TFlite doesn’t build with Opencl GPU on Macosx 2 and generally the standard TF runtime is better on desktop.
If you still need to use TFLite for testing you could try with the CPU XNNPACK delegate:

  
      

      TensorFlow
  

  
    

Interpreter.Options  |  TensorFlow Lite 5



  

  
    
    
  

  


Edit:
See more at

  

      github.com
  

  
    tensorflow/tensorflow/blob/master/tensorflow/lite/delegates/xnnpack/README.md 8


    # XNNPACK backend for TensorFlow Lite

XNNPACK is a highly optimized library of neural network inference operators for
ARM, x86, and WebAssembly architectures in Android, iOS, Windows, Linux, macOS,
and Emscripten environments. This document describes how to use the XNNPACK
library as an inference engine for TensorFlow Lite.

## Using XNNPACK engine with TensorFlow Lite interpreter

XNNPACK integrates with TensorFlow Lite interpreter through the delegation
mechanism. TensorFlow Lite supports several methods to enable XNNPACK
for floating-point inference.

### Enable XNNPACK via Java API on Android (recommended on Android)

Pre-built [nightly TensorFlow Lite binaries for Android](https://www.tensorflow.org/lite/guide/android#use_the_tensorflow_lite_aar_from_mavencentral)
include XNNPACK, albeit it is disabled by default. Use the `setUseXNNPACK`
method in `Interpreter.Options` class to enable it:

```java



  This file has been truncated. show original