 1, 1});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 3, 2, 2, 2, 4, 1, 1}));
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EXPECT_THAT(
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m.GetOutput(),
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ElementsAreArray(
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{1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8,
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1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8,
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1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8,
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1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8,
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1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8,
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1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8,
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9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
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9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
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9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
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9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
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9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
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9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16}));
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}
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TYPED_TEST(BroadcastToOpTest, ExtendingShape4DConstTest) {
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BroadcastToOpModel<TypeParam> m({3, 1, 2}, {4}, {3, 3, 2, 2});
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m.SetInput({1, 2, 3, 4, 5, 6});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 2, 2}));
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EXPECT_THAT(
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m.GetOutput(),
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ElementsAreArray({1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6, 1, 2, 1, 2, 3, 4,
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3, 4, 5, 6, 5, 6, 1, 2, 1, 2, 3, 4, 3, 4, 5, 6, 5, 6}));
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}
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TYPED_TEST(BroadcastToOpTest, NoBroadcastingConstTest) {
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BroadcastToOpModel<TypeParam> m({3, 1, 2}, {3}, {3, 1, 2});
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m.SetInput({1, 2, 3, 4, 5, 6});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 1, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
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}
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TYPED_TEST(BroadcastToOpTest, NoBroadcasting8DConstTest) {
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BroadcastToOpModel<TypeParam> m({3, 1, 1, 1, 1, 1, 1, 2}, {8},
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{3, 1, 1, 1, 1, 1, 1, 2});
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m.SetInput({1, 2, 3, 4, 5, 6});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 1, 1, 1, 1, 1, 1, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
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}
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TYPED_TEST(BroadcastToOpTest, Int64ShapeConstTest) {
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BroadcastToOpModel<TypeParam, int64_t> m({1, 1, 1, 1, 1, 1, 2, 1}, {8},
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{1, 1, 1, 1, 1, 1, 2, 2});
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m.SetInput({3, 4});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 1, 1, 1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 4, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, Int64ShapeDDynamicTest) {
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BroadcastToOpModel<TypeParam, int64_t> m({1, 1, 1, 1, 1, 1, 2, 1}, {8});
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m.SetInput({3, 4});
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m.SetShape({1, 1, 1, 1, 1, 1, 2, 2});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 1, 1, 1, 1, 2, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 4, 4}));
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}
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TYPED_TEST(BroadcastToOpTest, BroadcastToEmtpyShapeTest) {
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BroadcastToOpModel<TypeParam> m({3, 1, 2}, {3}, {3, 0, 2});
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m.SetInput({1, 2, 3, 4, 5, 6});
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ASSERT_EQ(m.Invoke(), kTfLiteOk);
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 0, 2}));
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}
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} // namespace
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} // namespace tflite
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