Tensorflow Lite Core ML Delegate

TensorFlow Lite Core ML Delegate enables running TensorFlow Lite models on Core ML framework, which results in faster model inference on iOS devices.

[TOC]

Supported iOS versions and processors

iOS 12 and later. In the older iOS versions, Core ML delegate will automatically fallback to CPU.
When running on iPhone Xs and later, it will use Neural Engine for faster inference.

Update code to use Core ML delegate

Swift

Initialize TensorFlow Lite interpreter with Core ML delegate.

swift

let coreMlDelegate = CoreMLDelegate()
let interpreter = try Interpreter(modelPath: modelPath,
                                  delegates: [coreMLDelegate])

Objective-C++

Interpreter initialization

Include coreml_delegate.h.

objectivec++

#include "tensorflow/lite/experimental/delegates/coreml/coreml_delegate.h"

Modify code following interpreter initialization to apply delegate.

objectivec++

// initializer interpreter with model.
tflite::InterpreterBuilder(*model, resolver)(&interpreter);

// Add following section to use Core ML delegate.
TfLiteCoreMlDelegateOptions options = {};
delegate = TfLiteCoreMlDelegateCreate(&options);
interpreter->ModifyGraphWithDelegate(delegate);

// Any calls to AllocateTensors must happen strictly AFTER all
// ModifyGraphWithDelegate calls.

// ...

Disposal

Add this code to the section where you dispose of the delegate (e.g. dealloc of class).

objectivec++

TfLiteCoreMlDelegateDelete(delegate);

Supported ops

Following ops are supported by the Core ML delegate.

Add
- Only certain shapes are broadcastable. In Core ML tensor layout, following tensor shapes are broadcastable. [B, C, H, W], [B, C, 1, 1], [B, 1, H, W], [B, 1, 1, 1].
AveragePool2D
Concat
Conv2D
- Weights and bias should be constant.
DepthwiseConv2D
- Weights and bias should be constant.
FullyConnected (aka Dense or InnerProduct)
- Weights and bias (if present) should be constant.
- Only supports single-batch case. Input dimensions should be 1, except the last dimension.
Hardswish
Logistic (aka Sigmoid)
MaxPool2D
MirrorPad
- Only 4D input with REFLECT mode is supported. Padding should be constant, and is only allowed for H and W dimensions.
Mul
- Only certain shapes are broadcastable. In Core ML tensor layout, following tensor shapes are broadcastable. [B, C, H, W], [B, C, 1, 1], [B, 1, H, W], [B, 1, 1, 1].
Pad and PadV2
- Only 4D input is supported. Padding should be constant, and is only allowed for H and W dimensions.
Relu
ReluN1To1
Relu6
Reshape
- Only supported when target Core ML version is 2, not supported when targeting Core ML 3.
ResizeBilinear
SoftMax
Tanh
TransposeConv
- Weights should be constant.

FAQ

Does Core ML delegate support fallback to CPU if a graph contains unsupported ops?
- Yes.
Does Core ML delegate work on iOS Simulator?
- Yes. The library includes x86 and x86_64 targets so it can run on a simulator, but you will not see performance boost over CPU.
Does TensorFlow Lite and Core ML delegate support macOS?
- TensorFlow Lite is only tested on iOS but not macOS.
Are custom TF Lite ops supported?
- No, CoreML delegate does not support custom ops and they will fallback to CPU.

Appendix

Core ML delegate Swift API

swift

/// A delegate that uses the `Core ML` framework for performing
/// TensorFlow Lite graph operations.
///
/// - Important: This is an experimental interface that is subject to change.
public final class CoreMLDelegate: Delegate {
 /// The configuration options for the `CoreMLDelegate`.
 public let options: Options

 // Conformance to the `Delegate` protocol.
 public private(set) var cDelegate: CDelegate

 * /// Creates a new instance configured with the given `options`.
 ///
 /// - Parameters:
 ///   - options: Configurations for the delegate. The default is a new instance of
 ///       `CoreMLDelegate.Options` with the default configuration values.
 public init(options: Options = Options()) {
   self.options = options
   var delegateOptions = TfLiteCoreMlDelegateOptions()
   cDelegate = TfLiteCoreMlDelegateCreate(&delegateOptions)
 }

 deinit {
   TfLiteCoreMlDelegateDelete(cDelegate)
 }
}

extension CoreMLDelegate {
 /// Options for configuring the `CoreMLDelegate`.
 public struct Options: Equatable, Hashable {
   /// Creates a new instance with the default values.
   public init() {}
 }
}

Core ML delegate C++ API

c++

typedef struct {
  // Only create delegate when Neural Engine is available on the device.
  TfLiteCoreMlDelegateEnabledDevices enabled_devices;
  // Specifies target Core ML version for model conversion.
  // Core ML 3 come with a lot more ops, but some ops (e.g. reshape) is not
  // delegated due to input rank constraint.
  // if not set to one of the valid versions, the delegate will use highest
  // version possible in the platform.
  // Valid versions: (2, 3)
  int coreml_version;
  // This sets the maximum number of Core ML delegates created.
  // Each graph corresponds to one delegated node subset in the
  // TFLite model. Set this to 0 to delegate all possible partitions.
  int max_delegated_partitions;
  // This sets the minimum number of nodes per partition delegated with
  // Core ML delegate. Defaults to 2.
  int min_nodes_per_partition;
#ifdef TFLITE_DEBUG_DELEGATE
  // This sets the index of the first node that could be delegated.
  int first_delegate_node_index;
  // This sets the index of the last node that could be delegated.
  int last_delegate_node_index;
#endif
} TfLiteCoreMlDelegateOptions;

// Return a delegate that uses CoreML for ops execution.
// Must outlive the interpreter.
TfLiteDelegate* TfLiteCoreMlDelegateCreate(
   const TfLiteCoreMlDelegateOptions* options);

// Do any needed cleanup and delete 'delegate'.
void TfLiteCoreMlDelegateDelete(TfLiteDelegate* delegate);