Tflite-support

Major features

+ Task
- ODML Image support in Java
- C headers in AAR
- Acceleration support in Java and C++ API
- Audio Embedder in C++ API
+ Support
- ODML Image proxy support in Java
+ Metadata
- Generic metadata writer

Fixes

+ Task
- No extra TFLite runtime in dependency tree (binary size decreased)
+ Support
- No TFLite runtime dependency

This release only targets on fixing a `ByteBuffer` incompatibility issue in the TFLite Metadata Java library. The updated metadata library can be found on Maven Central Repository.

Fixes

- On some devices, using TFLite Metadata library throws `NoSuchMethodError` at runtime. The error message looks like: "java.lang.NoSuchMethodError: No virtual method position(I)Ljava/nio/ByteBuffer; in class Ljava/nio/ByteBuffer; or its super classes"

Release changes

+ Java / Android artifacts are now pushed to Maven Central and Sonatype OSSRH Snapshot
+ Python artifacts now support Python 3.9

Major Features

Task Library

+ Add a new task: Audio classification in a new prebuilt artifact (maven: `org.tensorflow:tensorflow-lite-task-audio`)
+ Support YUV image and Android `media.Image` as inputs in vision Tasks
+ Support configuring max_seq_length in BertNLClassifier

Support Library

+ Support YUV, grayscale and Android media.Image in `TensorImage`
+ Add Audio data supports: `TensorAudio` and `AudioBuffer`

Metadata

+ Add Metadata Writers for common tasks in the pip package

Fixes

Task

+ Fix a JNI local ref overflow issue on lower version Android devices
+ Fix a memory leak issue in NL Classification

Metadata

+ Prevent using Flatbuffers 2.0 which is not compatible with TFLite Support

Codegen

+ Fix a class name generation error

Major features

It's the first release of the TFLite Support toolkit. We provides the following components:

- [TFLite Task Library](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview) (source, JCenter): enables integrating popular ML use cases in a few lines of code.
+ Image Classifier
+ Object Detector
+ Image Segmenter
+ NL Classifier
+ Bert NL Classifier
+ Bert Question Answerer
- [TFLite Support Library](https://www.tensorflow.org/lite/inference_with_metadata/lite_support) (source, JCenter): simplifies pre-processing/post-processing code for models.
+ Utilities for image pre/post processing
- [TFLite Metadata Library](https://www.tensorflow.org/lite/convert/metadata) (source, PyPI, JCenter, MavenCentral): reads and writes TFLite Metadata in models.
+ Utilities for extracting and populating TFLite Metadata
- [TFLite Support Codegen](https://www.tensorflow.org/lite/inference_with_metadata/codegen) (source, PyPI): generates model wrapper automatically based on Metadata.
- [TFLite Custom Ops](https://github.com/tensorflow/tflite-support/tree/master/tensorflow_lite_support/custom_ops) (source): helps deploying cutting-edge models on devices.

Compatibility

Verified TF version

The final RC for the formal release 0.1.0.