Metal Tensorflow Lite Interpreter

MetalTFLiteInterpreter is an Objective-C class designed to run TensorFlow Lite models using Metal for accelerated GPU execution.

Key Features

• TensorFlow Lite Support: Allows using models exported in TensorFlow Lite.
• Hardware Acceleration: Uses the Metal delegate to execute the model on a GPU.
• Easy Integration: Effortlessly binds input and output buffers.

Requirements

• Xcode 12.5+ (to support Metal)
• TensorFlow Lite C API
• macOS or iOS with Metal support

Installation

1. CocoaPods (Recommended): Add the TensorFlow Lite C API to your project via CocoaPods. In the Podfile, add the following configuration:

   pod 'TensorFlowLiteC', :subspecs => ['Metal']

   Then, run:

   pod install

2. Cloning: Clone the repository with the code or copy the necessary files to your project.

3. Dependency Configuration: Make sure that TensorFlow Lite and TensorFlowLiteCMetal are correctly added to your project.

Usage

1. Initialization: Create an instance of MetalTFLiteInterpreter, specifying the path to your model:

NSString *modelPath = @"path/to/your/model.tflite";
MetalTFLiteInterpreter *interpreter = [[MetalTFLiteInterpreter alloc] initWithFilePath:modelPath];

2. Buffer Binding: Bind an MTLBuffer to an input or output tensor by specifying the index:

BOOL success = [interpreter bindMetalBuffer:yourMTLBuffer toTensor:INPUT index:0];
if (!success) {
    NSLog(@"Failed to bind Metal buffer.");
}

3. Invoke Model: Call invoke to execute the model:

BOOL invocationSuccess = [interpreter invoke];
if (!invocationSuccess) {
    NSLog(@"Failed to invoke interpreter.");
}

4. Access Results: Access results through the output buffer:

void *outputBuffer = [interpreter bufferPointerForOutputTensor:0];
size_t outputSize = [interpreter bufferSizeForOutputTensor:0];

License

This project is licensed under the Apache License, Version 2.0.