diff --git a/neuralnetworks/1.3/utils/Android.bp b/neuralnetworks/1.3/utils/Android.bp
index 279b250..d5d897d 100644
--- a/neuralnetworks/1.3/utils/Android.bp
+++ b/neuralnetworks/1.3/utils/Android.bp
@@ -20,6 +20,7 @@
     srcs: ["src/*"],
     local_include_dirs: ["include/nnapi/hal/1.3/"],
     export_include_dirs: ["include"],
+    cflags: ["-Wthread-safety"],
     static_libs: [
         "neuralnetworks_types",
         "neuralnetworks_utils_hal_common",
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
new file mode 100644
index 0000000..637179d
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
@@ -0,0 +1,52 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
+
+#include <android/hardware/neuralnetworks/1.3/IBuffer.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <memory>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class Buffer final : public nn::IBuffer {
+    struct PrivateConstructorTag {};
+
+  public:
+    static nn::GeneralResult<std::shared_ptr<const Buffer>> create(
+            sp<V1_3::IBuffer> buffer, nn::Request::MemoryDomainToken token);
+
+    Buffer(PrivateConstructorTag tag, sp<V1_3::IBuffer> buffer,
+           nn::Request::MemoryDomainToken token);
+
+    nn::Request::MemoryDomainToken getToken() const override;
+
+    nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
+    nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+                                     const nn::Dimensions& dimensions) const override;
+
+  private:
+    const sp<V1_3::IBuffer> kBuffer;
+    const nn::Request::MemoryDomainToken kToken;
+};
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h
new file mode 100644
index 0000000..d46b111
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h
@@ -0,0 +1,83 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.2/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Callbacks.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class PreparedModelCallback final : public IPreparedModelCallback,
+                                    public hal::utils::IProtectedCallback {
+  public:
+    using Data = nn::GeneralResult<nn::SharedPreparedModel>;
+
+    Return<void> notify(V1_0::ErrorStatus status,
+                        const sp<V1_0::IPreparedModel>& preparedModel) override;
+    Return<void> notify_1_2(V1_0::ErrorStatus status,
+                            const sp<V1_2::IPreparedModel>& preparedModel) override;
+    Return<void> notify_1_3(ErrorStatus status, const sp<IPreparedModel>& preparedModel) override;
+
+    void notifyAsDeadObject() override;
+
+    Data get();
+
+  private:
+    void notifyInternal(Data result);
+
+    hal::utils::TransferValue<Data> mData;
+};
+
+class ExecutionCallback final : public IExecutionCallback, public hal::utils::IProtectedCallback {
+  public:
+    using Data = nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>;
+
+    Return<void> notify(V1_0::ErrorStatus status) override;
+    Return<void> notify_1_2(V1_0::ErrorStatus status,
+                            const hidl_vec<V1_2::OutputShape>& outputShapes,
+                            const V1_2::Timing& timing) override;
+    Return<void> notify_1_3(ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+                            const V1_2::Timing& timing) override;
+
+    void notifyAsDeadObject() override;
+
+    Data get();
+
+  private:
+    void notifyInternal(Data result);
+
+    hal::utils::TransferValue<Data> mData;
+};
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
index 43987a9..64aa96e 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
@@ -25,54 +25,54 @@
 
 namespace android::nn {
 
-Result<OperandType> convert(const hal::V1_3::OperandType& operandType);
-Result<OperationType> convert(const hal::V1_3::OperationType& operationType);
-Result<Priority> convert(const hal::V1_3::Priority& priority);
-Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities);
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<OperandType> convert(const hal::V1_3::OperandType& operandType);
+GeneralResult<OperationType> convert(const hal::V1_3::OperationType& operationType);
+GeneralResult<Priority> convert(const hal::V1_3::Priority& priority);
+GeneralResult<Capabilities> convert(const hal::V1_3::Capabilities& capabilities);
+GeneralResult<Capabilities::OperandPerformance> convert(
         const hal::V1_3::Capabilities::OperandPerformance& operandPerformance);
-Result<Operation> convert(const hal::V1_3::Operation& operation);
-Result<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime);
-Result<Operand> convert(const hal::V1_3::Operand& operand);
-Result<Model> convert(const hal::V1_3::Model& model);
-Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph);
-Result<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc);
-Result<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole);
-Result<Request> convert(const hal::V1_3::Request& request);
-Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool);
-Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint);
-Result<OptionalTimeoutDuration> convert(
+GeneralResult<Operation> convert(const hal::V1_3::Operation& operation);
+GeneralResult<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime);
+GeneralResult<Operand> convert(const hal::V1_3::Operand& operand);
+GeneralResult<Model> convert(const hal::V1_3::Model& model);
+GeneralResult<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph);
+GeneralResult<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc);
+GeneralResult<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole);
+GeneralResult<Request> convert(const hal::V1_3::Request& request);
+GeneralResult<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool);
+GeneralResult<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint);
+GeneralResult<OptionalTimeoutDuration> convert(
         const hal::V1_3::OptionalTimeoutDuration& optionalTimeoutDuration);
-Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
+GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
 
-Result<std::vector<BufferRole>> convert(
+GeneralResult<std::vector<BufferRole>> convert(
         const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles);
 
 }  // namespace android::nn
 
 namespace android::hardware::neuralnetworks::V1_3::utils {
 
-nn::Result<OperandType> convert(const nn::OperandType& operandType);
-nn::Result<OperationType> convert(const nn::OperationType& operationType);
-nn::Result<Priority> convert(const nn::Priority& priority);
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType);
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType);
+nn::GeneralResult<Priority> convert(const nn::Priority& priority);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
         const nn::Capabilities::OperandPerformance& operandPerformance);
-nn::Result<Operation> convert(const nn::Operation& operation);
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime);
-nn::Result<Operand> convert(const nn::Operand& operand);
-nn::Result<Model> convert(const nn::Model& model);
-nn::Result<Subgraph> convert(const nn::Model::Subgraph& subgraph);
-nn::Result<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
-nn::Result<BufferRole> convert(const nn::BufferRole& bufferRole);
-nn::Result<Request> convert(const nn::Request& request);
-nn::Result<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool);
-nn::Result<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint);
-nn::Result<OptionalTimeoutDuration> convert(
+nn::GeneralResult<Operation> convert(const nn::Operation& operation);
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime);
+nn::GeneralResult<Operand> convert(const nn::Operand& operand);
+nn::GeneralResult<Model> convert(const nn::Model& model);
+nn::GeneralResult<Subgraph> convert(const nn::Model::Subgraph& subgraph);
+nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
+nn::GeneralResult<BufferRole> convert(const nn::BufferRole& bufferRole);
+nn::GeneralResult<Request> convert(const nn::Request& request);
+nn::GeneralResult<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool);
+nn::GeneralResult<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint);
+nn::GeneralResult<OptionalTimeoutDuration> convert(
         const nn::OptionalTimeoutDuration& optionalTimeoutDuration);
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
 
-nn::Result<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
+nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
 
 }  // namespace android::hardware::neuralnetworks::V1_3::utils
 
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h
new file mode 100644
index 0000000..2f6c46a
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h
@@ -0,0 +1,91 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
+
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class Device final : public nn::IDevice {
+    struct PrivateConstructorTag {};
+
+  public:
+    static nn::GeneralResult<std::shared_ptr<const Device>> create(std::string name,
+                                                                   sp<V1_3::IDevice> device);
+
+    Device(PrivateConstructorTag tag, std::string name, std::string versionString,
+           nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+           nn::Capabilities capabilities, std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded,
+           sp<V1_3::IDevice> device, hal::utils::DeathHandler deathHandler);
+
+    const std::string& getName() const override;
+    const std::string& getVersionString() const override;
+    nn::Version getFeatureLevel() const override;
+    nn::DeviceType getType() const override;
+    const std::vector<nn::Extension>& getSupportedExtensions() const override;
+    const nn::Capabilities& getCapabilities() const override;
+    std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+    nn::GeneralResult<void> wait() const override;
+
+    nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+            const nn::Model& model) const override;
+
+    nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+            const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+            nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+            const std::vector<nn::NativeHandle>& dataCache,
+            const nn::CacheToken& token) const override;
+
+    nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+            nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+            const std::vector<nn::NativeHandle>& dataCache,
+            const nn::CacheToken& token) const override;
+
+    nn::GeneralResult<nn::SharedBuffer> allocate(
+            const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+            const std::vector<nn::BufferRole>& inputRoles,
+            const std::vector<nn::BufferRole>& outputRoles) const override;
+
+  private:
+    const std::string kName;
+    const std::string kVersionString;
+    const nn::DeviceType kDeviceType;
+    const std::vector<nn::Extension> kExtensions;
+    const nn::Capabilities kCapabilities;
+    const std::pair<uint32_t, uint32_t> kNumberOfCacheFilesNeeded;
+    const sp<V1_3::IDevice> kDevice;
+    const hal::utils::DeathHandler kDeathHandler;
+};
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
new file mode 100644
index 0000000..e0d69dd
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
@@ -0,0 +1,71 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
+
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class PreparedModel final : public nn::IPreparedModel {
+    struct PrivateConstructorTag {};
+
+  public:
+    static nn::GeneralResult<std::shared_ptr<const PreparedModel>> create(
+            sp<V1_3::IPreparedModel> preparedModel);
+
+    PreparedModel(PrivateConstructorTag tag, sp<V1_3::IPreparedModel> preparedModel,
+                  hal::utils::DeathHandler deathHandler);
+
+    nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
+            const nn::Request& request, nn::MeasureTiming measure,
+            const nn::OptionalTimePoint& deadline,
+            const nn::OptionalTimeoutDuration& loopTimeoutDuration) const override;
+
+    nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> executeFenced(
+            const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+            nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+            const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+            const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const override;
+
+    std::any getUnderlyingResource() const override;
+
+  private:
+    nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeSynchronously(
+            const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+            const OptionalTimeoutDuration& loopTimeoutDuration) const;
+    nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeAsynchronously(
+            const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+            const OptionalTimeoutDuration& loopTimeoutDuration) const;
+
+    const sp<V1_3::IPreparedModel> kPreparedModel;
+    const hal::utils::DeathHandler kDeathHandler;
+};
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h
new file mode 100644
index 0000000..2bc3257
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <string>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name);
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
index f8c975d..e61859d 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
@@ -22,6 +22,7 @@
 #include <android-base/logging.h>
 #include <android/hardware/neuralnetworks/1.3/types.h>
 #include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
 #include <nnapi/Types.h>
 #include <nnapi/Validation.h>
 #include <nnapi/hal/1.0/Conversions.h>
@@ -35,10 +36,14 @@
 
 template <typename Type>
 nn::Result<void> validate(const Type& halObject) {
-    const auto canonical = NN_TRY(nn::convert(halObject));
-    const auto version = NN_TRY(nn::validate(canonical));
+    const auto maybeCanonical = nn::convert(halObject);
+    if (!maybeCanonical.has_value()) {
+        return nn::error() << maybeCanonical.error().message;
+    }
+    const auto version = NN_TRY(nn::validate(maybeCanonical.value()));
     if (version > utils::kVersion) {
-        return NN_ERROR() << "";
+        return NN_ERROR() << "Insufficient version: " << version << " vs required "
+                          << utils::kVersion;
     }
     return {};
 }
@@ -55,9 +60,14 @@
 template <typename Type>
 decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
     auto canonical = NN_TRY(nn::convert(halObject));
-    const auto version = NN_TRY(nn::validate(canonical));
+    const auto maybeVersion = nn::validate(canonical);
+    if (!maybeVersion.has_value()) {
+        return nn::error() << maybeVersion.error();
+    }
+    const auto version = maybeVersion.value();
     if (version > utils::kVersion) {
-        return NN_ERROR() << "";
+        return NN_ERROR() << "Insufficient version: " << version << " vs required "
+                          << utils::kVersion;
     }
     return canonical;
 }
diff --git a/neuralnetworks/1.3/utils/src/Buffer.cpp b/neuralnetworks/1.3/utils/src/Buffer.cpp
new file mode 100644
index 0000000..f3fe9b5
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Buffer.cpp
@@ -0,0 +1,93 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#include "Buffer.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IBuffer.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/HandleError.h>
+
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <memory>
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<std::shared_ptr<const Buffer>> Buffer::create(
+        sp<V1_3::IBuffer> buffer, nn::Request::MemoryDomainToken token) {
+    if (buffer == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "V1_3::utils::Buffer::create must have non-null buffer";
+    }
+    if (token == static_cast<nn::Request::MemoryDomainToken>(0)) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "V1_3::utils::Buffer::create must have non-zero token";
+    }
+
+    return std::make_shared<const Buffer>(PrivateConstructorTag{}, std::move(buffer), token);
+}
+
+Buffer::Buffer(PrivateConstructorTag /*tag*/, sp<V1_3::IBuffer> buffer,
+               nn::Request::MemoryDomainToken token)
+    : kBuffer(std::move(buffer)), kToken(token) {
+    CHECK(kBuffer != nullptr);
+    CHECK(kToken != static_cast<nn::Request::MemoryDomainToken>(0));
+}
+
+nn::Request::MemoryDomainToken Buffer::getToken() const {
+    return kToken;
+}
+
+nn::GeneralResult<void> Buffer::copyTo(const nn::Memory& dst) const {
+    const auto hidlDst = NN_TRY(V1_0::utils::convert(dst));
+
+    const auto ret = kBuffer->copyTo(hidlDst);
+    const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        return NN_ERROR(canonical) << "IBuffer::copyTo failed with " << toString(status);
+    }
+
+    return {};
+}
+
+nn::GeneralResult<void> Buffer::copyFrom(const nn::Memory& src,
+                                         const nn::Dimensions& dimensions) const {
+    const auto hidlSrc = NN_TRY(V1_0::utils::convert(src));
+    const auto hidlDimensions = hidl_vec<uint32_t>(dimensions);
+
+    const auto ret = kBuffer->copyFrom(hidlSrc, hidlDimensions);
+    const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        return NN_ERROR(canonical) << "IBuffer::copyFrom failed with " << toString(status);
+    }
+
+    return {};
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Callbacks.cpp b/neuralnetworks/1.3/utils/src/Callbacks.cpp
new file mode 100644
index 0000000..ff81275
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Callbacks.cpp
@@ -0,0 +1,184 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#include "Callbacks.h"
+
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/1.0/PreparedModel.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/1.2/PreparedModel.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+        const sp<V1_0::IPreparedModel>& preparedModel) {
+    return NN_TRY(V1_0::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+        const sp<V1_2::IPreparedModel>& preparedModel) {
+    return NN_TRY(V1_2::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+        const sp<IPreparedModel>& preparedModel) {
+    return NN_TRY(utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+                                     const V1_2::Timing& timing) {
+    return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+                          NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResults(const hidl_vec<V1_2::OutputShape>& outputShapes,
+                               const V1_2::Timing& timing) {
+    return hal::utils::makeExecutionFailure(
+            convertExecutionGeneralResultsHelper(outputShapes, timing));
+}
+
+}  // namespace
+
+Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
+                                           const sp<V1_0::IPreparedModel>& preparedModel) {
+    if (status != V1_0::ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+    } else if (preparedModel == nullptr) {
+        notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                       << "Returned preparedModel is nullptr");
+    } else {
+        notifyInternal(convertPreparedModel(preparedModel));
+    }
+    return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_2(V1_0::ErrorStatus status,
+                                               const sp<V1_2::IPreparedModel>& preparedModel) {
+    if (status != V1_0::ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+    } else if (preparedModel == nullptr) {
+        notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                       << "Returned preparedModel is nullptr");
+    } else {
+        notifyInternal(convertPreparedModel(preparedModel));
+    }
+    return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_3(ErrorStatus status,
+                                               const sp<IPreparedModel>& preparedModel) {
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+    } else if (preparedModel == nullptr) {
+        notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                       << "Returned preparedModel is nullptr");
+    } else {
+        notifyInternal(convertPreparedModel(preparedModel));
+    }
+    return Void();
+}
+
+void PreparedModelCallback::notifyAsDeadObject() {
+    notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+PreparedModelCallback::Data PreparedModelCallback::get() {
+    return mData.take();
+}
+
+void PreparedModelCallback::notifyInternal(PreparedModelCallback::Data result) {
+    mData.put(std::move(result));
+}
+
+// ExecutionCallback methods begin here
+
+Return<void> ExecutionCallback::notify(V1_0::ErrorStatus status) {
+    if (status != V1_0::ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+    } else {
+        notifyInternal({});
+    }
+    return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_2(V1_0::ErrorStatus status,
+                                           const hidl_vec<V1_2::OutputShape>& outputShapes,
+                                           const V1_2::Timing& timing) {
+    if (status != V1_0::ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+    } else {
+        notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+    }
+    return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_3(ErrorStatus status,
+                                           const hidl_vec<V1_2::OutputShape>& outputShapes,
+                                           const V1_2::Timing& timing) {
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+    } else {
+        notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+    }
+    return Void();
+}
+
+void ExecutionCallback::notifyAsDeadObject() {
+    notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+ExecutionCallback::Data ExecutionCallback::get() {
+    return mData.take();
+}
+
+void ExecutionCallback::notifyInternal(ExecutionCallback::Data result) {
+    mData.put(std::move(result));
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 4c54e3b..0dc0785 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -27,6 +27,7 @@
 #include <nnapi/hal/1.0/Conversions.h>
 #include <nnapi/hal/1.2/Conversions.h>
 #include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
 
 #include <algorithm>
 #include <chrono>
@@ -79,7 +80,7 @@
 using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
 
 template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
     std::vector<ConvertOutput<Type>> canonical;
     canonical.reserve(arguments.size());
     for (const auto& argument : arguments) {
@@ -89,25 +90,25 @@
 }
 
 template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
     return convertVec(arguments);
 }
 
 }  // anonymous namespace
 
-Result<OperandType> convert(const hal::V1_3::OperandType& operandType) {
+GeneralResult<OperandType> convert(const hal::V1_3::OperandType& operandType) {
     return static_cast<OperandType>(operandType);
 }
 
-Result<OperationType> convert(const hal::V1_3::OperationType& operationType) {
+GeneralResult<OperationType> convert(const hal::V1_3::OperationType& operationType) {
     return static_cast<OperationType>(operationType);
 }
 
-Result<Priority> convert(const hal::V1_3::Priority& priority) {
+GeneralResult<Priority> convert(const hal::V1_3::Priority& priority) {
     return static_cast<Priority>(priority);
 }
 
-Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
+GeneralResult<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
     const bool validOperandTypes = std::all_of(
             capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
             [](const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
@@ -115,13 +116,14 @@
                 return !maybeType.has_value() ? false : validOperandType(maybeType.value());
             });
     if (!validOperandTypes) {
-        return NN_ERROR()
+        return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
                << "Invalid OperandType when converting OperandPerformance in Capabilities";
     }
 
     auto operandPerformance = NN_TRY(convert(capabilities.operandPerformance));
-    auto table =
-            NN_TRY(Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)));
+    auto table = NN_TRY(hal::utils::makeGeneralFailure(
+            Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
+            nn::ErrorStatus::GENERAL_FAILURE));
 
     return Capabilities{
             .relaxedFloat32toFloat16PerformanceScalar =
@@ -134,7 +136,7 @@
     };
 }
 
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<Capabilities::OperandPerformance> convert(
         const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
     return Capabilities::OperandPerformance{
             .type = NN_TRY(convert(operandPerformance.type)),
@@ -142,7 +144,7 @@
     };
 }
 
-Result<Operation> convert(const hal::V1_3::Operation& operation) {
+GeneralResult<Operation> convert(const hal::V1_3::Operation& operation) {
     return Operation{
             .type = NN_TRY(convert(operation.type)),
             .inputs = operation.inputs,
@@ -150,11 +152,11 @@
     };
 }
 
-Result<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime) {
+GeneralResult<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime) {
     return static_cast<Operand::LifeTime>(operandLifeTime);
 }
 
-Result<Operand> convert(const hal::V1_3::Operand& operand) {
+GeneralResult<Operand> convert(const hal::V1_3::Operand& operand) {
     return Operand{
             .type = NN_TRY(convert(operand.type)),
             .dimensions = operand.dimensions,
@@ -166,7 +168,7 @@
     };
 }
 
-Result<Model> convert(const hal::V1_3::Model& model) {
+GeneralResult<Model> convert(const hal::V1_3::Model& model) {
     return Model{
             .main = NN_TRY(convert(model.main)),
             .referenced = NN_TRY(convert(model.referenced)),
@@ -177,7 +179,7 @@
     };
 }
 
-Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
+GeneralResult<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
     auto operations = NN_TRY(convert(subgraph.operations));
 
     // Verify number of consumers.
@@ -186,9 +188,10 @@
     CHECK(subgraph.operands.size() == numberOfConsumers.size());
     for (size_t i = 0; i < subgraph.operands.size(); ++i) {
         if (subgraph.operands[i].numberOfConsumers != numberOfConsumers[i]) {
-            return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
-                              << numberOfConsumers[i] << " but found "
-                              << subgraph.operands[i].numberOfConsumers;
+            return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                   << "Invalid numberOfConsumers for operand " << i << ", expected "
+                   << numberOfConsumers[i] << " but found "
+                   << subgraph.operands[i].numberOfConsumers;
         }
     }
 
@@ -200,11 +203,11 @@
     };
 }
 
-Result<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc) {
+GeneralResult<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc) {
     return BufferDesc{.dimensions = bufferDesc.dimensions};
 }
 
-Result<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
+GeneralResult<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
     return BufferRole{
             .modelIndex = bufferRole.modelIndex,
             .ioIndex = bufferRole.ioIndex,
@@ -212,7 +215,7 @@
     };
 }
 
-Result<Request> convert(const hal::V1_3::Request& request) {
+GeneralResult<Request> convert(const hal::V1_3::Request& request) {
     return Request{
             .inputs = NN_TRY(convert(request.inputs)),
             .outputs = NN_TRY(convert(request.outputs)),
@@ -220,7 +223,7 @@
     };
 }
 
-Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool) {
+GeneralResult<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool) {
     using Discriminator = hal::V1_3::Request::MemoryPool::hidl_discriminator;
     switch (memoryPool.getDiscriminator()) {
         case Discriminator::hidlMemory:
@@ -228,15 +231,16 @@
         case Discriminator::token:
             return static_cast<Request::MemoryDomainToken>(memoryPool.token());
     }
-    return NN_ERROR() << "Invalid Request::MemoryPool discriminator "
-                      << underlyingType(memoryPool.getDiscriminator());
+    return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+           << "Invalid Request::MemoryPool discriminator "
+           << underlyingType(memoryPool.getDiscriminator());
 }
 
-Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint) {
+GeneralResult<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint) {
     constexpr auto kTimePointMaxCount = TimePoint::max().time_since_epoch().count();
-    const auto makeTimePoint = [](uint64_t count) -> Result<OptionalTimePoint> {
+    const auto makeTimePoint = [](uint64_t count) -> GeneralResult<OptionalTimePoint> {
         if (count > kTimePointMaxCount) {
-            return NN_ERROR()
+            return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
                    << "Unable to convert OptionalTimePoint because the count exceeds the max";
         }
         const auto nanoseconds = std::chrono::nanoseconds{count};
@@ -250,16 +254,17 @@
         case Discriminator::nanosecondsSinceEpoch:
             return makeTimePoint(optionalTimePoint.nanosecondsSinceEpoch());
     }
-    return NN_ERROR() << "Invalid OptionalTimePoint discriminator "
-                      << underlyingType(optionalTimePoint.getDiscriminator());
+    return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+           << "Invalid OptionalTimePoint discriminator "
+           << underlyingType(optionalTimePoint.getDiscriminator());
 }
 
-Result<OptionalTimeoutDuration> convert(
+GeneralResult<OptionalTimeoutDuration> convert(
         const hal::V1_3::OptionalTimeoutDuration& optionalTimeoutDuration) {
     constexpr auto kTimeoutDurationMaxCount = TimeoutDuration::max().count();
-    const auto makeTimeoutDuration = [](uint64_t count) -> Result<OptionalTimeoutDuration> {
+    const auto makeTimeoutDuration = [](uint64_t count) -> GeneralResult<OptionalTimeoutDuration> {
         if (count > kTimeoutDurationMaxCount) {
-            return NN_ERROR()
+            return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
                    << "Unable to convert OptionalTimeoutDuration because the count exceeds the max";
         }
         return TimeoutDuration{count};
@@ -272,11 +277,12 @@
         case Discriminator::nanoseconds:
             return makeTimeoutDuration(optionalTimeoutDuration.nanoseconds());
     }
-    return NN_ERROR() << "Invalid OptionalTimeoutDuration discriminator "
-                      << underlyingType(optionalTimeoutDuration.getDiscriminator());
+    return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+           << "Invalid OptionalTimeoutDuration discriminator "
+           << underlyingType(optionalTimeoutDuration.getDiscriminator());
 }
 
-Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
+GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
     switch (status) {
         case hal::V1_3::ErrorStatus::NONE:
         case hal::V1_3::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -289,10 +295,11 @@
         case hal::V1_3::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
             return static_cast<ErrorStatus>(status);
     }
-    return NN_ERROR() << "Invalid ErrorStatus " << underlyingType(status);
+    return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+           << "Invalid ErrorStatus " << underlyingType(status);
 }
 
-Result<std::vector<BufferRole>> convert(
+GeneralResult<std::vector<BufferRole>> convert(
         const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles) {
     return convertVec(bufferRoles);
 }
@@ -304,32 +311,32 @@
 
 using utils::convert;
 
-nn::Result<V1_0::PerformanceInfo> convert(
+nn::GeneralResult<V1_0::PerformanceInfo> convert(
         const nn::Capabilities::PerformanceInfo& performanceInfo) {
     return V1_0::utils::convert(performanceInfo);
 }
 
-nn::Result<V1_0::DataLocation> convert(const nn::DataLocation& dataLocation) {
+nn::GeneralResult<V1_0::DataLocation> convert(const nn::DataLocation& dataLocation) {
     return V1_0::utils::convert(dataLocation);
 }
 
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
     return V1_0::utils::convert(operandValues);
 }
 
-nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
     return V1_0::utils::convert(memory);
 }
 
-nn::Result<V1_0::RequestArgument> convert(const nn::Request::Argument& argument) {
+nn::GeneralResult<V1_0::RequestArgument> convert(const nn::Request::Argument& argument) {
     return V1_0::utils::convert(argument);
 }
 
-nn::Result<V1_2::Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
+nn::GeneralResult<V1_2::Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
     return V1_2::utils::convert(extraParams);
 }
 
-nn::Result<V1_2::Model::ExtensionNameAndPrefix> convert(
+nn::GeneralResult<V1_2::Model::ExtensionNameAndPrefix> convert(
         const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
     return V1_2::utils::convert(extensionNameAndPrefix);
 }
@@ -338,7 +345,7 @@
 using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
 
 template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
     hidl_vec<ConvertOutput<Type>> halObject(arguments.size());
     for (size_t i = 0; i < arguments.size(); ++i) {
         halObject[i] = NN_TRY(convert(arguments[i]));
@@ -347,42 +354,41 @@
 }
 
 template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
     return convertVec(arguments);
 }
 
-nn::Result<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
     Request::MemoryPool ret;
     ret.hidlMemory(NN_TRY(convert(memory)));
     return ret;
 }
 
-nn::Result<Request::MemoryPool> makeMemoryPool(const nn::Request::MemoryDomainToken& token) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Request::MemoryDomainToken& token) {
     Request::MemoryPool ret;
     ret.token(underlyingType(token));
     return ret;
 }
 
-nn::Result<Request::MemoryPool> makeMemoryPool(
-        const std::shared_ptr<const nn::IBuffer>& /*buffer*/) {
-    return NN_ERROR() << "Unable to make memory pool from IBuffer";
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::SharedBuffer& /*buffer*/) {
+    return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Unable to make memory pool from IBuffer";
 }
 
 }  // anonymous namespace
 
-nn::Result<OperandType> convert(const nn::OperandType& operandType) {
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType) {
     return static_cast<OperandType>(operandType);
 }
 
-nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType) {
     return static_cast<OperationType>(operationType);
 }
 
-nn::Result<Priority> convert(const nn::Priority& priority) {
+nn::GeneralResult<Priority> convert(const nn::Priority& priority) {
     return static_cast<Priority>(priority);
 }
 
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
     std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
     operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
     std::copy_if(capabilities.operandPerformance.asVector().begin(),
@@ -403,7 +409,7 @@
     };
 }
 
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
         const nn::Capabilities::OperandPerformance& operandPerformance) {
     return Capabilities::OperandPerformance{
             .type = NN_TRY(convert(operandPerformance.type)),
@@ -411,7 +417,7 @@
     };
 }
 
-nn::Result<Operation> convert(const nn::Operation& operation) {
+nn::GeneralResult<Operation> convert(const nn::Operation& operation) {
     return Operation{
             .type = NN_TRY(convert(operation.type)),
             .inputs = operation.inputs,
@@ -419,14 +425,15 @@
     };
 }
 
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime) {
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime) {
     if (operandLifeTime == nn::Operand::LifeTime::POINTER) {
-        return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "Model cannot be converted because it contains pointer-based memory";
     }
     return static_cast<OperandLifeTime>(operandLifeTime);
 }
 
-nn::Result<Operand> convert(const nn::Operand& operand) {
+nn::GeneralResult<Operand> convert(const nn::Operand& operand) {
     return Operand{
             .type = NN_TRY(convert(operand.type)),
             .dimensions = operand.dimensions,
@@ -439,9 +446,10 @@
     };
 }
 
-nn::Result<Model> convert(const nn::Model& model) {
+nn::GeneralResult<Model> convert(const nn::Model& model) {
     if (!hal::utils::hasNoPointerData(model)) {
-        return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "Model cannot be converted because it contains pointer-based memory";
     }
 
     return Model{
@@ -454,7 +462,7 @@
     };
 }
 
-nn::Result<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
+nn::GeneralResult<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
     auto operands = NN_TRY(convert(subgraph.operands));
 
     // Update number of consumers.
@@ -473,11 +481,11 @@
     };
 }
 
-nn::Result<BufferDesc> convert(const nn::BufferDesc& bufferDesc) {
+nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc) {
     return BufferDesc{.dimensions = bufferDesc.dimensions};
 }
 
-nn::Result<BufferRole> convert(const nn::BufferRole& bufferRole) {
+nn::GeneralResult<BufferRole> convert(const nn::BufferRole& bufferRole) {
     return BufferRole{
             .modelIndex = bufferRole.modelIndex,
             .ioIndex = bufferRole.ioIndex,
@@ -485,9 +493,10 @@
     };
 }
 
-nn::Result<Request> convert(const nn::Request& request) {
+nn::GeneralResult<Request> convert(const nn::Request& request) {
     if (!hal::utils::hasNoPointerData(request)) {
-        return NN_ERROR() << "Request cannot be converted because it contains pointer-based memory";
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "Request cannot be converted because it contains pointer-based memory";
     }
 
     return Request{
@@ -497,30 +506,31 @@
     };
 }
 
-nn::Result<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool) {
+nn::GeneralResult<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool) {
     return std::visit([](const auto& o) { return makeMemoryPool(o); }, memoryPool);
 }
 
-nn::Result<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint) {
+nn::GeneralResult<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint) {
     OptionalTimePoint ret;
     if (optionalTimePoint.has_value()) {
         const auto count = optionalTimePoint.value().time_since_epoch().count();
         if (count < 0) {
-            return NN_ERROR() << "Unable to convert OptionalTimePoint because time since epoch "
-                                 "count is negative";
+            return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                   << "Unable to convert OptionalTimePoint because time since epoch count is "
+                      "negative";
         }
         ret.nanosecondsSinceEpoch(count);
     }
     return ret;
 }
 
-nn::Result<OptionalTimeoutDuration> convert(
+nn::GeneralResult<OptionalTimeoutDuration> convert(
         const nn::OptionalTimeoutDuration& optionalTimeoutDuration) {
     OptionalTimeoutDuration ret;
     if (optionalTimeoutDuration.has_value()) {
         const auto count = optionalTimeoutDuration.value().count();
         if (count < 0) {
-            return NN_ERROR()
+            return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
                    << "Unable to convert OptionalTimeoutDuration because count is negative";
         }
         ret.nanoseconds(count);
@@ -528,7 +538,7 @@
     return ret;
 }
 
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
     switch (errorStatus) {
         case nn::ErrorStatus::NONE:
         case nn::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -545,7 +555,7 @@
     }
 }
 
-nn::Result<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
+nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
     return convertVec(bufferRoles);
 }
 
diff --git a/neuralnetworks/1.3/utils/src/Device.cpp b/neuralnetworks/1.3/utils/src/Device.cpp
new file mode 100644
index 0000000..c215f39
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Device.cpp
@@ -0,0 +1,269 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#include "Device.h"
+
+#include "Buffer.h"
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.1/Conversions.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/1.2/Device.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <any>
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<hidl_vec<sp<IPreparedModel>>> convert(
+        const std::vector<nn::SharedPreparedModel>& preparedModels) {
+    hidl_vec<sp<IPreparedModel>> hidlPreparedModels(preparedModels.size());
+    for (size_t i = 0; i < preparedModels.size(); ++i) {
+        std::any underlyingResource = preparedModels[i]->getUnderlyingResource();
+        if (const auto* hidlPreparedModel =
+                    std::any_cast<sp<IPreparedModel>>(&underlyingResource)) {
+            hidlPreparedModels[i] = *hidlPreparedModel;
+        } else {
+            return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+                   << "Unable to convert from nn::IPreparedModel to V1_3::IPreparedModel";
+        }
+    }
+    return hidlPreparedModels;
+}
+
+nn::GeneralResult<nn::SharedBuffer> convert(
+        nn::GeneralResult<std::shared_ptr<const Buffer>> result) {
+    return NN_TRY(std::move(result));
+}
+
+}  // namespace
+
+nn::GeneralResult<std::shared_ptr<const Device>> Device::create(std::string name,
+                                                                sp<V1_3::IDevice> device) {
+    if (name.empty()) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "V1_3::utils::Device::create must have non-empty name";
+    }
+    if (device == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "V1_3::utils::Device::create must have non-null device";
+    }
+
+    auto versionString = NN_TRY(V1_2::utils::initVersionString(device.get()));
+    const auto deviceType = NN_TRY(V1_2::utils::initDeviceType(device.get()));
+    auto extensions = NN_TRY(V1_2::utils::initExtensions(device.get()));
+    auto capabilities = NN_TRY(V1_2::utils::initCapabilities(device.get()));
+    const auto numberOfCacheFilesNeeded =
+            NN_TRY(V1_2::utils::initNumberOfCacheFilesNeeded(device.get()));
+
+    auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(device));
+    return std::make_shared<const Device>(
+            PrivateConstructorTag{}, std::move(name), std::move(versionString), deviceType,
+            std::move(extensions), std::move(capabilities), numberOfCacheFilesNeeded,
+            std::move(device), std::move(deathHandler));
+}
+
+Device::Device(PrivateConstructorTag /*tag*/, std::string name, std::string versionString,
+               nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+               nn::Capabilities capabilities,
+               std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded, sp<V1_3::IDevice> device,
+               hal::utils::DeathHandler deathHandler)
+    : kName(std::move(name)),
+      kVersionString(std::move(versionString)),
+      kDeviceType(deviceType),
+      kExtensions(std::move(extensions)),
+      kCapabilities(std::move(capabilities)),
+      kNumberOfCacheFilesNeeded(numberOfCacheFilesNeeded),
+      kDevice(std::move(device)),
+      kDeathHandler(std::move(deathHandler)) {}
+
+const std::string& Device::getName() const {
+    return kName;
+}
+
+const std::string& Device::getVersionString() const {
+    return kVersionString;
+}
+
+nn::Version Device::getFeatureLevel() const {
+    return nn::Version::ANDROID_R;
+}
+
+nn::DeviceType Device::getType() const {
+    return kDeviceType;
+}
+
+const std::vector<nn::Extension>& Device::getSupportedExtensions() const {
+    return kExtensions;
+}
+
+const nn::Capabilities& Device::getCapabilities() const {
+    return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> Device::getNumberOfCacheFilesNeeded() const {
+    return kNumberOfCacheFilesNeeded;
+}
+
+nn::GeneralResult<void> Device::wait() const {
+    const auto ret = kDevice->ping();
+    return hal::utils::handleTransportError(ret);
+}
+
+nn::GeneralResult<std::vector<bool>> Device::getSupportedOperations(const nn::Model& model) const {
+    // Ensure that model is ready for IPC.
+    std::optional<nn::Model> maybeModelInShared;
+    const nn::Model& modelInShared =
+            NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+    const auto hidlModel = NN_TRY(convert(modelInShared));
+
+    nn::GeneralResult<std::vector<bool>> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                                                  << "uninitialized";
+    auto cb = [&result, &model](ErrorStatus status, const hidl_vec<bool>& supportedOperations) {
+        if (status != ErrorStatus::NONE) {
+            const auto canonical =
+                    validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+            result = NN_ERROR(canonical)
+                     << "IDevice::getSupportedOperations_1_3 failed with " << toString(status);
+        } else if (supportedOperations.size() != model.main.operations.size()) {
+            result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                     << "IDevice::getSupportedOperations_1_3 returned vector of size "
+                     << supportedOperations.size() << " but expected "
+                     << model.main.operations.size();
+        } else {
+            result = supportedOperations;
+        }
+    };
+
+    const auto ret = kDevice->getSupportedOperations_1_3(hidlModel, cb);
+    NN_TRY(hal::utils::handleTransportError(ret));
+
+    return result;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModel(
+        const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+        nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+        const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+    // Ensure that model is ready for IPC.
+    std::optional<nn::Model> maybeModelInShared;
+    const nn::Model& modelInShared =
+            NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+    const auto hidlModel = NN_TRY(convert(modelInShared));
+    const auto hidlPreference = NN_TRY(V1_1::utils::convert(preference));
+    const auto hidlPriority = NN_TRY(convert(priority));
+    const auto hidlDeadline = NN_TRY(convert(deadline));
+    const auto hidlModelCache = NN_TRY(V1_2::utils::convert(modelCache));
+    const auto hidlDataCache = NN_TRY(V1_2::utils::convert(dataCache));
+    const auto hidlToken = token;
+
+    const auto cb = sp<PreparedModelCallback>::make();
+    const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+    const auto ret =
+            kDevice->prepareModel_1_3(hidlModel, hidlPreference, hidlPriority, hidlDeadline,
+                                      hidlModelCache, hidlDataCache, hidlToken, cb);
+    const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        return NN_ERROR(canonical) << "prepareModel_1_3 failed with " << toString(status);
+    }
+
+    return cb->get();
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModelFromCache(
+        nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+        const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+    const auto hidlDeadline = NN_TRY(convert(deadline));
+    const auto hidlModelCache = NN_TRY(V1_2::utils::convert(modelCache));
+    const auto hidlDataCache = NN_TRY(V1_2::utils::convert(dataCache));
+    const auto hidlToken = token;
+
+    const auto cb = sp<PreparedModelCallback>::make();
+    const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+    const auto ret = kDevice->prepareModelFromCache_1_3(hidlDeadline, hidlModelCache, hidlDataCache,
+                                                        hidlToken, cb);
+    const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        return NN_ERROR(canonical) << "prepareModelFromCache_1_3 failed with " << toString(status);
+    }
+
+    return cb->get();
+}
+
+nn::GeneralResult<nn::SharedBuffer> Device::allocate(
+        const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+        const std::vector<nn::BufferRole>& inputRoles,
+        const std::vector<nn::BufferRole>& outputRoles) const {
+    const auto hidlDesc = NN_TRY(convert(desc));
+    const auto hidlPreparedModels = NN_TRY(convert(preparedModels));
+    const auto hidlInputRoles = NN_TRY(convert(inputRoles));
+    const auto hidlOutputRoles = NN_TRY(convert(outputRoles));
+
+    nn::GeneralResult<nn::SharedBuffer> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+                                                 << "uninitialized";
+    auto cb = [&result](ErrorStatus status, const sp<IBuffer>& buffer, uint32_t token) {
+        if (status != ErrorStatus::NONE) {
+            const auto canonical =
+                    validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+            result = NN_ERROR(canonical) << "IDevice::allocate failed with " << toString(status);
+        } else if (buffer == nullptr) {
+            result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Returned buffer is nullptr";
+        } else if (token == 0) {
+            result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Returned token is invalid (0)";
+        } else {
+            result = convert(
+                    Buffer::create(buffer, static_cast<nn::Request::MemoryDomainToken>(token)));
+        }
+    };
+
+    const auto ret =
+            kDevice->allocate(hidlDesc, hidlPreparedModels, hidlInputRoles, hidlOutputRoles, cb);
+    NN_TRY(hal::utils::handleTransportError(ret));
+
+    return result;
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/PreparedModel.cpp b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
new file mode 100644
index 0000000..df9b280
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
@@ -0,0 +1,267 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#include "PreparedModel.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+                              const V1_2::Timing& timing) {
+    return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+                          NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
+        const hidl_vec<V1_2::OutputShape>& outputShapes, const V1_2::Timing& timing) {
+    return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
+}
+
+nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
+        const std::vector<nn::SyncFence>& syncFences) {
+    hidl_vec<hidl_handle> handles(syncFences.size());
+    for (size_t i = 0; i < syncFences.size(); ++i) {
+        handles[i] = NN_TRY(V1_2::utils::convert(syncFences[i].getHandle()));
+    }
+    return handles;
+}
+
+nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> convertFencedExecutionCallbackResults(
+        const V1_2::Timing& timingLaunched, const V1_2::Timing& timingFenced) {
+    return std::make_pair(NN_TRY(validatedConvertToCanonical(timingLaunched)),
+                          NN_TRY(validatedConvertToCanonical(timingFenced)));
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+convertExecuteFencedResults(const hidl_handle& syncFence,
+                            const sp<IFencedExecutionCallback>& callback) {
+    auto resultSyncFence = nn::SyncFence::createAsSignaled();
+    if (syncFence.getNativeHandle() != nullptr) {
+        auto nativeHandle = NN_TRY(validatedConvertToCanonical(syncFence));
+        resultSyncFence = NN_TRY(hal::utils::makeGeneralFailure(
+                nn::SyncFence::create(std::move(nativeHandle)), nn::ErrorStatus::GENERAL_FAILURE));
+    }
+
+    if (callback == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "callback is null";
+    }
+
+    // Create callback which can be used to retrieve the execution error status and timings.
+    nn::ExecuteFencedInfoCallback resultCallback =
+            [callback]() -> nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> {
+        nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> result =
+                NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+        auto cb = [&result](ErrorStatus status, const V1_2::Timing& timingLaunched,
+                            const V1_2::Timing& timingFenced) {
+            if (status != ErrorStatus::NONE) {
+                const auto canonical = validatedConvertToCanonical(status).value_or(
+                        nn::ErrorStatus::GENERAL_FAILURE);
+                result = NN_ERROR(canonical) << "getExecutionInfo failed with " << toString(status);
+            } else {
+                result = convertFencedExecutionCallbackResults(timingLaunched, timingFenced);
+            }
+        };
+
+        const auto ret = callback->getExecutionInfo(cb);
+        NN_TRY(hal::utils::handleTransportError(ret));
+
+        return result;
+    };
+
+    return std::make_pair(std::move(resultSyncFence), std::move(resultCallback));
+}
+
+}  // namespace
+
+nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
+        sp<V1_3::IPreparedModel> preparedModel) {
+    if (preparedModel == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+               << "V1_3::utils::PreparedModel::create must have non-null preparedModel";
+    }
+
+    auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
+    return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
+                                                 std::move(deathHandler));
+}
+
+PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_3::IPreparedModel> preparedModel,
+                             hal::utils::DeathHandler deathHandler)
+    : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeSynchronously(const Request& request, V1_2::MeasureTiming measure,
+                                    const OptionalTimePoint& deadline,
+                                    const OptionalTimeoutDuration& loopTimeoutDuration) const {
+    nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+            NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+    const auto cb = [&result](ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+                              const V1_2::Timing& timing) {
+        if (status != ErrorStatus::NONE) {
+            const auto canonical =
+                    validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+            result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
+        } else {
+            result = convertExecutionResults(outputShapes, timing);
+        }
+    };
+
+    const auto ret = kPreparedModel->executeSynchronously_1_3(request, measure, deadline,
+                                                              loopTimeoutDuration, cb);
+    NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+
+    return result;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeAsynchronously(const Request& request, V1_2::MeasureTiming measure,
+                                     const OptionalTimePoint& deadline,
+                                     const OptionalTimeoutDuration& loopTimeoutDuration) const {
+    const auto cb = sp<ExecutionCallback>::make();
+    const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+    const auto ret =
+            kPreparedModel->execute_1_3(request, measure, deadline, loopTimeoutDuration, cb);
+    const auto status =
+            NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+    if (status != ErrorStatus::NONE) {
+        const auto canonical =
+                validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+        return NN_ERROR(canonical) << "executeAsynchronously failed with " << toString(status);
+    }
+
+    return cb->get();
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
+        const nn::Request& request, nn::MeasureTiming measure,
+        const nn::OptionalTimePoint& deadline,
+        const nn::OptionalTimeoutDuration& loopTimeoutDuration) const {
+    // Ensure that request is ready for IPC.
+    std::optional<nn::Request> maybeRequestInShared;
+    const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
+            hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
+
+    const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
+    const auto hidlMeasure =
+            NN_TRY(hal::utils::makeExecutionFailure(V1_2::utils::convert(measure)));
+    const auto hidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
+    const auto hidlLoopTimeoutDuration =
+            NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
+
+    nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+            NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+    const bool preferSynchronous = true;
+
+    // Execute synchronously if allowed.
+    if (preferSynchronous) {
+        result = executeSynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+                                      hidlLoopTimeoutDuration);
+    }
+
+    // Run asymchronous execution if execution has not already completed.
+    if (!result.has_value()) {
+        result = executeAsynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+                                       hidlLoopTimeoutDuration);
+    }
+
+    // Flush output buffers if suxcessful execution.
+    if (result.has_value()) {
+        NN_TRY(hal::utils::makeExecutionFailure(
+                hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
+    }
+
+    return result;
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFenced(const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+                             nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+                             const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+                             const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const {
+    // Ensure that request is ready for IPC.
+    std::optional<nn::Request> maybeRequestInShared;
+    const nn::Request& requestInShared =
+            NN_TRY(hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared));
+
+    const auto hidlRequest = NN_TRY(convert(requestInShared));
+    const auto hidlWaitFor = NN_TRY(convertSyncFences(waitFor));
+    const auto hidlMeasure = NN_TRY(V1_2::utils::convert(measure));
+    const auto hidlDeadline = NN_TRY(convert(deadline));
+    const auto hidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
+    const auto hidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+
+    nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> result =
+            NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+    auto cb = [&result](ErrorStatus status, const hidl_handle& syncFence,
+                        const sp<IFencedExecutionCallback>& callback) {
+        if (status != ErrorStatus::NONE) {
+            const auto canonical =
+                    validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+            result = NN_ERROR(canonical) << "executeFenced failed with " << toString(status);
+        } else {
+            result = convertExecuteFencedResults(syncFence, callback);
+        }
+    };
+
+    const auto ret = kPreparedModel->executeFenced(hidlRequest, hidlWaitFor, hidlMeasure,
+                                                   hidlDeadline, hidlLoopTimeoutDuration,
+                                                   hidlTimeoutDurationAfterFence, cb);
+    NN_TRY(hal::utils::handleTransportError(ret));
+    auto [syncFence, callback] = NN_TRY(std::move(result));
+
+    // If executeFenced required the request memory to be moved into shared memory, block here until
+    // the fenced execution has completed and flush the memory back.
+    if (maybeRequestInShared.has_value()) {
+        const auto state = syncFence.syncWait({});
+        if (state != nn::SyncFence::FenceState::SIGNALED) {
+            return NN_ERROR() << "syncWait failed with " << state;
+        }
+        NN_TRY(hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared));
+    }
+
+    return std::make_pair(std::move(syncFence), std::move(callback));
+}
+
+std::any PreparedModel::getUnderlyingResource() const {
+    sp<V1_3::IPreparedModel> resource = kPreparedModel;
+    return resource;
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Service.cpp b/neuralnetworks/1.3/utils/src/Service.cpp
new file mode 100644
index 0000000..62887fb
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Service.cpp
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#include "Service.h"
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientDevice.h>
+#include <string>
+#include "Device.h"
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name) {
+    hal::utils::ResilientDevice::Factory makeDevice =
+            [name](bool blocking) -> nn::GeneralResult<nn::SharedDevice> {
+        auto service = blocking ? IDevice::getService(name) : IDevice::tryGetService(name);
+        if (service == nullptr) {
+            return NN_ERROR() << (blocking ? "getService" : "tryGetService") << " returned nullptr";
+        }
+        return Device::create(name, std::move(service));
+    };
+
+    return hal::utils::ResilientDevice::create(std::move(makeDevice));
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_3::utils