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Commit be6f8762 authored by android-build-team Robot's avatar android-build-team Robot
Browse files

Snap for 6508895 from dd1c5aee to mainline-release 

Change-Id: Id818e1ab8b299184e4090e121f661258fac971c8
parents 661bb4c5 dd1c5aee

current.txt

+3 −2
Original line number Diff line number Diff line
@@ -602,10 +602,11 @@ b69a7615c508acf5c5201efd1bfa3262167874fc3594e2db5a3ff93addd8ac75 android.hardwar 
eb2fa0c883c2185d514be0b84c179b283753ef0c1b77b45b4f359bd23bba8b75 android.hardware.neuralnetworks@1.0::IPreparedModel

92e101b30e47bdf526a01c52cecfbe730def5997b8260ab497eb949eb2a6dcdf android.hardware.neuralnetworks@1.0::types

5f6d3097ba84cb63c430787123f4de1b31c11f90b531b98eae9a8623a5ae962a android.hardware.neuralnetworks@1.1::types

c2711d8748ccbcc858d5d5ec1abf145d9ab4c0b27db8ca215d7c39665a9b6652 android.hardware.neuralnetworks@1.1::types # b/155508675, b/155662254, b/155238914

fb382e986c10b8fbb797a8546e8f9ea6d1107bfe6f3fb7e57f6bbbf1f807a906 android.hardware.neuralnetworks@1.2::IDevice

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

ee1a0dee5be00a6fe2d4d3270068c78016dcb194d768fe07ed894ea20904037f android.hardware.neuralnetworks@1.2::types

882b1c042ff842d7c52a794fab60bf6c599ef6b100ce99fa1772615096811d05 android.hardware.neuralnetworks@1.2::types # b/155508675

9c53b727cfa9efde38ebe3914e1e95939cff29c072a1b8c8f419d24853b98831 android.hardware.neuralnetworks@1.2::types # b/155508675, b/155662254, b/155238914, b/155660285

a785a57447a81e9c130eef6904c3a5c256076c6a04588c40620ebd6fa2660d77 android.hardware.radio@1.2::types

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

fd65298e1e09e0e3c781ab18305920d757dbe55a3b459ce17814ec5cf6dfee99 android.hardware.wifi@1.0::IWifiP2pIface
@@ -719,7 +720,7 @@ a3eddd9bbdc87e8c22764070037dd1154f1cf006e6fba93364c4f85d4c134a19 android.hardwar 
ee9dc34b9925b8367b1111c72bd6d9d375432735e451572ca5a665d8516a7744 android.hardware.neuralnetworks@1.3::IPreparedModel

eee3430cc86c97c7b407495863d8fb61da6f1a64b7721e77b9b4909b11b174e9 android.hardware.neuralnetworks@1.3::IPreparedModelCallback

acf84925f8ee0a651f2ec547ac334034de266479b93af5434f6c1f25e66aba96 android.hardware.neuralnetworks@1.3::types

07801d19ca8a4f20543dae6b4d0c4d8b87e5161d3c431e973a1839cb7915a666 android.hardware.neuralnetworks@1.3::types # b/155508675

e9080d04218e98512b63aace9ff3da52f0130238391f15cbbf7df396a3ec9072 android.hardware.neuralnetworks@1.3::types # b/155508675, b/155662254, b/155238914, b/155660285

b454df853441c12f6e425e8a60dd29fda20f5e6e39b93d1103e4b37495db38aa android.hardware.radio@1.5::IRadio

fcbb0742a88215ee7a6d7ce0825d253eb2b50391fc6c8c48667f9fd7f6d4549e android.hardware.radio@1.5::IRadioIndication

b809193970a91ca637a4b0184767315601d32e3ef3d5992ffbc7a8d14a14f015 android.hardware.radio@1.5::IRadioResponse

neuralnetworks/1.1/types.hal

+6 −0
Original line number Diff line number Diff line
@@ -126,6 +126,8 @@ enum OperationType : @1.0::OperationType { 
     * * 0: A tensor of the same {@link OperandType} as input0.

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

     *      the scale and zeroPoint must be the same as input0.

     *      If all dimensions are reduced and keep_dims is false, the output

     *      shape is [1].

     */

    MEAN = 31,
@@ -232,6 +234,8 @@ enum OperationType : @1.0::OperationType { 
     *      removed.

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

     *      the scale and zeroPoint must be the same as input0.

     *      If all input dimensions are equal to 1 and are to be squeezed, the

     *      output shape is [1].

     */

    SQUEEZE = 34,
@@ -278,6 +282,8 @@ enum OperationType : @1.0::OperationType { 
     *      where k is the number of bits set in shrink_axis_mask.

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

     *      the scale and zeroPoint must be the same as input0.

     *      If shrink_axis_mask is true for all input dimensions, the output

     *      shape is [1].

     */

    STRIDED_SLICE = 35,

neuralnetworks/1.2/types.hal

+8 −0
Original line number Diff line number Diff line
@@ -1955,6 +1955,8 @@ enum OperationType : int32_t { 
     * * 0: A tensor of the same {@link OperandType} as input0.

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

     *      the scale and zeroPoint must be the same as input0.

     *      If all dimensions are reduced and keep_dims is false, the output

     *      shape is [1].

     */

    MEAN = @1.1::OperationType:MEAN,
@@ -2078,6 +2080,8 @@ enum OperationType : int32_t { 
     *      removed.

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

     *      the scale and zeroPoint must be the same as input0.

     *      If all input dimensions are equal to 1 and are to be squeezed, the

     *      output shape is [1].

     */

    SQUEEZE = @1.1::OperationType:SQUEEZE,
@@ -2125,6 +2129,8 @@ enum OperationType : int32_t { 
     *      where k is the number of bits set in shrink_axis_mask.

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

     *      the scale and zeroPoint must be the same as input0.

     *      If shrink_axis_mask is true for all input dimensions, the output

     *      shape is [1].

     */

    STRIDED_SLICE = @1.1::OperationType:STRIDED_SLICE,
@@ -2239,6 +2245,7 @@ enum OperationType : int32_t { 
     *

     * Outputs:

     * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor.

     *      If input is 1-dimensional, the output shape is [1].

     */

    // There is no underscore in ARG_MAX to avoid name conflict with

    // the macro defined in libc/kernel/uapi/linux/limits.h.
@@ -2263,6 +2270,7 @@ enum OperationType : int32_t { 
     *

     * Outputs:

     * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor.

     *      If input is 1-dimensional, the output shape is [1].

     */

    ARGMIN = 40,  // See ARGMAX for naming discussion.

neuralnetworks/1.3/types.hal

+8 −0
Original line number Diff line number Diff line
@@ -2012,6 +2012,8 @@ enum OperationType : int32_t { 
     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and

     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,

     *      the scale and zeroPoint must be the same as input0.

     *      If all dimensions are reduced and keep_dims is false, the output

     *      shape is [1].

     */

    MEAN = @1.2::OperationType:MEAN,
@@ -2141,6 +2143,8 @@ enum OperationType : int32_t { 
     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and

     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,

     *      the scale and zeroPoint must be the same as input0.

     *      If all input dimensions are equal to 1 and are to be squeezed, the

     *      output shape is [1].

     */

    SQUEEZE = @1.2::OperationType:SQUEEZE,
@@ -2190,6 +2194,8 @@ enum OperationType : int32_t { 
     *      For a {@link OperandType::TENSOR_QUANT8_ASYMM} and

     *      {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor,

     *      the scale and zeroPoint must be the same as input0.

     *      If shrink_axis_mask is true for all input dimensions, the output

     *      shape is [1].

     */

    STRIDED_SLICE = @1.2::OperationType:STRIDED_SLICE,
@@ -2313,6 +2319,7 @@ enum OperationType : int32_t { 
     *

     * Outputs:

     * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor.

     *      If input is 1-dimensional, the output shape is [1].

     */

    // There is no underscore in ARG_MAX to avoid name conflict with

    // the macro defined in libc/kernel/uapi/linux/limits.h.
@@ -2338,6 +2345,7 @@ enum OperationType : int32_t { 
     *

     * Outputs:

     * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor.

     *      If input is 1-dimensional, the output shape is [1].

     */

    ARGMIN = @1.2::OperationType:ARGMIN,  // See ARGMAX for naming discussion.

tv/tuner/1.0/vts/functional/FrontendTests.cpp

+115 −0
Original line number Diff line number Diff line
@@ -246,6 +246,120 @@ AssertionResult FrontendTests::stopScanFrontend() { 
    return AssertionResult(status == Result::SUCCESS);

}



void FrontendTests::verifyFrontendStatus(vector<FrontendStatusType> statusTypes,

                                         vector<FrontendStatus> expectStatuses) {

    ASSERT_TRUE(mFrontend) << "Frontend is not opened yet.";

    Result status;

    vector<FrontendStatus> realStatuses;



    mFrontend->getStatus(statusTypes, [&](Result result, const hidl_vec<FrontendStatus>& statuses) {

        status = result;

        realStatuses = statuses;

    });



    ASSERT_TRUE(realStatuses.size() == statusTypes.size());

    for (int i = 0; i < statusTypes.size(); i++) {

        FrontendStatusType type = statusTypes[i];

        switch (type) {

            case FrontendStatusType::DEMOD_LOCK: {

                ASSERT_TRUE(realStatuses[i].isDemodLocked() == expectStatuses[i].isDemodLocked());

                break;

            }

            case FrontendStatusType::SNR: {

                ASSERT_TRUE(realStatuses[i].snr() == expectStatuses[i].snr());

                break;

            }

            case FrontendStatusType::BER: {

                ASSERT_TRUE(realStatuses[i].ber() == expectStatuses[i].ber());

                break;

            }

            case FrontendStatusType::PER: {

                ASSERT_TRUE(realStatuses[i].per() == expectStatuses[i].per());

                break;

            }

            case FrontendStatusType::PRE_BER: {

                ASSERT_TRUE(realStatuses[i].preBer() == expectStatuses[i].preBer());

                break;

            }

            case FrontendStatusType::SIGNAL_QUALITY: {

                ASSERT_TRUE(realStatuses[i].signalQuality() == expectStatuses[i].signalQuality());

                break;

            }

            case FrontendStatusType::SIGNAL_STRENGTH: {

                ASSERT_TRUE(realStatuses[i].signalStrength() == expectStatuses[i].signalStrength());

                break;

            }

            case FrontendStatusType::SYMBOL_RATE: {

                ASSERT_TRUE(realStatuses[i].symbolRate() == expectStatuses[i].symbolRate());

                break;

            }

            case FrontendStatusType::FEC: {

                ASSERT_TRUE(realStatuses[i].innerFec() == expectStatuses[i].innerFec());

                break;

            }

            case FrontendStatusType::MODULATION: {

                // TODO: check modulation status

                break;

            }

            case FrontendStatusType::SPECTRAL: {

                ASSERT_TRUE(realStatuses[i].inversion() == expectStatuses[i].inversion());

                break;

            }

            case FrontendStatusType::LNB_VOLTAGE: {

                ASSERT_TRUE(realStatuses[i].lnbVoltage() == expectStatuses[i].lnbVoltage());

                break;

            }

            case FrontendStatusType::PLP_ID: {

                ASSERT_TRUE(realStatuses[i].plpId() == expectStatuses[i].plpId());

                break;

            }

            case FrontendStatusType::EWBS: {

                ASSERT_TRUE(realStatuses[i].isEWBS() == expectStatuses[i].isEWBS());

                break;

            }

            case FrontendStatusType::AGC: {

                ASSERT_TRUE(realStatuses[i].agc() == expectStatuses[i].agc());

                break;

            }

            case FrontendStatusType::LNA: {

                ASSERT_TRUE(realStatuses[i].isLnaOn() == expectStatuses[i].isLnaOn());

                break;

            }

            case FrontendStatusType::LAYER_ERROR: {

                vector<bool> realLayberError = realStatuses[i].isLayerError();

                vector<bool> expectLayerError = expectStatuses[i].isLayerError();

                ASSERT_TRUE(realLayberError.size() == expectLayerError.size());

                for (int i = 0; i < realLayberError.size(); i++) {

                    ASSERT_TRUE(realLayberError[i] == expectLayerError[i]);

                }

                break;

            }

            case FrontendStatusType::MER: {

                ASSERT_TRUE(realStatuses[i].mer() == expectStatuses[i].mer());

                break;

            }

            case FrontendStatusType::FREQ_OFFSET: {

                ASSERT_TRUE(realStatuses[i].freqOffset() == expectStatuses[i].freqOffset());

                break;

            }

            case FrontendStatusType::HIERARCHY: {

                ASSERT_TRUE(realStatuses[i].hierarchy() == expectStatuses[i].hierarchy());

                break;

            }

            case FrontendStatusType::RF_LOCK: {

                ASSERT_TRUE(realStatuses[i].isRfLocked() == expectStatuses[i].isRfLocked());

                break;

            }

            case FrontendStatusType::ATSC3_PLP_INFO:

                // TODO: verify plpinfo

                break;

            default:

                continue;

        }

    }

    ASSERT_TRUE(status == Result::SUCCESS);

}



AssertionResult FrontendTests::tuneFrontend(FrontendConfig config) {

    EXPECT_TRUE(mFrontendCallback)

            << "test with openFrontendById/setFrontendCallback/getFrontendInfo first.";
@@ -294,6 +408,7 @@ void FrontendTests::tuneTest(FrontendConfig frontendConf) { 
    ASSERT_TRUE(openFrontendById(feId));

    ASSERT_TRUE(setFrontendCallback());

    ASSERT_TRUE(tuneFrontend(frontendConf));

    verifyFrontendStatus(frontendConf.tuneStatusTypes, frontendConf.expectTuneStatuses);

    ASSERT_TRUE(stopTuneFrontend());

    ASSERT_TRUE(closeFrontend());

}