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Commit 8ebc7737 authored by Xusong Wang's avatar Xusong Wang Committed by android-build-merger
Browse files

NN HAL: Upgrade IPreparedModel::executeSynchronously to 1.3. 

am: d4a060bb

Change-Id: I41acc0e984d75b8073195dc4a9c4345198f5ad7e
parents 336af578 d4a060bb

current.txt

+1 −1
Original line number Diff line number Diff line
@@ -595,7 +595,7 @@ c228aaa27f66c48e147159a4f4996c5273191fece1b08de31bd171c61334855e android.hardwar 
adb0efdf1462e9b2e742c0dcadd598666aac551f178be06e755bfcdf5797abd0 android.hardware.keymaster@4.1::IOperation

7a04ea5595ed418ca3e91c28b8bd7353dd988be9be7b0c8c9e64fb4b77bd4523 android.hardware.keymaster@4.1::types

9e59fffceed0dd72a9799e04505db5f777bbbea1af0695ba4107ef6d967c6fda android.hardware.neuralnetworks@1.3::IDevice

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

258825966435b3ed08832055bb736d81516013e405f161d9ccde9a90cfcdde83 android.hardware.neuralnetworks@1.3::IPreparedModel

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

cf1d55e8c68300090747ab90b94c22e4c859b29c84ced68a317c595bb115eab2 android.hardware.neuralnetworks@1.3::types

3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi

neuralnetworks/1.3/IPreparedModel.hal

+61 −3
Original line number Diff line number Diff line
@@ -18,9 +18,11 @@ package android.hardware.neuralnetworks@1.3; 


import @1.0::ErrorStatus;

import @1.0::Request;

import @1.2::MeasureTiming;

import @1.2::IExecutionCallback;

import @1.2::IPreparedModel;

import @1.2::MeasureTiming;

import @1.2::OutputShape;

import @1.2::Timing;



/**

 * IPreparedModel describes a model that has been prepared for execution and
@@ -62,8 +64,8 @@ interface IPreparedModel extends @1.2::IPreparedModel { 
     *   values, the execution should complete successfully (ErrorStatus::NONE):

     *   There must be no failure unless the device itself is in a bad state.

     *

     * Any number of calls to the execute, execute_1_2, execute_1_3, and executeSynchronously

     * functions, in any combination, may be made concurrently, even on the same

     * Any number of calls to the execute* and executeSynchronously* functions,

     * in any combination, may be made concurrently, even on the same

     * IPreparedModel object.

     *

     * @param request The input and output information on which the prepared
@@ -87,4 +89,60 @@ interface IPreparedModel extends @1.2::IPreparedModel { 
     */

    execute_1_3(Request request, MeasureTiming measure, IExecutionCallback callback)

        generates (ErrorStatus status);



    /**

     * Performs a synchronous execution on a prepared model.

     *

     * The execution is performed synchronously with respect to the caller.

     * executeSynchronously_1_3 must verify the inputs to the function are

     * correct. If there is an error, executeSynchronously_1_3 must immediately

     * return with the appropriate ErrorStatus value. If the inputs to the

     * function are valid and there is no error, executeSynchronously_1_3 must

     * perform the execution, and must not return until the execution is

     * complete.

     *

     * The caller must not change the content of any data object referenced by

     * 'request' (described by the {@link @1.0::DataLocation} of a

     * {@link @1.0::RequestArgument}) until executeSynchronously_1_3

     * returns. executeSynchronously_1_3 must not change the content of any of the

     * data objects corresponding to 'request' inputs.

     *

     * If the prepared model was prepared from a model wherein all tensor

     * operands have fully specified dimensions, and the inputs to the function

     * are valid, and at execution time every operation's input operands have

     * legal values, then the execution should complete successfully

     * (ErrorStatus::NONE): There must be no failure unless the device itself is

     * in a bad state.

     *

     * Any number of calls to the execute* and executeSynchronously* functions,

     * in any combination, may be made concurrently, even on the same

     * IPreparedModel object.

     *

     * @param request The input and output information on which the prepared

     *                model is to be executed.

     * @param measure Specifies whether or not to measure duration of the execution.

     *                The duration runs from the time the driver sees the call

     *                to the executeSynchronously_1_3 function to the time the driver

     *                returns from the function.

     * @return status Error status of the execution, must be:

     *                - NONE if execution is performed successfully

     *                - DEVICE_UNAVAILABLE if driver is offline or busy

     *                - GENERAL_FAILURE if there is an unspecified error

     *                - OUTPUT_INSUFFICIENT_SIZE if at least one output

     *                  operand buffer is not large enough to store the

     *                  corresponding output

     *                - INVALID_ARGUMENT if one of the input arguments is

     *                  invalid

     * @return outputShapes A list of shape information of model output operands.

     *                      The index into "outputShapes" corresponds to the index

     *                      of the output operand in the Request outputs vector.

     *                      outputShapes must be empty unless the status is either

     *                      NONE or OUTPUT_INSUFFICIENT_SIZE.

     * @return Timing Duration of execution. Unless measure is YES and status is

     *                NONE, all times must be reported as UINT64_MAX. A driver may

     *                choose to report any time as UINT64_MAX, indicating that

     *                measurement is not available.

     */

    executeSynchronously_1_3(Request request, MeasureTiming measure)

            generates (ErrorStatus status, vec<OutputShape> outputShapes, Timing timing);

};

neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp

+1 −1
Original line number Diff line number Diff line
@@ -215,7 +215,7 @@ static Return<ErrorStatus> ExecutePreparedModel(const sp<IPreparedModel>& prepar 
                                                hidl_vec<OutputShape>* outputShapes,

                                                Timing* timing) {

    ErrorStatus result;

    Return<void> ret = preparedModel->executeSynchronously(

    Return<void> ret = preparedModel->executeSynchronously_1_3(

            request, measure,

            [&result, outputShapes, timing](ErrorStatus error, const hidl_vec<OutputShape>& shapes,

                                            const Timing& time) {

neuralnetworks/1.3/vts/functional/ValidateRequest.cpp

+4 −4
Original line number Diff line number Diff line
@@ -79,9 +79,9 @@ static void validate(const sp<IPreparedModel>& preparedModel, const std::string& 


    // synchronous

    {

        SCOPED_TRACE(message + " [executeSynchronously]");

        SCOPED_TRACE(message + " [executeSynchronously_1_3]");



        Return<void> executeStatus = preparedModel->executeSynchronously(

        Return<void> executeStatus = preparedModel->executeSynchronously_1_3(

                request, measure,

                [](ErrorStatus error, const hidl_vec<OutputShape>& outputShapes,

                   const Timing& timing) {
@@ -158,8 +158,8 @@ void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& req 
}



void validateRequestFailure(const sp<IPreparedModel>& preparedModel, const Request& request) {

    SCOPED_TRACE("Expecting request to fail [executeSynchronously]");

    Return<void> executeStatus = preparedModel->executeSynchronously(

    SCOPED_TRACE("Expecting request to fail [executeSynchronously_1_3]");

    Return<void> executeStatus = preparedModel->executeSynchronously_1_3(

            request, MeasureTiming::NO,

            [](ErrorStatus error, const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {

                ASSERT_NE(ErrorStatus::NONE, error);