flutter_native_ml 1.1.0

Direct access to on-device ML accelerators (Apple Neural Engine / Core ML on iOS, LiteRT GPU delegate, NNAPI and XNNPACK on Android) for fast native inference.

1.1.0

Fixed

• Android did not compile. The Kotlin plugin imported com.google.ai.edge.litert.* classes that no Maven artifact provides. The plugin now depends on LiteRT (com.google.ai.edge.litert:litert / litert-gpu) and uses its org.tensorflow.lite Interpreter API.
• Android returned the tensor type under dtype while Dart expected dataType, which crashed getSignature().
• Android ran model loading and inference on the UI thread.
• Inference with the GPU delegate now always happens on the thread that created the delegate (a LiteRT requirement); every model has its own worker thread.
• iOS mutated shared state from a concurrent queue and returned some results off the main thread.
• iOS ignored the model's declared input shape and always built 1-D arrays.
• iOS/Android accepted only List<double> inputs; integer lists, typed lists and mixed num lists now work.
• startStream / stopStream were not implemented on Android and only emitted timestamps on iOS.
• dart run flutter_native_ml:ml_builder did not work (the CLI lived in a separate package). It now ships as bin/ml_builder.dart.
• Manifest package attribute removed (deprecated with AGP 8).

Added

• ComputeUnit.cpuAndGpu and ComputeUnit.cpuAndNeuralEngine (NNAPI on Android), with automatic CPU fallback. The compute unit actually used is reported in NativeMLModel.acceleratorUsed and InferenceResult.acceleratorUsed.
• loadModel(filePath: ...) for models stored on the device, numThreads and allowFp16 options.
• iOS: .mlmodel / .mlpackage assets are compiled on device and cached, so a single-file asset is enough (compiled .mlmodelc bundles are directories that Flutter does not bundle as one asset).
• iOS: image inputs/outputs (ImageInput, raw or PNG/JPEG), string, int64, double, dictionary and sequence features; float16 arrays.
• Android: all LiteRT tensor types (float32, int8/uint8/int16/int32/int64, bool, string), quantization parameters in the signature, SignatureDef aliases, dynamic shapes via TensorData(data, shape: [...]), native inference timing.
• Streaming API: model.startStream(), model.pushStreamInput(), model.stopStream() with a bounded native queue that drops stale frames.
• FlutterNativeML.getDeviceCapabilities(), getPlatformVersion(), disposeAll().
• NativeMLException with stable error codes instead of raw PlatformExceptions.
• Typed-list outputs (Float32List, Int32List, ...) plus InferenceResult.doubles(), ints(), argmax() and outputShapes.
• Swift Package Manager support alongside CocoaPods; privacy manifest bundled.
• Kotlin DSL build script compatible with Flutter's built-in Kotlin support.

Changed

• Minimum iOS version is 13.0; Android plugin targets Java 17 (as Flutter requires).
• ModelSignature/TensorInfo gained type, elementCount, hasDynamicShape, isOptional, quantization fields and metadata.
• The static FlutterNativeML.startStream/stopStream helpers are deprecated in favour of the NativeMLModel methods.

1.0.1

• Fixed bugs on android.

1.0.0

• Initial release.