Add tests for the slice op with const inputs
PiperOrigin-RevId: 256358275
This commit is contained in:
A. Unique TensorFlower
TensorFlower Gardener
parent
2b96dc608e
commit
cc5b183064
@ -23,20 +23,39 @@ namespace {
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using ::testing::ElementsAreArray;
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enum class TestType {
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CONST = 0,
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DYNAMIC = 1,
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};
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template <typename input_type, typename index_type>
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class SliceOpModel : public SingleOpModel {
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public:
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SliceOpModel(std::initializer_list<int> input_shape,
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std::initializer_list<int> begin_shape,
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std::initializer_list<index_type> begin_data,
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std::initializer_list<int> size_shape,
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TensorType tensor_index_type, TensorType tensor_input_type) {
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std::initializer_list<index_type> size_data,
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TensorType tensor_index_type, TensorType tensor_input_type,
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TestType input_tensor_types) {
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input_ = AddInput(tensor_input_type);
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begin_ = AddInput(tensor_index_type);
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size_ = AddInput(tensor_index_type);
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if (input_tensor_types == TestType::DYNAMIC) {
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begin_ = AddInput(tensor_index_type);
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size_ = AddInput(tensor_index_type);
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} else {
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begin_ =
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AddConstInput(GetTensorType<index_type>(), begin_data, begin_shape);
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size_ = AddConstInput(GetTensorType<index_type>(), size_data, size_shape);
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}
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output_ = AddOutput(tensor_input_type);
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SetBuiltinOp(BuiltinOperator_SLICE, BuiltinOptions_SliceOptions,
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CreateSliceOptions(builder_).Union());
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BuildInterpreter({input_shape, begin_shape, size_shape});
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if (input_tensor_types == TestType::DYNAMIC) {
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PopulateTensor<index_type>(begin_, begin_data);
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PopulateTensor<index_type>(size_, size_data);
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}
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}
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void SetInput(std::initializer_list<input_type> data) {
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@ -45,12 +64,6 @@ class SliceOpModel : public SingleOpModel {
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void SetStringInput(std::vector<string> data) {
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PopulateStringTensor(input_, data);
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}
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void SetBegin(std::initializer_list<index_type> data) {
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PopulateTensor<index_type>(begin_, data);
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}
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void SetSize(std::initializer_list<index_type> data) {
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PopulateTensor<index_type>(size_, data);
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}
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std::vector<input_type> GetOutput() {
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return ExtractVector<input_type>(output_);
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@ -64,57 +77,53 @@ class SliceOpModel : public SingleOpModel {
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int output_;
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};
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TEST(SliceOpTest, In1D) {
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SliceOpModel<float, int32_t> m({4}, {1}, {1}, TensorType_INT32,
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TensorType_FLOAT32);
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class SliceOpTest : public ::testing::TestWithParam<TestType> {};
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TEST_P(SliceOpTest, In1D) {
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SliceOpModel<float, int32_t> m({4}, {1}, {1}, {1}, {2}, TensorType_INT32,
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TensorType_FLOAT32, GetParam());
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m.SetInput({1, 2, 3, 4});
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m.SetBegin({1});
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m.SetSize({2});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({2, 3}));
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}
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TEST(SliceOpTest, In2D) {
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SliceOpModel<float, int32_t> m({2, 3}, {2}, {2}, TensorType_INT32,
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TensorType_FLOAT32);
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TEST_P(SliceOpTest, In2D) {
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SliceOpModel<float, int32_t> m({2, 3}, {2}, {1, 0}, {2}, {1, 2},
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TensorType_INT32, TensorType_FLOAT32,
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GetParam());
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m.SetInput({1, 2, 3, 4, 5, 6});
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m.SetBegin({1, 0});
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m.SetSize({1, 2});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({4, 5}));
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}
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TEST(SliceOpTest, In3D) {
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SliceOpModel<float, int32_t> m({2, 3, 2}, {3}, {4}, TensorType_INT32,
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TensorType_FLOAT32);
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TEST_P(SliceOpTest, In3D) {
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SliceOpModel<float, int32_t> m({2, 3, 2}, {3}, {0, 0, 0}, {3}, {2, 3, 2},
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TensorType_INT32, TensorType_FLOAT32,
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GetParam());
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m.SetInput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
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m.SetBegin({0, 0, 0});
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m.SetSize({2, 3, 2});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 3, 2}));
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EXPECT_THAT(m.GetOutput(),
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ElementsAreArray({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}));
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}
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TEST(SliceOpTest, InputFloat) {
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SliceOpModel<float, int32_t> m({4, 1, 1, 1}, {4}, {4}, TensorType_INT32,
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TensorType_FLOAT32);
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TEST_P(SliceOpTest, InputFloat) {
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SliceOpModel<float, int32_t> m({4, 1, 1, 1}, {4}, {1, 0, 0, 0}, {4},
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{3, 1, 1, 1}, TensorType_INT32,
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TensorType_FLOAT32, GetParam());
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m.SetInput({1, 2, 3, 4});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({3, 1, 1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 1, 1, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({2, 3, 4}));
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}
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TEST(SliceOpTest, IndexInt64) {
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SliceOpModel<float, int64_t> m({4, 1, 1, 1}, {4}, {4}, TensorType_INT64,
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TensorType_FLOAT32);
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TEST_P(SliceOpTest, IndexInt64) {
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SliceOpModel<float, int64_t> m({4, 1, 1, 1}, {4}, {1, 0, 0, 0}, {4},
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{3, 1, 1, 1}, TensorType_INT64,
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TensorType_FLOAT32, GetParam());
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m.SetInput({1, 2, 3, 4});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({3, 1, 1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 1, 1, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({2, 3, 4}));
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@ -122,116 +131,106 @@ TEST(SliceOpTest, IndexInt64) {
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// See these test cases under:
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// https://www.tensorflow.org/versions/master/api_docs/python/tf/slice
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TEST(SliceOpTest, InputInteger1) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, InputInteger1) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{1, 1, 3, 1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({1, 1, 3, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 1, 3, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3}));
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}
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TEST(SliceOpTest, InputInteger2) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, InputInteger2) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{1, 2, 3, 1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({1, 2, 3, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 2, 3, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 4, 4, 4}));
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}
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TEST(SliceOpTest, InputInteger3) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, InputInteger3) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{2, 1, 3, 1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({2, 1, 3, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 3, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 5, 5, 5}));
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}
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TEST(SliceOpTest, SizeMinus1) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, SizeMinus1) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{2, 1, -1, 1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({2, 1, -1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 3, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 5, 5, 5}));
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}
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TEST(SliceOpTest, BeginNonZeroSizeMinus1Axis1) {
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SliceOpModel<int32_t, int32_t> m({3, 3, 2, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, BeginNonZeroSizeMinus1Axis1) {
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SliceOpModel<int32_t, int32_t> m({3, 3, 2, 1}, {4}, {1, 1, 0, 0}, {4},
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{2, -1, 1, 1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9});
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m.SetBegin({1, 1, 0, 0});
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m.SetSize({2, -1, 1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 2, 1, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({5, 6, 8, 9}));
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}
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TEST(SliceOpTest, BeginNonZeroSizeMinus1Axis2) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, BeginNonZeroSizeMinus1Axis2) {
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SliceOpModel<int32_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 1, 0}, {4},
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{2, 1, -1, 1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 1, 0});
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m.SetSize({2, 1, -1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 2, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 5, 5}));
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}
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TEST(SliceOpTest, BeginNonZeroSizeMinus1Axis3) {
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SliceOpModel<int32_t, int32_t> m({3, 1, 2, 3}, {4}, {4}, TensorType_INT32,
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TensorType_INT32);
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TEST_P(SliceOpTest, BeginNonZeroSizeMinus1Axis3) {
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SliceOpModel<int32_t, int32_t> m({3, 1, 2, 3}, {4}, {1, 0, 0, 1}, {4},
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{2, 1, 1, -1}, TensorType_INT32,
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TensorType_INT32, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 1});
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m.SetSize({2, 1, 1, -1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 1, 2}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 5, 5}));
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}
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TEST(SliceOpTest, SliceUint8) {
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SliceOpModel<uint8_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_UINT8);
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TEST_P(SliceOpTest, SliceUint8) {
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SliceOpModel<uint8_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{2, 1, -1, 1}, TensorType_INT32,
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TensorType_UINT8, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({2, 1, -1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 3, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 5, 5, 5}));
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}
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TEST(SliceOpTest, SliceInt8) {
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SliceOpModel<int8_t, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_INT8);
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TEST_P(SliceOpTest, SliceInt8) {
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SliceOpModel<int8_t, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{2, 1, -1, 1}, TensorType_INT32,
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TensorType_INT8, GetParam());
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m.SetInput({1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({2, 1, -1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 3, 1}));
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EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 3, 3, 5, 5, 5}));
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}
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TEST(SliceOpTest, SliceString) {
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SliceOpModel<string, int32_t> m({3, 2, 3, 1}, {4}, {4}, TensorType_INT32,
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TensorType_STRING);
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TEST_P(SliceOpTest, SliceString) {
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SliceOpModel<string, int32_t> m({3, 2, 3, 1}, {4}, {1, 0, 0, 0}, {4},
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{2, 1, -1, 1}, TensorType_INT32,
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TensorType_STRING, GetParam());
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m.SetStringInput({"0,0,0,0", "0,0,1,0", "0,0,2,0", //
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"0,1,0,0", "0,1,1,0", "0,1,2,0", //
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"1,0,0,0", "1,0,1,0", "1,0,2,0", //
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"1,1,0,0", "1,1,1,0", "1,1,2,0", //
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"2,0,0,0", "2,0,1,0", "2,0,2,0", //
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"2,1,0,0", "2,1,1,0", "2,1,2,0"});
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m.SetBegin({1, 0, 0, 0});
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m.SetSize({2, 1, -1, 1});
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 3, 1}));
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EXPECT_THAT(m.GetOutput(),
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@ -239,5 +238,8 @@ TEST(SliceOpTest, SliceString) {
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"2,0,0,0", "2,0,1,0", "2,0,2,0"}));
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}
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INSTANTIATE_TEST_SUITE_P(SliceOpTest, SliceOpTest,
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::testing::Values(TestType::CONST, TestType::DYNAMIC));
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} // namespace
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} // namespace tflite
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