Update TFLite NNAPI delegate with NNAPI 1.2 features.

- Only try to delegate to NNAPI 1.2+ if there is at least one accelerator available.

PiperOrigin-RevId: 238036055

tensorflow/lite/delegates/nnapi/nnapi_delegate.cc

@@ -1286,7 +1286,18 @@ TfLiteDelegate* NnApiDelegate() {
             !nnapi->nnapi_exists) {
           return kTfLiteOk;
         }
-
+        // For NNAPI 1.2+, check if there is any accelerator available.
+        // If not, don't delegate to NNAPI's CPU reference implementation.
+        if (nnapi->android_sdk_version >= kMinSdkVersionForNNAPI12) {
+          uint32_t device_count = 0;
+          RETURN_TFLITE_ERROR_IF_NN_ERROR(
+              context, nnapi->ANeuralNetworks_getDeviceCount(&device_count));
+          // Any available accelerator will make the device_count larger than 1.
+          // More sophisticated check and whitelisting can be added later.
+          if (device_count <= 1) {
+            return kTfLiteOk;
+          }
+        }
         // Allocate one element in vector already since TensorFlow Lite uses
         // the first value as the number of nodes. The actual value will be set
         // later, after the vector has been filled.

tensorflow/lite/nnapi/NeuralNetworksTypes.h

@@ -132,6 +132,25 @@ enum {
   ANEURALNETWORKS_PADDING_VALID = 2,
 };
 
+/**
+ * Device types.
+ *
+ * The type of NNAPI device.
+ */
+enum {
+  /** The device type cannot be provided. */
+  ANEURALNETWORKS_DEVICE_UNKNOWN = 0,
+  /** The device does not fall into any category below. */
+  ANEURALNETWORKS_DEVICE_OTHER = 1,
+  /** The device runs NNAPI models on single or multi-core CPU. */
+  ANEURALNETWORKS_DEVICE_CPU = 2,
+  /** The device can run NNAPI models and also accelerate graphics APIs such
+   * as OpenGL ES and Vulkan. */
+  ANEURALNETWORKS_DEVICE_GPU = 3,
+  /** Dedicated accelerator for Machine Learning workloads. */
+  ANEURALNETWORKS_DEVICE_ACCELERATOR = 4,
+};
+
 /**
  * ANeuralNetworksMemory is an opaque type that represents memory.
  *

tensorflow/lite/nnapi/nnapi_implementation.cc

@@ -170,6 +170,7 @@ const NnApi LoadNnApi() {
   LOAD_FUNCTION_OPTIONAL(libneuralnetworks, ANeuralNetworksDevice_getVersion);
   LOAD_FUNCTION_OPTIONAL(libneuralnetworks,
                          ANeuralNetworksDevice_getFeatureLevel);
+  LOAD_FUNCTION_OPTIONAL(libneuralnetworks, ANeuralNetworksDevice_getType);
   LOAD_FUNCTION_OPTIONAL(libneuralnetworks,
                          ANeuralNetworksModel_getSupportedOperationsForDevices);
   LOAD_FUNCTION_OPTIONAL(libneuralnetworks,

tensorflow/lite/nnapi/nnapi_implementation.h

@@ -694,6 +694,25 @@ struct NnApi {
   int (*ANeuralNetworksDevice_getFeatureLevel)(
       const ANeuralNetworksDevice* device, int64_t* featureLevel);
 
+  /**
+   * Get the type of a given device.
+   *
+   * The device type can be used to help application developers to distribute
+   * Machine Learning workloads and other workloads such as graphical rendering.
+   * E.g., for an app which renders AR scenes based on real time object
+   * detection results, the developer could choose an ACCELERATOR type device
+   * for ML workloads, and reserve GPU for graphical rendering.
+   *
+   * @param device The representation of the specified device.
+   * @param type The returned {@link DeviceTypeCode} of the specified device.
+   *
+   * @return ANEURALNETWORKS_NO_ERROR if successful.
+   *
+   * Available since API level 29.
+   */
+  int (*ANeuralNetworksDevice_getType)(const ANeuralNetworksDevice* device,
+                                       int32_t* type);
+
   /**
    * Get the supported operations for a specified set of devices. If multiple
    * devices are selected, the supported operation list is a union of supported