Furiosa SDK

Furiosa™ SDK is a software development kit (SDK) for running deep-neural network inference using FuriosaAI NPU chips. It is a collection of libraries and command line tools including compiler and profiler. It also provides Python bindings that allow users to develop their application easily with abundant Python ecosystem, such as NumPy, Jupyter notebooks and scientific Python packages.

Documentation

Installation

You can install Furiosa SDK with pip.

pip install furiosa-sdk

You can install also furiosa-sdk with extra packages (e.g., litmus, quantizer):

pip install 'furiosa-sdk[litmus,quantizer]'

The following are the extra packages:

litmus: Command line tool to check if a model is compatible with furiosa-sdk
models: Library which provides pretained models for Furiosa NPU
quantizer: Library which quantizes and optimizes DNN models
server: Serving framework enabling a DNN model to provide HTTP/GRPC endpoints
serving: FastAPI-based Serving Library

Releases

License

Copyright 2023 FuriosaAI, Inc.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Release files for furiosa-sdk 0.10.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for furiosa-sdk 0.10.2
File	Interpreter	ABI	Platform	Reset
furiosa_sdk-0.10.2-py3-none-any.whl 2.6 kB May 29, 2024	Python 3	none	any	Details

Release files / furiosa_sdk-0.10.2-py3-none-any.whl

Download URL	furiosa_sdk-0.10.2-py3-none-any.whl
Size	2.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`677a758720cadf99320894f52c34c4406a8dfd33e272342dc423210ad5587633`
BLAKE2b-256 checksum How to use checksums	`bb26cfaf7fbd3b2e241769ccd1fdc0ed3568485622f5d990acab91a8dba2ce59`
Upload date	May 29, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.0 CPython/3.9.19`