Interpreter API (Java) - GpuDelegateV2 support
Hi @cfasana,

The Java Interpreter API currently doesn't have GpuDelegateV2 directly. However if you would like to achieve the faster inference speed you can use `GpuDelegate`  class by setting the `isPrecisionLossAllowed` flag to `true` in the following way as a workaround. But for memory usage and max precision, feature requests will be raised. Thanks for letting us know.
```
GpuDelegateOptions options = new GpuDelegateOptions();
options.isPrecisionLossAllowed = true;  
GpuDelegate gpuDelegate = new GpuDelegate(options);
InterpreterOptions interpreterOptions = new InterpreterOptions();
interpreterOptions.addDelegate(gpuDelegate);
Interpreter interpreter = new Interpreter(modelBuffer, interpreterOptions);
```
or 
Also try with tflite_flutter library which will provide access to GpuDelegateV2 through DART API.

Hi @pkgoogle,
As @cfasana mentioned,  `GpuDelegateV2` need to be included in Java Interpreter API with the support of  ```(TFLITE_GPU_INFERENCE_PRIORITY_MIN_LATENCY, TFLITE_GPU_INFERENCE_PRIORITY_MIN_MEMORY_USAGE, TFLITE_GPU_INFERENCE_PRIORITY_MAX_PRECISION)```. Raised a feature request.

Thank You Hi @LakshmiKalaKadali,
thanks for the feedback.
I will proceed as you suggested while awaiting the Java Interpreter API update. Hi @sirakiin, can you please take a look a this feature request? Thanks.
Hi,
I am trying to run a TFLite model on the GPU of an Android device.
According to this [documentation](https://www.tensorflow.org/lite/android/delegates/gpu), it is possible to use both the `Interpreter API` and the `Native c++ API` to achieve this.

At the moment, I am using the following dependencies:
```
implementation 'org.tensorflow:tensorflow-lite:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-select-tf-ops:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-support:0.4.4'
implementation 'org.tensorflow:tensorflow-lite-gpu:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-gpu-api:2.15.0'
implementation 'org.tensorflow:tensorflow-lite-gpu-delegate-plugin:0.4.4'
```

I was able to successfully run my model using the `GPUDelegate` provided by the Java Interpreter API. However, this delegate does not allow to specify inference priority options (`TFLITE_GPU_INFERENCE_PRIORITY_MIN_LATENCY`, `TFLITE_GPU_INFERENCE_PRIORITY_MIN_MEMORY_USAGE`, `TFLITE_GPU_INFERENCE_PRIORITY_MAX_PRECISION`).

These options can be specified if the Native C++ API is used given the presence of GpuDelegateV2. However, at the moment I don't see this option in the Interpreter API since there is no class named `GpuDelegateV2`.

Is there a way to make use of this new delegate without the need of using the Native C++ API?