platform_hardware_interfaces/neuralnetworks/1.2/IDevice.hal

/*
 * Copyright (C) 2018 The Android Open Source Project
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package android.hardware.neuralnetworks@1.2;

import @1.0::ErrorStatus;
import @1.0::IPreparedModelCallback;
import @1.1::ExecutionPreference;
import @1.1::IDevice;

/**
 * This interface represents a device driver.
 */
interface IDevice extends @1.1::IDevice {
    /**
     * Get the version string of the driver implementation.
     *
     * The version string must be a unique token among the set of version strings of
     * drivers of a specific device. The token identifies the device driver's
     * implementation. The token must not be confused with the feature level which is solely
     * defined by the interface version. This API is opaque to the Android framework, but the
     * Android framework may use the information for debugging or to pass on to NNAPI applications.
     *
     * Application developers sometimes have specific requirements to ensure good user experiences,
     * and they need more information to make intelligent decisions when the Android framework cannot.
     * For example, combined with the device name and other information, the token can help
     * NNAPI applications filter devices based on their needs:
     *     - An application demands a certain level of performance, but a specific version of
     *       the driver cannot meet that requirement because of a performance regression.
     *       The application can blacklist the driver based on the version provided.
     *     - An application has a minimum precision requirement, but certain versions of
     *       the driver cannot meet that requirement because of bugs or certain optimizations.
     *       The application can filter out versions of these drivers.
     *
     * @return status Error status returned from querying the version string. Must be:
     *     - NONE if the query was successful
     *     - DEVICE_UNAVAILABLE if driver is offline or busy
     *     - GENERAL_FAILURE if the query resulted in an
     *       unspecified error
     * @return version The version string of the device implementation.
     *     Must have nonzero length
     */
    getVersionString() generates (ErrorStatus status, string version);

    /**
     * Gets the supported operations in a model.
     *
     * getSupportedOperations indicates which operations of a model are fully
     * supported by the vendor driver. If an operation may not be supported for
     * any reason, getSupportedOperations must return false for that operation.
     *
     * @param model A model whose operations--and their corresponding operands--
     *     are to be verified by the driver.
     * @return status Error status of the call, must be:
     *     - NONE if successful
     *     - DEVICE_UNAVAILABLE if driver is offline or busy
     *     - GENERAL_FAILURE if there is an unspecified error
     *     - INVALID_ARGUMENT if provided model is invalid
     * @return supportedOperations A list of supported operations, where true
     *     indicates the operation is supported and false indicates the
     *     operation is not supported. The index of "supported" corresponds with
     *     the index of the operation it is describing.
     */
    getSupportedOperations_1_2(Model model)
            generates (ErrorStatus status, vec<bool> supportedOperations);

    /**
     * Creates a prepared model for execution.
     *
     * prepareModel is used to make any necessary transformations or alternative
     * representations to a model for execution, possibly including
     * transformations on the constant data, optimization on the model's graph,
     * or compilation into the device's native binary format. The model itself
     * is not changed.
     *
     * The model is prepared asynchronously with respect to the caller. The
     * prepareModel function must verify the inputs to the prepareModel function
     * are correct. If there is an error, prepareModel must immediately invoke
     * the callback with the appropriate ErrorStatus value and nullptr for the
     * IPreparedModel, then return with the same ErrorStatus. If the inputs to
     * the prepareModel function are valid and there is no error, prepareModel
     * must launch an asynchronous task to prepare the model in the background,
     * and immediately return from prepareModel with ErrorStatus::NONE. If the
     * asynchronous task fails to launch, prepareModel must immediately invoke
     * the callback with ErrorStatus::GENERAL_FAILURE and nullptr for the
     * IPreparedModel, then return with ErrorStatus::GENERAL_FAILURE.
     *
     * When the asynchronous task has finished preparing the model, it must
     * immediately invoke the callback function provided as an input to
     * prepareModel. If the model was prepared successfully, the callback object
     * must be invoked with an error status of ErrorStatus::NONE and the
     * produced IPreparedModel object. If an error occurred preparing the model,
     * the callback object must be invoked with the appropriate ErrorStatus
     * value and nullptr for the IPreparedModel.
     *
     * The only information that may be unknown to the model at this stage is
     * the shape of the tensors, which may only be known at execution time. As
     * such, some driver services may return partially prepared models, where
     * the prepared model may only be finished when it is paired with a set of
     * inputs to the model. Note that the same prepared model object may be
     * used with different shapes of inputs on different (possibly concurrent)
     * executions.
     *
     * Multiple threads may call prepareModel on the same model concurrently.
     *
     * @param model The model to be prepared for execution.
     * @param preference Indicates the intended execution behavior of a prepared
     *     model.
     * @param callback A callback object used to return the error status of
     *     preparing the model for execution and the prepared model if
     *     successful, nullptr otherwise. The callback object's notify function
     *     must be called exactly once, even if the model could not be prepared.
     * @return status Error status of launching a task which prepares the model
     *     in the background; must be:
     *     - NONE if preparation task is successfully launched
     *     - DEVICE_UNAVAILABLE if driver is offline or busy
     *     - GENERAL_FAILURE if there is an unspecified error
     *     - INVALID_ARGUMENT if one of the input arguments is invalid
     */
    prepareModel_1_2(Model model, ExecutionPreference preference,
                     IPreparedModelCallback callback)
          generates (ErrorStatus status);
};