Loading current.txt +2 −2 Original line number Diff line number Diff line Loading @@ -338,8 +338,8 @@ e15ebdf1e0a326ff5b8a59668d4d8cd3852bd88388eae91de13f5f7e1af50ed1 android.hardwar b8c7ed58aa8740361e63d0ce9e7c94227572a629f356958840b34809d2393a7c android.hardware.media.bufferpool@1.0::IClientManager 4a2c0dc82780e6c90731725a103feab8ab6ecf85a64e049b9cbd2b2c61620fe1 android.hardware.media.bufferpool@1.0::IConnection 6aef1218e5949f867b0104752ac536c1b707222a403341720de90141df129e3e android.hardware.media.bufferpool@1.0::types 3e4d8e0085ebe8549efb8ad4b8b400a141a3fa3f47ae23696b3e05a1612eb003 android.hardware.neuralnetworks@1.1::IDevice 50db076b03a6760557fc60ef433ba9dd2ff983cf3305eeb504b0fff3eaa604ff android.hardware.neuralnetworks@1.1::types 7698dc2382a2eeb43541840e3ee624f34108efdfb976b2bfa7c13ef15fb8c4c4 android.hardware.neuralnetworks@1.1::IDevice 5604001029a255648a9e955de0a822a48d9ba7cc259b106fb8be0cd43dc8eece android.hardware.neuralnetworks@1.1::types 8d3d86da0bfa4bf070970d8303c659f67f35d670c287d45a3f542e4fedadd578 android.hardware.nfc@1.1::INfc e85f566698d2a2c28100e264fcf2c691a066756ddf8dd341d009ff50cfe10614 android.hardware.nfc@1.1::INfcClientCallback 5e278fcaa3287d397d8eebe1c22aaa28150f5caae1cf9381cd6dc32cb37899c5 android.hardware.nfc@1.1::types Loading neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp +2 −2 Original line number Diff line number Diff line Loading @@ -242,8 +242,8 @@ void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> c // launch prepare model sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback(); ASSERT_NE(nullptr, preparedModelCallback.get()); Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(model, preparedModelCallback); Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1( model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback); ASSERT_TRUE(prepareLaunchStatus.isOk()); ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus)); Loading neuralnetworks/1.1/IDevice.hal +4 −1 Original line number Diff line number Diff line Loading @@ -102,6 +102,8 @@ interface IDevice extends @1.0::IDevice { * Multiple threads can 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 Loading @@ -115,6 +117,7 @@ interface IDevice extends @1.0::IDevice { * - INVALID_ARGUMENT if one of the input arguments is * invalid */ prepareModel_1_1(Model model, IPreparedModelCallback callback) prepareModel_1_1(Model model, ExecutionPreference preference, IPreparedModelCallback callback) generates (ErrorStatus status); }; neuralnetworks/1.1/types.hal +21 −0 Original line number Diff line number Diff line Loading @@ -382,3 +382,24 @@ struct Model { */ bool relaxComputationFloat32toFloat16; }; /** * Execution preferences. */ enum ExecutionPreference : int32_t { /** * Prefer executing in a way that minimizes battery drain. * This is desirable for compilations that will be executed often. */ LOW_POWER = 0, /** * Prefer returning a single answer as fast as possible, even if this causes * more power consumption. */ FAST_SINGLE_ANSWER = 1, /** * Prefer maximizing the throughput of successive frames, for example when * processing successive frames coming from the camera. */ SUSTAINED_SPEED = 2, }; neuralnetworks/1.1/vts/functional/ValidateModel.cpp +31 −5 Original line number Diff line number Diff line Loading @@ -50,13 +50,13 @@ static void validateGetSupportedOperations(const sp<IDevice>& device, const std: } static void validatePrepareModel(const sp<IDevice>& device, const std::string& message, const V1_1::Model& model) { const V1_1::Model& model, ExecutionPreference preference) { SCOPED_TRACE(message + " [prepareModel_1_1]"); sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback(); ASSERT_NE(nullptr, preparedModelCallback.get()); Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(model, preparedModelCallback); device->prepareModel_1_1(model, preference, preparedModelCallback); ASSERT_TRUE(prepareLaunchStatus.isOk()); ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus)); Loading @@ -67,15 +67,24 @@ static void validatePrepareModel(const sp<IDevice>& device, const std::string& m ASSERT_EQ(nullptr, preparedModel.get()); } static bool validExecutionPreference(ExecutionPreference preference) { return preference == ExecutionPreference::LOW_POWER || preference == ExecutionPreference::FAST_SINGLE_ANSWER || preference == ExecutionPreference::SUSTAINED_SPEED; } // Primary validation function. This function will take a valid model, apply a // mutation to it to invalidate the model, then pass it to interface calls that // use the model. Note that the model here is passed by value, and any mutation // to the model does not leave this function. static void validate(const sp<IDevice>& device, const std::string& message, V1_1::Model model, const std::function<void(Model*)>& mutation) { const std::function<void(Model*)>& mutation, ExecutionPreference preference = ExecutionPreference::FAST_SINGLE_ANSWER) { mutation(&model); if (validExecutionPreference(preference)) { validateGetSupportedOperations(device, message, model); validatePrepareModel(device, message, model); } validatePrepareModel(device, message, model, preference); } // Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation, Loading Loading @@ -486,6 +495,22 @@ static void addOperationOutputTest(const sp<IDevice>& device, const V1_1::Model& } } ///////////////////////// VALIDATE EXECUTION PREFERENCE ///////////////////////// static const int32_t invalidExecutionPreferences[] = { static_cast<int32_t>(ExecutionPreference::LOW_POWER) - 1, // lower bound static_cast<int32_t>(ExecutionPreference::SUSTAINED_SPEED) + 1, // upper bound }; static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const V1_1::Model& model) { for (int32_t preference : invalidExecutionPreferences) { const std::string message = "mutateExecutionPreferenceTest: preference " + std::to_string(preference); validate(device, message, model, [](Model*) {}, static_cast<ExecutionPreference>(preference)); } } ////////////////////////// ENTRY POINT ////////////////////////////// void ValidationTest::validateModel(const V1_1::Model& model) { Loading @@ -503,6 +528,7 @@ void ValidationTest::validateModel(const V1_1::Model& model) { removeOperationOutputTest(device, model); addOperationInputTest(device, model); addOperationOutputTest(device, model); mutateExecutionPreferenceTest(device, model); } } // namespace functional Loading Loading
current.txt +2 −2 Original line number Diff line number Diff line Loading @@ -338,8 +338,8 @@ e15ebdf1e0a326ff5b8a59668d4d8cd3852bd88388eae91de13f5f7e1af50ed1 android.hardwar b8c7ed58aa8740361e63d0ce9e7c94227572a629f356958840b34809d2393a7c android.hardware.media.bufferpool@1.0::IClientManager 4a2c0dc82780e6c90731725a103feab8ab6ecf85a64e049b9cbd2b2c61620fe1 android.hardware.media.bufferpool@1.0::IConnection 6aef1218e5949f867b0104752ac536c1b707222a403341720de90141df129e3e android.hardware.media.bufferpool@1.0::types 3e4d8e0085ebe8549efb8ad4b8b400a141a3fa3f47ae23696b3e05a1612eb003 android.hardware.neuralnetworks@1.1::IDevice 50db076b03a6760557fc60ef433ba9dd2ff983cf3305eeb504b0fff3eaa604ff android.hardware.neuralnetworks@1.1::types 7698dc2382a2eeb43541840e3ee624f34108efdfb976b2bfa7c13ef15fb8c4c4 android.hardware.neuralnetworks@1.1::IDevice 5604001029a255648a9e955de0a822a48d9ba7cc259b106fb8be0cd43dc8eece android.hardware.neuralnetworks@1.1::types 8d3d86da0bfa4bf070970d8303c659f67f35d670c287d45a3f542e4fedadd578 android.hardware.nfc@1.1::INfc e85f566698d2a2c28100e264fcf2c691a066756ddf8dd341d009ff50cfe10614 android.hardware.nfc@1.1::INfcClientCallback 5e278fcaa3287d397d8eebe1c22aaa28150f5caae1cf9381cd6dc32cb37899c5 android.hardware.nfc@1.1::types Loading
neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp +2 −2 Original line number Diff line number Diff line Loading @@ -242,8 +242,8 @@ void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> c // launch prepare model sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback(); ASSERT_NE(nullptr, preparedModelCallback.get()); Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(model, preparedModelCallback); Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1( model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback); ASSERT_TRUE(prepareLaunchStatus.isOk()); ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus)); Loading
neuralnetworks/1.1/IDevice.hal +4 −1 Original line number Diff line number Diff line Loading @@ -102,6 +102,8 @@ interface IDevice extends @1.0::IDevice { * Multiple threads can 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 Loading @@ -115,6 +117,7 @@ interface IDevice extends @1.0::IDevice { * - INVALID_ARGUMENT if one of the input arguments is * invalid */ prepareModel_1_1(Model model, IPreparedModelCallback callback) prepareModel_1_1(Model model, ExecutionPreference preference, IPreparedModelCallback callback) generates (ErrorStatus status); };
neuralnetworks/1.1/types.hal +21 −0 Original line number Diff line number Diff line Loading @@ -382,3 +382,24 @@ struct Model { */ bool relaxComputationFloat32toFloat16; }; /** * Execution preferences. */ enum ExecutionPreference : int32_t { /** * Prefer executing in a way that minimizes battery drain. * This is desirable for compilations that will be executed often. */ LOW_POWER = 0, /** * Prefer returning a single answer as fast as possible, even if this causes * more power consumption. */ FAST_SINGLE_ANSWER = 1, /** * Prefer maximizing the throughput of successive frames, for example when * processing successive frames coming from the camera. */ SUSTAINED_SPEED = 2, };
neuralnetworks/1.1/vts/functional/ValidateModel.cpp +31 −5 Original line number Diff line number Diff line Loading @@ -50,13 +50,13 @@ static void validateGetSupportedOperations(const sp<IDevice>& device, const std: } static void validatePrepareModel(const sp<IDevice>& device, const std::string& message, const V1_1::Model& model) { const V1_1::Model& model, ExecutionPreference preference) { SCOPED_TRACE(message + " [prepareModel_1_1]"); sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback(); ASSERT_NE(nullptr, preparedModelCallback.get()); Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(model, preparedModelCallback); device->prepareModel_1_1(model, preference, preparedModelCallback); ASSERT_TRUE(prepareLaunchStatus.isOk()); ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus)); Loading @@ -67,15 +67,24 @@ static void validatePrepareModel(const sp<IDevice>& device, const std::string& m ASSERT_EQ(nullptr, preparedModel.get()); } static bool validExecutionPreference(ExecutionPreference preference) { return preference == ExecutionPreference::LOW_POWER || preference == ExecutionPreference::FAST_SINGLE_ANSWER || preference == ExecutionPreference::SUSTAINED_SPEED; } // Primary validation function. This function will take a valid model, apply a // mutation to it to invalidate the model, then pass it to interface calls that // use the model. Note that the model here is passed by value, and any mutation // to the model does not leave this function. static void validate(const sp<IDevice>& device, const std::string& message, V1_1::Model model, const std::function<void(Model*)>& mutation) { const std::function<void(Model*)>& mutation, ExecutionPreference preference = ExecutionPreference::FAST_SINGLE_ANSWER) { mutation(&model); if (validExecutionPreference(preference)) { validateGetSupportedOperations(device, message, model); validatePrepareModel(device, message, model); } validatePrepareModel(device, message, model, preference); } // Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation, Loading Loading @@ -486,6 +495,22 @@ static void addOperationOutputTest(const sp<IDevice>& device, const V1_1::Model& } } ///////////////////////// VALIDATE EXECUTION PREFERENCE ///////////////////////// static const int32_t invalidExecutionPreferences[] = { static_cast<int32_t>(ExecutionPreference::LOW_POWER) - 1, // lower bound static_cast<int32_t>(ExecutionPreference::SUSTAINED_SPEED) + 1, // upper bound }; static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const V1_1::Model& model) { for (int32_t preference : invalidExecutionPreferences) { const std::string message = "mutateExecutionPreferenceTest: preference " + std::to_string(preference); validate(device, message, model, [](Model*) {}, static_cast<ExecutionPreference>(preference)); } } ////////////////////////// ENTRY POINT ////////////////////////////// void ValidationTest::validateModel(const V1_1::Model& model) { Loading @@ -503,6 +528,7 @@ void ValidationTest::validateModel(const V1_1::Model& model) { removeOperationOutputTest(device, model); addOperationInputTest(device, model); addOperationOutputTest(device, model); mutateExecutionPreferenceTest(device, model); } } // namespace functional Loading