2018-10-31 16:43:12 +01:00
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/*
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* Copyright (C) 2018 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* 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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package android.hardware.neuralnetworks@1.2;
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import @1.0::ErrorStatus;
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import @1.0::IPreparedModel;
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import @1.0::Request;
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2019-01-15 19:52:41 +01:00
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import IBurstCallback;
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import IBurstContext;
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2018-10-31 16:43:12 +01:00
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import IExecutionCallback;
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/**
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* IPreparedModel describes a model that has been prepared for execution and
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* is used to launch executions.
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*/
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interface IPreparedModel extends @1.0::IPreparedModel {
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/**
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* Launches an asynchronous execution on a prepared model.
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*
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* The execution is performed asynchronously with respect to the caller.
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* execute_1_2 must verify the inputs to the function are correct. If there is
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* an error, execute_1_2 must immediately invoke the callback with the
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* appropriate ErrorStatus value, then return with the same ErrorStatus. If
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* the inputs to the function are valid and there is no error, execute_1_2 must
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* launch an asynchronous task to perform the execution in the background,
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* and immediately return with ErrorStatus::NONE. If the asynchronous task
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* fails to launch, execute_1_2 must immediately invoke the callback with
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* ErrorStatus::GENERAL_FAILURE, then return with
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* ErrorStatus::GENERAL_FAILURE.
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*
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* When the asynchronous task has finished its execution, it must
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* immediately invoke the callback object provided as an input to the
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* execute_1_2 function. This callback must be provided with the ErrorStatus of
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* the execution.
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*
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* If the prepared model was prepared from a model wherein all
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* tensor operands have fully specified dimensions, and the inputs
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* to the function are valid, then the execution should launch
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* and complete successfully (ErrorStatus::NONE). There must be
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* no failure unless the device itself is in a bad state.
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*
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2018-12-21 20:20:26 +01:00
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* Any number of calls to the execute, execute_1_2, and executeSynchronously
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* functions, in any combination, may be made concurrently, even on the same
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* IPreparedModel object.
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2018-10-31 16:43:12 +01:00
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*
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* @param request The input and output information on which the prepared
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* model is to be executed.
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2019-01-23 23:01:52 +01:00
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* @param measure Specifies whether or not to measure duration of the execution.
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* The duration runs from the time the driver sees the call
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* to the execute_1_2 function to the time the driver invokes
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* the callback.
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2018-10-31 16:43:12 +01:00
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* @param callback A callback object used to return the error status of
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* the execution. The callback object's notify function must
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* be called exactly once, even if the execution was
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* unsuccessful.
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* @return status Error status of the call, must be:
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* - NONE if task is successfully launched
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* - DEVICE_UNAVAILABLE if driver is offline or busy
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* - GENERAL_FAILURE if there is an unspecified error
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* - OUTPUT_INSUFFICIENT_SIZE if provided output buffer is
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* not large enough to store the resultant values
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* - INVALID_ARGUMENT if one of the input arguments is
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* invalid
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*/
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2019-01-23 23:01:52 +01:00
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execute_1_2(Request request, MeasureTiming measure, IExecutionCallback callback)
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2018-10-31 16:43:12 +01:00
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generates (ErrorStatus status);
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2018-12-21 20:20:26 +01:00
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/**
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* Performs a synchronous execution on a prepared model.
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*
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* The execution is performed synchronously with respect to the caller.
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* executeSynchronously must verify the inputs to the function are
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* correct. If there is an error, executeSynchronously must immediately
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* return with the appropriate ErrorStatus value. If the inputs to the
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* function are valid and there is no error, executeSynchronously must
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* perform the execution, and must not return until the execution is
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* complete.
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*
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* If the prepared model was prepared from a model wherein all tensor
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* operands have fully specified dimensions, and the inputs to the function
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* are valid, then the execution should complete successfully
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* (ErrorStatus::NONE). There must be no failure unless the device itself is
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* in a bad state.
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*
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* Any number of calls to the execute, execute_1_2, and executeSynchronously
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* functions, in any combination, may be made concurrently, even on the same
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* IPreparedModel object.
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*
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* @param request The input and output information on which the prepared
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* model is to be executed.
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2019-01-23 23:01:52 +01:00
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* @param measure Specifies whether or not to measure duration of the execution.
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* The duration runs from the time the driver sees the call
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* to the executeSynchronously function to the time the driver
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* returns from the function.
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2018-12-21 20:20:26 +01:00
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* @return status Error status of the execution, must be:
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* - NONE if execution is performed successfully
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* - DEVICE_UNAVAILABLE if driver is offline or busy
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* - GENERAL_FAILURE if there is an unspecified error
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2019-01-15 19:52:41 +01:00
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* - OUTPUT_INSUFFICIENT_SIZE if at least one output
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* operand buffer is not large enough to store the
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* corresponding output
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2018-12-21 20:20:26 +01:00
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* - INVALID_ARGUMENT if one of the input arguments is
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* invalid
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2019-01-15 19:52:41 +01:00
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* @return outputShapes A list of shape information of model output operands.
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* The index into "outputShapes" corresponds to the index
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* of the output operand in the Request outputs vector.
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* outputShapes must be empty unless the status is either
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* NONE or OUTPUT_INSUFFICIENT_SIZE.
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2019-01-23 23:01:52 +01:00
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* @return Timing Duration of execution. Unless measure is YES and status is
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* NONE, all times must be reported as UINT64_MAX. A driver may
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* choose to report any time as UINT64_MAX, indicating that
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* measurement is not available.
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2018-12-21 20:20:26 +01:00
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*/
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2019-01-23 23:01:52 +01:00
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executeSynchronously(Request request, MeasureTiming measure)
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generates (ErrorStatus status, vec<OutputShape> outputShapes, Timing timing);
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2019-01-15 19:52:41 +01:00
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/**
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* Configure a Burst object used to execute multiple inferences on a
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* prepared model in rapid succession.
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*
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* @param callback A callback object used to retrieve memory resources
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* corresponding to a unique identifiers ("slots").
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* @param requestChannel Used by the client to send a serialized Request to
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* the Burst for execution. requestChannel must not be
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* used to pass a second Request object until a result
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* has been received from resultChannel.
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* @param resultChannel Used by the service to return the results of an
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* execution to the client: the status of the execution
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* and OutputShape of all output tensors. resultChannel
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* must be used to return the results if a Request was
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* sent through the requestChannel.
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* @return status Error status of configuring the execution burst, must be:
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* - NONE if the burst is successfully configured
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* - DEVICE_UNAVAILABLE if driver is offline or busy
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* - GENERAL_FAILURE if there is an unspecified error
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* - INVALID_ARGUMENT if one of the input arguments is
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* invalid
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* @return context Object containing all resources (such as cached
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* hidl_memory) related to a Burst if successful, otherwise
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* nullptr.
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*/
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configureExecutionBurst(IBurstCallback callback,
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fmq_sync<FmqRequestDatum> requestChannel,
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fmq_sync<FmqResultDatum> resultChannel)
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generates (ErrorStatus status, IBurstContext context);
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2018-10-31 16:43:12 +01:00
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};
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