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      1 # TensorFlow Lite 2019 Roadmap
      2 
      3 **Updated: March 6th, 2019**
      4 
      5 The following represents a high level overview of our 2019 plan. You should be
      6 conscious that this roadmap may change at anytime relative to a range of factors
      7 and the order below does not reflect any type of priority. As a matter of
      8 principle, we typically prioritize issues that the majority of our users are
      9 asking for and so this list fundamentally reflects that.
     10 
     11 We break our roadmap into four key segments: usability, performance,
     12 optimization and portability. We strongly encourage you to comment on our
     13 roadmap and provide us feedback in the TF Lite discussion groups and forums.
     14 
     15 ## Usability
     16 
     17 *   **More ops coverage**
     18     *   Prioritize many more ops based on user feedback
     19 *   **Op versioning & signatures**
     20     *   Op kernels will get version numbers
     21     *   Op kernels will be identifiable by signature
     22 *   **New Convertor**
     23     *   Implementing a new TensorFlow Lite convertor that will better handle
     24         graph conversion (i.e. control flow, conditionals etc) and replace TOCO
     25 *   **Continue to improve TF Select Ops**
     26     *   Support more types of conversion utilizing TF Selects such as hash
     27         tables, strings etc.
     28     *   Support smaller binary size when using select TF ops via op stripping
     29 *   **LSTM / RNN support**
     30     *   Add full support of conversion for LSTMs and RNNs
     31 *   **Graph Visualization Tooling**
     32     *   Provide enhanced graph visualization tooling
     33 *   **Pre-and-post processing support**
     34     *   Add more support for pre-and-post processing of inference
     35 *   **Control Flow & Training on-device**
     36     *   Add support for control flow related ops
     37     *   Add support for training on-device
     38 *   **New APIs**
     39     *   New C API as core for language bindings and most clients
     40     *   Objective-C API for iOS
     41     *   SWIFT API for iOS
     42     *   Updated Java API for Android
     43     *   C# Unity language bindings
     44 *   **Add more Models**
     45     *   Add more models to the support section of the site
     46 
     47 ## Performance
     48 
     49 *   **More hardware delegates**
     50     *   Add support for more hardware delegates
     51 *   **Support NN API**
     52     *   Continually support and improve support for NN API
     53 *   **Framework Extensibility**
     54     *   Enable simplistic overwriting of CPU kernels with customized optimized
     55         versions
     56 *   **GPU Delegate**
     57     *   Continue to extend the total support ops for OpenGL and Metal ops
     58     *   Open-source
     59 *   **Improve TFLite CPU performance**
     60     *   Optimizations for float and quantized models
     61 
     62 ## Optimization
     63 
     64 *   **Model Optimization Toolkit**
     65     *   Post training quantization + hybrid kernels
     66     *   Post Training quantization + fixed-point kernels
     67     *   Training with quantization
     68 *   **More support for more techniques**
     69     *   RNN Support
     70     *   Sparsity/Pruning
     71     *   Lower bit-width support
     72 
     73 ## Portability
     74 
     75 *   **Microcontroller Support**
     76     *   Add support for a range of 8-bit, 16-bit and 32-bit MCU architecture use
     77         cases for Speech and Image Classification
     78