Loading neuralnetworks/1.2/Android.bp 0 → 100644 +24 −0 Original line number Diff line number Diff line // This file is autogenerated by hidl-gen -Landroidbp. hidl_interface { name: "android.hardware.neuralnetworks@1.2", root: "android.hardware", vndk: { enabled: true, }, srcs: [ "types.hal", "IDevice.hal", ], interfaces: [ "android.hardware.neuralnetworks@1.0", "android.hardware.neuralnetworks@1.1", "android.hidl.base@1.0", ], types: [ "Model", "Operation", "OperationType", ], gen_java: false, } neuralnetworks/1.2/IDevice.hal 0 → 100644 +106 −0 Original line number Diff line number Diff line /* * 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 { /** * 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); }; neuralnetworks/1.2/types.hal 0 → 100644 +112 −0 Original line number Diff line number Diff line /* * 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::Operand; import @1.0::PerformanceInfo; import @1.1::OperationType; /** * Operation types. * * The type of an operation in a model. */ enum OperationType : @1.1::OperationType { }; /** * Describes one operation of the model's graph. */ struct Operation { /** * The operation type. */ OperationType type; /** * Describes the table that contains the indexes of the inputs of the * operation. The offset is the index in the operandIndexes table. */ vec<uint32_t> inputs; /** * Describes the table that contains the indexes of the outputs of the * operation. The offset is the index in the operandIndexes table. */ vec<uint32_t> outputs; }; /** * A Neural Network Model. * * This includes not only the execution graph, but also constant data such as * weights or scalars added at construction time. The only information that * may not be known is the shape of the input tensors. */ struct Model { /** * All operands included in the model. */ vec<Operand> operands; /** * All operations included in the model. * * The operations are sorted into execution order. Every operand * with lifetime MODEL_OUTPUT or TEMPORARY_VARIABLE must be * written before it is read. */ vec<Operation> operations; /** * Input indexes of the model. There must be at least one. * * Each value corresponds to the index of the operand in "operands". */ vec<uint32_t> inputIndexes; /** * Output indexes of the model. There must be at least one. * * Each value corresponds to the index of the operand in "operands". */ vec<uint32_t> outputIndexes; /** * A byte buffer containing operand data that were copied into the model. * * An operand's value must be located here if and only if Operand::lifetime * equals OperandLifeTime::CONSTANT_COPY. */ vec<uint8_t> operandValues; /** * A collection of shared memory pools containing operand values. * * An operand's value must be located here if and only if Operand::lifetime * equals OperandLifeTime::CONSTANT_REFERENCE. */ vec<memory> pools; /** * 'true' indicates TENSOR_FLOAT32 may be calculated with range and/or * precision as low as that of the IEEE 754 16-bit floating-point format. * 'false' indicates TENSOR_FLOAT32 must be calculated using at least the * range and precision of the IEEE 754 32-bit floating-point format. */ bool relaxComputationFloat32toFloat16; }; Loading
neuralnetworks/1.2/Android.bp 0 → 100644 +24 −0 Original line number Diff line number Diff line // This file is autogenerated by hidl-gen -Landroidbp. hidl_interface { name: "android.hardware.neuralnetworks@1.2", root: "android.hardware", vndk: { enabled: true, }, srcs: [ "types.hal", "IDevice.hal", ], interfaces: [ "android.hardware.neuralnetworks@1.0", "android.hardware.neuralnetworks@1.1", "android.hidl.base@1.0", ], types: [ "Model", "Operation", "OperationType", ], gen_java: false, }
neuralnetworks/1.2/IDevice.hal 0 → 100644 +106 −0 Original line number Diff line number Diff line /* * 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 { /** * 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); };
neuralnetworks/1.2/types.hal 0 → 100644 +112 −0 Original line number Diff line number Diff line /* * 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::Operand; import @1.0::PerformanceInfo; import @1.1::OperationType; /** * Operation types. * * The type of an operation in a model. */ enum OperationType : @1.1::OperationType { }; /** * Describes one operation of the model's graph. */ struct Operation { /** * The operation type. */ OperationType type; /** * Describes the table that contains the indexes of the inputs of the * operation. The offset is the index in the operandIndexes table. */ vec<uint32_t> inputs; /** * Describes the table that contains the indexes of the outputs of the * operation. The offset is the index in the operandIndexes table. */ vec<uint32_t> outputs; }; /** * A Neural Network Model. * * This includes not only the execution graph, but also constant data such as * weights or scalars added at construction time. The only information that * may not be known is the shape of the input tensors. */ struct Model { /** * All operands included in the model. */ vec<Operand> operands; /** * All operations included in the model. * * The operations are sorted into execution order. Every operand * with lifetime MODEL_OUTPUT or TEMPORARY_VARIABLE must be * written before it is read. */ vec<Operation> operations; /** * Input indexes of the model. There must be at least one. * * Each value corresponds to the index of the operand in "operands". */ vec<uint32_t> inputIndexes; /** * Output indexes of the model. There must be at least one. * * Each value corresponds to the index of the operand in "operands". */ vec<uint32_t> outputIndexes; /** * A byte buffer containing operand data that were copied into the model. * * An operand's value must be located here if and only if Operand::lifetime * equals OperandLifeTime::CONSTANT_COPY. */ vec<uint8_t> operandValues; /** * A collection of shared memory pools containing operand values. * * An operand's value must be located here if and only if Operand::lifetime * equals OperandLifeTime::CONSTANT_REFERENCE. */ vec<memory> pools; /** * 'true' indicates TENSOR_FLOAT32 may be calculated with range and/or * precision as low as that of the IEEE 754 16-bit floating-point format. * 'false' indicates TENSOR_FLOAT32 must be calculated using at least the * range and precision of the IEEE 754 32-bit floating-point format. */ bool relaxComputationFloat32toFloat16; };
