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Commit 76f5263d authored by Slava Shklyaev's avatar Slava Shklyaev Committed by Gerrit Code Review
Browse files

Merge changes from topic "quant_coupling" 

* changes:
  Add QUANT8_ASYMM_SIGNED support to SELECT op
  Add quantization coupling test
  Combine test parameters into TestConfig structure
parents ddad94ab 3683c785

current.txt

+2 −2
Original line number Diff line number Diff line
@@ -578,7 +578,7 @@ f1109cbb10297b7429a11fab42afa912710b303c9bf20bd5cdb8bd57b9c84186 android.hardwar 
9d8ee57c490ffeaa28f702eaea8d198cb510e4bbfb99e6cb5f63e73341057c7c android.hardware.neuralnetworks@1.1::types

fb382e986c10b8fbb797a8546e8f9ea6d1107bfe6f3fb7e57f6bbbf1f807a906 android.hardware.neuralnetworks@1.2::IDevice

40e71cd693de5b832325c5d8f081f2ff20a7ba2b89d401cee5b4b3eb0e241681 android.hardware.neuralnetworks@1.2::IPreparedModel

71c0f7127335e5b74d1615d5e7f129831b43ffbae5318ad0924d7d8d8910a859 android.hardware.neuralnetworks@1.2::types

72de91c3feba4b19c159cd1c413cbea596b78240caa43e31194e20e6f5b05c49 android.hardware.neuralnetworks@1.2::types

a785a57447a81e9c130eef6904c3a5c256076c6a04588c40620ebd6fa2660d77 android.hardware.radio@1.2::types

1a6e2bd289f22931c526b21916910f1d4c436b7acb9556e4243de4ce8e6cc2e4 android.hardware.soundtrigger@2.0::ISoundTriggerHwCallback

fd65298e1e09e0e3c781ab18305920d757dbe55a3b459ce17814ec5cf6dfee99 android.hardware.wifi@1.0::IWifiP2pIface
@@ -597,7 +597,7 @@ adb0efdf1462e9b2e742c0dcadd598666aac551f178be06e755bfcdf5797abd0 android.hardwar 
9e59fffceed0dd72a9799e04505db5f777bbbea1af0695ba4107ef6d967c6fda android.hardware.neuralnetworks@1.3::IDevice

4a6c3b3556da951b4def21ba579a227c022980fe4465df6cdfbe20628fa75f5a android.hardware.neuralnetworks@1.3::IPreparedModel

94e803236398bed1febb11cc21051bc42ec003700139b099d6c479e02a7ca3c3 android.hardware.neuralnetworks@1.3::IPreparedModelCallback

c511b1427b1c3f76af90967bbddaaf250db983a8d3abb9ff189fb5a807cf3d4d android.hardware.neuralnetworks@1.3::types

554baa3b317e077b850afcbaac99daeef56861b1786540e56275a4fcad1f43e3 android.hardware.neuralnetworks@1.3::types

274fb1254a6d1a97824ec5c880eeefc0e410dc6d3a2a4c34052201169d2b7de0 android.hardware.radio@1.5::types

c8e81d912827a5d49b2ddcdc4eb4556c5d231a899a1dca879309e04210daa4a0 android.hardware.radio@1.5::IRadio

a62a93faf173b14a6175b683ebf61ffa568dc61f81e369d2dce7b1265e86cf2f android.hardware.radio@1.5::IRadioIndication

neuralnetworks/1.2/types.hal

+6 −5
Original line number Diff line number Diff line
@@ -2448,15 +2448,17 @@ enum OperationType : int32_t { 
     *       then clipping is disabled.

     *       If all the input tensors have type {@link OperandType::TENSOR_FLOAT32},

     *       this scalar must be of the type {@link OperandType::FLOAT32},

     *       otherwise if all the input tensors have the type {@link OperandType::TENSOR_FLOAT16},

     *       this scalar must be of type {@link OperandType::FLOAT16}.

     *       otherwise if all the input tensors have the type

     *       {@link OperandType::TENSOR_FLOAT16}, this scalar must be

     *       of type {@link OperandType::FLOAT16}.

     * * 50: The clipping threshold for the output from the

     *       projection layer, such that values are bound within

     *       [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.

     *       If all the input tensors have type {@link OperandType::TENSOR_FLOAT32},

     *       this scalar must be of the type {@link OperandType::FLOAT32},

     *       otherwise if all the input tensors have the type {@link OperandType::TENSOR_FLOAT16},

     *       this scalar must be of type {@link OperandType::FLOAT16}.

     *       otherwise if all the input tensors have the type

     *       {@link OperandType::TENSOR_FLOAT16}, this scalar must be

     *       of type {@link OperandType::FLOAT16}.

     * * 51: merge_outputs

     *       An {@link OperandType::BOOL} scalar specifying if the outputs

     *       from forward and backward cells should be merged.
@@ -4124,7 +4126,6 @@ enum OperationType : int32_t { 
     * * 0: A tensor of the same type and shape as input1 and input2.

     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,

     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.

     *

     */

    SELECT = 84,

neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp

+46 −49
Original line number Diff line number Diff line
@@ -58,8 +58,20 @@ using V1_0::Request; 
using V1_1::ExecutionPreference;

using HidlToken = hidl_array<uint8_t, static_cast<uint32_t>(Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;



namespace {



enum class Executor { ASYNC, SYNC, BURST };



enum class OutputType { FULLY_SPECIFIED, UNSPECIFIED, INSUFFICIENT };



struct TestConfig {

    Executor executor;

    MeasureTiming measureTiming;

    OutputType outputType;

};



}  // namespace



Model createModel(const TestModel& testModel) {

    // Model operands.

    hidl_vec<Operand> operands(testModel.operands.size());
@@ -194,31 +206,31 @@ static std::shared_ptr<::android::nn::ExecutionBurstController> CreateBurst( 
    return android::nn::ExecutionBurstController::create(preparedModel,

                                                         std::chrono::microseconds{0});

}

enum class Executor { ASYNC, SYNC, BURST };



void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,

                           Executor executor, MeasureTiming measure, OutputType outputType) {

                           const TestConfig& testConfig) {

    // If output0 does not have size larger than one byte, we can not test with insufficient buffer.

    if (outputType == OutputType::INSUFFICIENT && !isOutputSizeGreaterThanOne(testModel, 0)) {

    if (testConfig.outputType == OutputType::INSUFFICIENT &&

        !isOutputSizeGreaterThanOne(testModel, 0)) {

        return;

    }



    Request request = createRequest(testModel);

    if (outputType == OutputType::INSUFFICIENT) {

    if (testConfig.outputType == OutputType::INSUFFICIENT) {

        makeOutputInsufficientSize(/*outputIndex=*/0, &request);

    }



    ErrorStatus executionStatus;

    hidl_vec<OutputShape> outputShapes;

    Timing timing;

    switch (executor) {

    switch (testConfig.executor) {

        case Executor::ASYNC: {

            SCOPED_TRACE("asynchronous");



            // launch execution

            sp<ExecutionCallback> executionCallback = new ExecutionCallback();

            Return<ErrorStatus> executionLaunchStatus =

                    ExecutePreparedModel(preparedModel, request, measure, executionCallback);

            Return<ErrorStatus> executionLaunchStatus = ExecutePreparedModel(

                    preparedModel, request, testConfig.measureTiming, executionCallback);

            ASSERT_TRUE(executionLaunchStatus.isOk());

            EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
@@ -234,8 +246,8 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo 
            SCOPED_TRACE("synchronous");



            // execute

            Return<ErrorStatus> executionReturnStatus =

                    ExecutePreparedModel(preparedModel, request, measure, &outputShapes, &timing);

            Return<ErrorStatus> executionReturnStatus = ExecutePreparedModel(

                    preparedModel, request, testConfig.measureTiming, &outputShapes, &timing);

            ASSERT_TRUE(executionReturnStatus.isOk());

            executionStatus = static_cast<ErrorStatus>(executionReturnStatus);
@@ -258,14 +270,14 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo 
            // execute burst

            int n;

            std::tie(n, outputShapes, timing, std::ignore) =

                    controller->compute(request, measure, keys);

                    controller->compute(request, testConfig.measureTiming, keys);

            executionStatus = nn::convertResultCodeToErrorStatus(n);



            break;

        }

    }



    if (outputType != OutputType::FULLY_SPECIFIED &&

    if (testConfig.outputType != OutputType::FULLY_SPECIFIED &&

        executionStatus == ErrorStatus::GENERAL_FAILURE) {

        LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "

                     "execute model that it does not support.";
@@ -274,7 +286,7 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo 
                  << std::endl;

        GTEST_SKIP();

    }

    if (measure == MeasureTiming::NO) {

    if (testConfig.measureTiming == MeasureTiming::NO) {

        EXPECT_EQ(UINT64_MAX, timing.timeOnDevice);

        EXPECT_EQ(UINT64_MAX, timing.timeInDriver);

    } else {
@@ -283,7 +295,7 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo 
        }

    }



    switch (outputType) {

    switch (testConfig.outputType) {

        case OutputType::FULLY_SPECIFIED:

            // If the model output operands are fully specified, outputShapes must be either

            // either empty, or have the same number of elements as the number of outputs.
@@ -321,44 +333,29 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo 


void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,

                           bool testDynamicOutputShape) {

    std::initializer_list<OutputType> outputTypesList;

    std::initializer_list<MeasureTiming> measureTimingList;

    std::initializer_list<Executor> executorList;



    if (testDynamicOutputShape) {

        EvaluatePreparedModel(preparedModel, testModel, Executor::ASYNC, MeasureTiming::NO,

                              OutputType::UNSPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::SYNC, MeasureTiming::NO,

                              OutputType::UNSPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::BURST, MeasureTiming::NO,

                              OutputType::UNSPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::ASYNC, MeasureTiming::YES,

                              OutputType::UNSPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::SYNC, MeasureTiming::YES,

                              OutputType::UNSPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::BURST, MeasureTiming::YES,

                              OutputType::UNSPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::ASYNC, MeasureTiming::NO,

                              OutputType::INSUFFICIENT);

        EvaluatePreparedModel(preparedModel, testModel, Executor::SYNC, MeasureTiming::NO,

                              OutputType::INSUFFICIENT);

        EvaluatePreparedModel(preparedModel, testModel, Executor::BURST, MeasureTiming::NO,

                              OutputType::INSUFFICIENT);

        EvaluatePreparedModel(preparedModel, testModel, Executor::ASYNC, MeasureTiming::YES,

                              OutputType::INSUFFICIENT);

        EvaluatePreparedModel(preparedModel, testModel, Executor::SYNC, MeasureTiming::YES,

                              OutputType::INSUFFICIENT);

        EvaluatePreparedModel(preparedModel, testModel, Executor::BURST, MeasureTiming::YES,

                              OutputType::INSUFFICIENT);

        outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};

        measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};

        executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};

    } else {

        EvaluatePreparedModel(preparedModel, testModel, Executor::ASYNC, MeasureTiming::NO,

                              OutputType::FULLY_SPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::SYNC, MeasureTiming::NO,

                              OutputType::FULLY_SPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::BURST, MeasureTiming::NO,

                              OutputType::FULLY_SPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::ASYNC, MeasureTiming::YES,

                              OutputType::FULLY_SPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::SYNC, MeasureTiming::YES,

                              OutputType::FULLY_SPECIFIED);

        EvaluatePreparedModel(preparedModel, testModel, Executor::BURST, MeasureTiming::YES,

                              OutputType::FULLY_SPECIFIED);

        outputTypesList = {OutputType::FULLY_SPECIFIED};

        measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};

        executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};

    }



    for (const OutputType outputType : outputTypesList) {

        for (const MeasureTiming measureTiming : measureTimingList) {

            for (const Executor executor : executorList) {

                const TestConfig testConfig = {.executor = executor,

                                               .measureTiming = measureTiming,

                                               .outputType = outputType};

                EvaluatePreparedModel(preparedModel, testModel, testConfig);

            }

        }

    }

}

neuralnetworks/1.3/types.hal

+9 −6
Original line number Diff line number Diff line
@@ -2375,15 +2375,17 @@ enum OperationType : int32_t { 
     *       then clipping is disabled.

     *       If all the input tensors have type {@link OperandType::TENSOR_FLOAT32},

     *       this scalar must be of the type {@link OperandType::FLOAT32},

     *       otherwise if all the input tensors have the type {@link OperandType::TENSOR_FLOAT16},

     *       this scalar must be of type {@link OperandType::FLOAT16}.

     *       otherwise if all the input tensors have the type

     *       {@link OperandType::TENSOR_FLOAT16}, this scalar must be

     *       of type {@link OperandType::FLOAT16}.

     * * 50: The clipping threshold for the output from the

     *       projection layer, such that values are bound within

     *       [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.

     *       If all the input tensors have type {@link OperandType::TENSOR_FLOAT32},

     *       this scalar must be of the type {@link OperandType::FLOAT32},

     *       otherwise if all the input tensors have the type {@link OperandType::TENSOR_FLOAT16},

     *       this scalar must be of type {@link OperandType::FLOAT16}.

     *       otherwise if all the input tensors have the type

     *       {@link OperandType::TENSOR_FLOAT16}, this scalar must be

     *       of type {@link OperandType::FLOAT16}.

     * * 51: merge_outputs

     *       An {@link OperandType::BOOL} scalar specifying if the outputs

     *       from forward and backward cells should be merged.
@@ -4034,6 +4036,7 @@ enum OperationType : int32_t { 
     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_INT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} (since HAL version 1.3)

     *

     * Supported tensor rank: from 1

     *
@@ -4044,14 +4047,14 @@ enum OperationType : int32_t { 
     *      true) or input2 (if false).

     * * 1: An input tensor of the same shape as input0.

     * * 2: An input tensor of the same shape and type as input1.

     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,

     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM}

     *      and {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,

     *      the scales and zeroPoint can be different from input1 scale and zeroPoint.

     *

     * Outputs:

     * * 0: A tensor of the same type and shape as input1 and input2.

     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor,

     *      the scale and zeroPoint can be different from inputs' scale and zeroPoint.

     *

     */

    SELECT = @1.2::OperationType:SELECT,

neuralnetworks/1.3/vts/functional/CompilationCachingTests.cpp

+14 −28
Original line number Diff line number Diff line
@@ -456,8 +456,7 @@ TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) { 
    }



    // Execute and verify results.

    EvaluatePreparedModel(preparedModel, testModel,

                          /*testDynamicOutputShape=*/false);

    EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

}



TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
@@ -519,8 +518,7 @@ TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) { 
    }



    // Execute and verify results.

    EvaluatePreparedModel(preparedModel, testModel,

                          /*testDynamicOutputShape=*/false);

    EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

}



TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
@@ -541,8 +539,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -566,8 +563,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -590,8 +586,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -615,8 +610,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -727,8 +721,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -752,8 +745,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -776,8 +768,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -801,8 +792,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -914,8 +904,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -937,8 +926,7 @@ TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) { 
        saveModelToCache(model, modelCache, dataCache, &preparedModel);

        ASSERT_NE(preparedModel, nullptr);

        // Execute and verify results.

        EvaluatePreparedModel(preparedModel, testModel,

                              /*testDynamicOutputShape=*/false);

        EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);

        // Check if prepareModelFromCache fails.

        preparedModel = nullptr;

        ErrorStatus status;
@@ -1082,8 +1070,7 @@ TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) { 
                ASSERT_EQ(preparedModel, nullptr);

            } else {

                ASSERT_NE(preparedModel, nullptr);

                EvaluatePreparedModel(preparedModel, testModelAdd,

                                      /*testDynamicOutputShape=*/false);

                EvaluatePreparedModel(preparedModel, testModelAdd, /*testKind=*/TestKind::GENERAL);

            }

        }

    }
@@ -1144,8 +1131,7 @@ TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) { 
                ASSERT_EQ(preparedModel, nullptr);

            } else {

                ASSERT_NE(preparedModel, nullptr);

                EvaluatePreparedModel(preparedModel, testModelAdd,

                                      /*testDynamicOutputShape=*/false);

                EvaluatePreparedModel(preparedModel, testModelAdd, /*testKind=*/TestKind::GENERAL);

            }

        }

    }