Merge pull request #27371 from Dayananda-V:tflite_unpack_test_append
PiperOrigin-RevId: 241423125
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TensorFlower Gardener
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@ -12,7 +12,6 @@ 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 <vector>
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#include <gtest/gtest.h>
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#include "tensorflow/lite/interpreter.h"
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#include "tensorflow/lite/kernels/register.h"
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@ -22,7 +21,7 @@ limitations under the License.
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namespace tflite {
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namespace {
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using ::testing::ElementsAre;
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using ::testing::ElementsAreArray;
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template <typename T>
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class UnpackOpModel : public SingleOpModel {
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@ -67,192 +66,97 @@ class UnpackOpModel : public SingleOpModel {
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std::vector<int> outputs_;
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};
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// float32 tests.
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TEST(UnpackOpTest, FloatThreeOutputs) {
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UnpackOpModel<float> model({TensorType_FLOAT32, {3, 2}}, 0);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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template <typename T>
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void Check(int axis, const std::initializer_list<int>& input_shape,
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const std::initializer_list<T>& input_data,
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const std::vector<std::vector<int>>& exp_output_shape,
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const std::vector<std::vector<T>>& exp_output_data,
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const TensorType& type = TensorType_FLOAT32) {
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UnpackOpModel<T> m({type, input_shape}, axis);
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m.SetInput(input_data);
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m.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 3);
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EXPECT_THAT(output_shapes[0], ElementsAre(2));
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EXPECT_THAT(output_shapes[1], ElementsAre(2));
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EXPECT_THAT(output_shapes[2], ElementsAre(2));
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EXPECT_THAT(m.GetOutputShapes(), ElementsAreArray(exp_output_shape));
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// Check outputs values.
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const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 3);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 2));
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EXPECT_THAT(output_datas[1], ElementsAre(3, 4));
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EXPECT_THAT(output_datas[2], ElementsAre(5, 6));
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EXPECT_THAT(m.GetOutputDatas(), ElementsAreArray(exp_output_data));
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}
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// float32 tests.
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TEST(UnpackOpTest, FloatThreeOutputs) {
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Check<float>(/*axis=*/0, /*input_shape=*/{3, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{2}, {2}, {2}},
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/*expected_output_data=*/{{1, 2}, {3, 4}, {5, 6}});
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}
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TEST(UnpackOpTest, FloatThreeOutputsAxisOne) {
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UnpackOpModel<float> model({TensorType_FLOAT32, {3, 2}}, 1);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 2);
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EXPECT_THAT(output_shapes[0], ElementsAre(3));
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EXPECT_THAT(output_shapes[1], ElementsAre(3));
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// Check outputs values.
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const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 2);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5));
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EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6));
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Check<float>(/*axis=*/1, /*input_shape=*/{3, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{3}, {3}},
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/*expected_output_data=*/{{1, 3, 5}, {2, 4, 6}});
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}
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TEST(UnpackOpTest, FloatThreeOutputsNegativeAxisOne) {
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UnpackOpModel<float> model({TensorType_FLOAT32, {3, 2}}, -1);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 2);
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EXPECT_THAT(output_shapes[0], ElementsAre(3));
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EXPECT_THAT(output_shapes[1], ElementsAre(3));
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// Check outputs values.
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const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 2);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5));
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EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6));
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Check<float>(/*axis=*/-1, /*input_shape=*/{3, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{3}, {3}},
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/*expected_output_data=*/{{1, 3, 5}, {2, 4, 6}});
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}
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TEST(UnpackOpTest, FloatThreeOutputsNegativeAxisTwo) {
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UnpackOpModel<float> model({TensorType_FLOAT32, {3, 2}}, -2);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 3);
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EXPECT_THAT(output_shapes[0], ElementsAre(2));
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EXPECT_THAT(output_shapes[1], ElementsAre(2));
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EXPECT_THAT(output_shapes[2], ElementsAre(2));
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// Check outputs values.
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const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 3);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 2));
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EXPECT_THAT(output_datas[1], ElementsAre(3, 4));
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EXPECT_THAT(output_datas[2], ElementsAre(5, 6));
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Check<float>(/*axis=*/-2, /*input_shape=*/{3, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{2}, {2}, {2}},
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/*expected_output_data=*/{{1, 2}, {3, 4}, {5, 6}});
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}
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TEST(UnpackOpTest, FloatOneOutput) {
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UnpackOpModel<float> model({TensorType_FLOAT32, {1, 6}}, 0);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 1);
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EXPECT_THAT(output_shapes[0], ElementsAre(6));
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// Check outputs values.
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const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 1);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 2, 3, 4, 5, 6));
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Check<float>(/*axis=*/0, /*input_shape=*/{1, 6},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{6}},
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/*expected_output_data=*/{{1, 2, 3, 4, 5, 6}});
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}
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TEST(UnpackOpTest, FloatThreeDimensionsOutputs) {
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UnpackOpModel<float> model({TensorType_FLOAT32, {2, 2, 2}}, 2);
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model.SetInput({1, 2, 3, 4, 5, 6, 7, 8});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 2);
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EXPECT_THAT(output_shapes[0], ElementsAre(2, 2));
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EXPECT_THAT(output_shapes[1], ElementsAre(2, 2));
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// Check outputs values.
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const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 2);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5, 7));
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EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6, 8));
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Check<float>(/*axis=*/2, /*input_shape=*/{2, 2, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6, 7, 8},
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/*expected_output_shape=*/{{2, 2}, {2, 2}},
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/*expected_output_data=*/{{1, 3, 5, 7}, {2, 4, 6, 8}});
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}
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// int32 tests.
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TEST(UnpackOpTest, IntThreeOutputs) {
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UnpackOpModel<int32_t> model({TensorType_INT32, {3, 2}}, 0);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 3);
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EXPECT_THAT(output_shapes[0], ElementsAre(2));
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EXPECT_THAT(output_shapes[1], ElementsAre(2));
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EXPECT_THAT(output_shapes[2], ElementsAre(2));
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// Check outputs values.
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const std::vector<std::vector<int32_t>>& output_datas =
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model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 3);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 2));
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EXPECT_THAT(output_datas[1], ElementsAre(3, 4));
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EXPECT_THAT(output_datas[2], ElementsAre(5, 6));
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Check<int32_t>(/*axis=*/0, /*input_shape=*/{3, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{2}, {2}, {2}},
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/*expected_output_data=*/{{1, 2}, {3, 4}, {5, 6}},
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/*type=*/TensorType_INT32);
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}
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TEST(UnpackOpTest, IntThreeOutputsAxisOne) {
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UnpackOpModel<int32_t> model({TensorType_INT32, {3, 2}}, 1);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 2);
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EXPECT_THAT(output_shapes[0], ElementsAre(3));
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EXPECT_THAT(output_shapes[1], ElementsAre(3));
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// Check outputs values.
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const std::vector<std::vector<int32_t>>& output_datas =
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model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 2);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5));
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EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6));
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Check<int32_t>(/*axis=*/1, /*input_shape=*/{3, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{3}, {3}},
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/*expected_output_data=*/{{1, 3, 5}, {2, 4, 6}},
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/*type=*/TensorType_INT32);
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}
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TEST(UnpackOpTest, IntOneOutput) {
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UnpackOpModel<int32_t> model({TensorType_INT32, {1, 6}}, 0);
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model.SetInput({1, 2, 3, 4, 5, 6});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 1);
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EXPECT_THAT(output_shapes[0], ElementsAre(6));
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// Check outputs values.
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const std::vector<std::vector<int32_t>>& output_datas =
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model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 1);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 2, 3, 4, 5, 6));
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Check<int32_t>(/*axis=*/0, /*input_shape=*/{1, 6},
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/*input_data=*/{1, 2, 3, 4, 5, 6},
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/*expected_output_shape=*/{{6}},
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/*expected_output_data=*/{{1, 2, 3, 4, 5, 6}},
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/*type=*/TensorType_INT32);
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}
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TEST(UnpackOpTest, IntThreeDimensionsOutputs) {
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UnpackOpModel<int32_t> model({TensorType_INT32, {2, 2, 2}}, 2);
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model.SetInput({1, 2, 3, 4, 5, 6, 7, 8});
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model.Invoke();
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// Check outputs shapes.
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const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes();
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EXPECT_EQ(output_shapes.size(), 2);
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EXPECT_THAT(output_shapes[0], ElementsAre(2, 2));
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EXPECT_THAT(output_shapes[1], ElementsAre(2, 2));
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// Check outputs values.
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const std::vector<std::vector<int32_t>>& output_datas =
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model.GetOutputDatas();
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EXPECT_EQ(output_datas.size(), 2);
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EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5, 7));
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EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6, 8));
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Check<int32_t>(/*axis=*/2, /*input_shape=*/{2, 2, 2},
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/*input_data=*/{1, 2, 3, 4, 5, 6, 7, 8},
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/*expected_output_shape=*/{{2, 2}, {2, 2}},
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/*expected_output_data=*/{{1, 3, 5, 7}, {2, 4, 6, 8}},
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/*type=*/TensorType_INT32);
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}
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} // namespace
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