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https://github.com/Evolution-X/hardware_interfaces
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48544cc38a
Under certain circumstances, we guarantee that a prepared model can be executed successfully. In describing those circumstances, we neglected to specify that operation input operands must have legal values for the guarantee to hold. For example, the guarantee doesn't hold if an ADD operation has an activation input that is not one of the defined values; or if a RESHAPE operation has a shape input in which two or more components are -1. This change modifies the guarantee to apply only when operation input operands have legal values. It also documents this guarantee for burst execution. Note that if an operation has an input operand that can be proven to have an illegal value at preparation time (e.g., a constant value that is illegal), model preparation might (but is not required to) fail for that reason. Bug: 135933040 Test: $ cd neuralnetworks ; mma Change-Id: I8b421550dd89e4bbbdae899e7cb5e9e88a46d2fb
191 lines
10 KiB
Plaintext
191 lines
10 KiB
Plaintext
/*
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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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import IBurstCallback;
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import IBurstContext;
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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 launch is successful, the caller must not change the content of
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* any data object referenced by 'request' (described by the
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* {@link @1.0::DataLocation} of a {@link @1.0::RequestArgument}) until the
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* asynchronous task has invoked the callback object. The asynchronous task
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* must not change the content of any of the data objects corresponding to
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* 'request' inputs.
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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:
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* - the execution should launch successfully (ErrorStatus::NONE): There
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* must be no failure unless the device itself is in a bad state.
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* - if at execution time every operation's input operands have legal
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* values, the execution should complete successfully (ErrorStatus::NONE):
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* There must be no failure unless the device itself is 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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* @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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* @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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execute_1_2(Request request, MeasureTiming measure, IExecutionCallback callback)
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generates (ErrorStatus status);
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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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* The caller must not change the content of any data object referenced by
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* 'request' (described by the {@link @1.0::DataLocation} of a
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* {@link @1.0::RequestArgument}) until executeSynchronously
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* returns. executeSynchronously must not change the content of any of the
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* data objects corresponding to 'request' inputs.
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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, and at execution time every operation's input operands have
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* legal values, 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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* @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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* @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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* - 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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* - INVALID_ARGUMENT if one of the input arguments is
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* invalid
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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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* @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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*/
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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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/**
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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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* If the prepared model was prepared from a model wherein all tensor
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* operands have fully specified dimensions, and a valid serialized Request
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* is sent to the Burst for execution, and at execution time every
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* operation's input operands have legal values, then the execution should
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* complete successfully (ErrorStatus::NONE): There must be no failure
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* unless the device itself is in a bad state.
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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. The client must not change
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* the content of any data object referenced by the
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* Request (described by the {@link @1.0::DataLocation}
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* of an {@link OperandInformation}) until a result
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* has been received from resultChannel. Execution
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* must not change the content of any of the data
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* objects corresponding to Request inputs. requestChannel
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* must not be used to pass a second Request object
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* until a result 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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};
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