*********************************************************
Release Notes - 0.6.0
*********************************************************

FuriosaAI SDK 0.6.0 is a major release. 
It includes 234 PRs on performance improvements, added functionalities, and bug fixes, 
as well as approximately 900 commits. 

How to upgrade
--------------------------------------------------------
If you are using the APT repositories, you easily upgrade with the instructions below:
More detailed instructions can be found at :ref:`RequiredPackages`.

  .. code-block:: sh

    apt-get update && \
    apt-get install furiosa-driver-pdma furiosa-libnpu-warboy furiosa-libnux

    pip uninstall furiosa-sdk-quantizer furiosa-sdk-runtime furiosa-sdk-validator && \
    pip install --upgrade furiosa-sdk


Major changes 
--------------------------------------------------------
The kernel driver (furiosa-driver-pdma) has been upgraded to 1.2.2, and the user-level driver (furiosa-libnpu-warboy) 
has been upgraded to 0.5.2, thereby providing more stable and higher NPU performance. Other major changes include the following: 

Compiler 
================================================================
* Addition of NPU accelerated operators (see :ref:`SupportedOperators` for full list of accelerated operators)

    * Space-to-depth (CRD mode)
    * Transpose
    * Slice (height axis only)
    * Concat (height axis only)
    * Grouped Convolution (if groups <= 128)

* Improvements to significantly reduce frequency of CPU tasks in models with 
  operators that require large memory usage (reduced execution time)

Quantizer
================================================================

* Improve model quantization process to ensure idempotency 
* Remove PyTorch reliance 
* Improve code quality by removing multiple Pylint warnings
* Upgrade multiple library dependencies (e.g. Numpy -> 1.21.5, Pyyaml -> 6.0.0)

Python SDK
================================================================

* Python SDK project structure change 

  * furiosa-sdk-runtime -> furiosa-sdk
  * furiosa-sdk-quantizer -> furiosa-quantizer
  * furiosa-sdk-validator -> furiosa-litmus

* Validator, a package that checks for model compatibility with Furiosa SDK, is renamed to litmus. Installation instruction has also been updated accordingly. 

See :ref:`Litmus` for more detailed usage instructions.

  .. code-block:: sh

    $ pip install 'furiosa-sdk[litmus]'

Furiosa Serving: Addition of FastAPI-based advanced serving library 
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
furiosa-serving is based on FastAPI. It allows you to easily add Python-based business logic or image pre/postprocessing code, 
before or after executing model inference API.  

You can install using the following instructions. 

  .. code-block:: sh

    $ pip install 'furiosa-sdk[serving]'


The usage example is shown below. You can find more detailed instructions at  
`furiosa-serving Github <https://github.com/furiosa-ai/furiosa-sdk/tree/main/python/furiosa-serving>`_.

  .. code-block:: python

    from typing import Dict

    from fastapi import File, UploadFile
    from furiosa.server.utils.thread import synchronous
    from furiosa.serving import ServeAPI, ServeModel
    import numpy as np


    serve = ServeAPI()


    model: ServeModel = synchronous(serve.model)(
        'imagenet',
        location='./examples/assets/models/image_classification.onnx'
    )

    @model.post("/models/imagenet/infer")
    async def infer(image: UploadFile = File(...)) -> Dict:
        # Convert image to Numpy array with your preprocess() function
        tensors: List[np.ndarray] = preprocess(image)

        # Infer from ServeModel
        result: List[np.ndarray] = await model.predict(tensors)

        # Classify model from numpy array with your postprocess() function
        response: Dict = postprocess(result)

        return response