Add tile op tests with const input
PiperOrigin-RevId: 251637948
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A. Unique TensorFlower
TensorFlower Gardener
parent
8b7052c4d8
commit
770481fb3e
@ -23,24 +23,16 @@ namespace tflite {
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namespace {
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using ::testing::ElementsAreArray;
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class TileOpModel : public SingleOpModel {
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class TileOpBaseModel : public SingleOpModel {
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public:
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TileOpModel(std::initializer_list<int> input_shape, TensorType input_type,
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TensorType multiply_type) {
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input_ = AddInput(input_type);
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multipliers_ = AddInput(TensorType_INT32);
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output_ = AddOutput(input_type);
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SetBuiltinOp(BuiltinOperator_TILE, BuiltinOptions_TileOptions, 0);
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BuildInterpreter({input_shape, {static_cast<int>(input_shape.size())}});
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}
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template <typename T>
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void SetInput(std::initializer_list<T> data) {
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PopulateTensor<T>(input_, data);
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}
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void SetMultipliers(std::initializer_list<int32_t> data) {
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PopulateTensor<int32_t>(multipliers_, data);
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template <typename T>
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void SetMultipliers(std::initializer_list<T> data) {
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PopulateTensor<T>(multipliers_, data);
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}
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template <typename T>
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@ -57,30 +49,83 @@ class TileOpModel : public SingleOpModel {
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};
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template <typename T>
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void Check(std::initializer_list<int> input_shape,
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std::initializer_list<T> input_data,
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std::initializer_list<int> multipliers_data,
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std::initializer_list<int> exp_output_shape,
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std::initializer_list<T> exp_output_data, TensorType input_type,
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TensorType multiply_type) {
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TileOpModel m(input_shape, input_type, multiply_type);
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m.SetInput(input_data);
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m.SetMultipliers(multipliers_data);
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m.Invoke();
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class TileOpConstModel : public TileOpBaseModel {
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public:
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TileOpConstModel(std::initializer_list<int> input_shape,
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TensorType input_type, TensorType multiply_type,
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std::initializer_list<T> multipliers_data) {
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input_ = AddInput(input_type);
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multipliers_ = AddConstInput(multiply_type, multipliers_data,
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{static_cast<int>(multipliers_data.size())});
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output_ = AddOutput(input_type);
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SetBuiltinOp(BuiltinOperator_TILE, BuiltinOptions_TileOptions, 0);
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BuildInterpreter({input_shape, {static_cast<int>(input_shape.size())}});
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}
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};
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(exp_output_shape));
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EXPECT_THAT(m.GetOutput<T>(), ElementsAreArray(exp_output_data));
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class TileOpDynamicModel : public TileOpBaseModel {
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public:
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TileOpDynamicModel(std::initializer_list<int> input_shape,
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TensorType input_type, TensorType multiply_type) {
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input_ = AddInput(input_type);
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multipliers_ = AddInput(multiply_type);
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output_ = AddOutput(input_type);
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SetBuiltinOp(BuiltinOperator_TILE, BuiltinOptions_TileOptions, 0);
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BuildInterpreter({input_shape, {static_cast<int>(input_shape.size())}});
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}
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};
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enum class TestType {
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kConst = 0,
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kDynamic = 1,
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};
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template <typename InputType, typename MultipliersType = int32_t>
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void Check(std::initializer_list<int> input_shape,
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std::initializer_list<InputType> input_data,
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std::initializer_list<MultipliersType> multipliers_data,
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std::initializer_list<int> exp_output_shape,
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std::initializer_list<InputType> exp_output_data,
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TensorType input_type, TensorType multiply_type,
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TestType test_type) {
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switch (test_type) {
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case TestType::kConst: {
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TileOpConstModel<MultipliersType> m(input_shape, input_type,
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multiply_type, multipliers_data);
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m.SetInput(input_data);
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(exp_output_shape));
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EXPECT_THAT(m.template GetOutput<InputType>(),
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ElementsAreArray(exp_output_data));
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return;
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}
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case TestType::kDynamic: {
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TileOpDynamicModel m(input_shape, input_type, multiply_type);
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m.SetInput(input_data);
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m.SetMultipliers(multipliers_data);
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m.Invoke();
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EXPECT_THAT(m.GetOutputShape(), ElementsAreArray(exp_output_shape));
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EXPECT_THAT(m.template GetOutput<InputType>(),
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ElementsAreArray(exp_output_data));
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return;
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}
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}
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}
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TEST(TileTest, Float32Vector) {
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Check<float>(/*input_shape=*/{3}, /*input_data=*/{1.0, 2.0, 3.0},
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class TileTest : public ::testing::TestWithParam<TestType> {};
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TEST_P(TileTest, Float32Vector) {
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Check<float>(/*input_shape=*/{3},
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/*input_data=*/{1.0, 2.0, 3.0},
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/*multipliers_data=*/{2}, /*exp_output_shape=*/{6},
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/*exp_output_data=*/{1.0, 2.0, 3.0, 1.0, 2.0, 3.0},
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/*input_type=*/TensorType_FLOAT32,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, Float32Matrix) {
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TEST_P(TileTest, Float32Matrix) {
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Check<float>(
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/*input_shape=*/{2, 3},
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/*input_data=*/{11.f, 12.f, 13.f, 21.f, 22.f, 23.f},
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@ -88,10 +133,10 @@ TEST(TileTest, Float32Matrix) {
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/*exp_output_data=*/
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{11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f, 13.f, 21.f, 22.f, 23.f},
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/*input_type=*/TensorType_FLOAT32,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, Float32HighDimension) {
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TEST_P(TileTest, Float32HighDimension) {
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Check<float>(
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/*input_shape=*/{1, 2, 3},
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/*input_data=*/{11.f, 12.f, 13.f, 21.f, 22.f, 23.f},
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@ -102,30 +147,30 @@ TEST(TileTest, Float32HighDimension) {
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11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f,
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13.f, 21.f, 22.f, 23.f},
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/*input_type=*/TensorType_FLOAT32,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, Uint8Matrix) {
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TEST_P(TileTest, Uint8Matrix) {
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Check<uint8_t>(
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/*input_shape=*/{2, 3},
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/*input_data=*/{11, 12, 13, 21, 22, 23},
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/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
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/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
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/*input_type=*/TensorType_UINT8,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, Int32Matrix) {
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TEST_P(TileTest, Int32Matrix) {
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Check<int32_t>(
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/*input_shape=*/{2, 3},
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/*input_data=*/{11, 12, 13, 21, 22, 23},
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/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
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/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
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/*input_type=*/TensorType_INT32,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, BooleanMatrix) {
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TEST_P(TileTest, BooleanMatrix) {
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Check<bool>(
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/*input_shape=*/{2, 3},
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/*input_data=*/{true, false, false, true, true, false},
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@ -134,27 +179,31 @@ TEST(TileTest, BooleanMatrix) {
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{true, false, false, true, true, false, true, false, false, true, true,
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false},
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/*input_type=*/TensorType_BOOL,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, Int64Matrix) {
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TEST_P(TileTest, Int64Matrix) {
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Check<int64_t>(
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/*input_shape=*/{2, 3},
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/*input_data=*/{11, 12, 13, 21, 22, 23},
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/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
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/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
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/*input_type=*/TensorType_INT64,
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/*multiply_type=*/TensorType_INT32);
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/*multiply_type=*/TensorType_INT32, GetParam());
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}
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TEST(TileTest, Int64Matrix64Multipliers) {
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Check<int64_t>(
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TEST_P(TileTest, Int64Matrix64Multipliers) {
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Check<int64_t, int64_t>(
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/*input_shape=*/{2, 3},
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/*input_data=*/{11, 12, 13, 21, 22, 23},
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/*multipliers_data=*/{2, 1}, /*exp_output_shape=*/{4, 3},
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/*exp_output_data=*/{11, 12, 13, 21, 22, 23, 11, 12, 13, 21, 22, 23},
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/*input_type=*/TensorType_INT64,
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/*multiply_type=*/TensorType_INT64);
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/*multiply_type=*/TensorType_INT64, GetParam());
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}
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INSTANTIATE_TEST_SUITE_P(TileTest, TileTest,
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::testing::Values(TestType::kConst,
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TestType::kDynamic));
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} // namespace
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} // namespace tflite
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