Nano Installation#

You can select bigdl-nano along with some dependencies specific to PyTorch or Tensorflow using the following panel.

FrameWork
Version
Inference Opt
Release
Install CMD	NA

Note

Since bigdl-nano is still in the process of rapid iteration, we highly recommend that you install nightly build version through the above command to facilitate your use of the latest features.

For stable version, please refer to the document and installation guide here .

Environment Management#

Install in conda environment (Recommended)#

conda create -n env
conda activate env

# select your preference in above panel to find the proper command to replace the below command, e.g.
pip install --pre --upgrade bigdl-nano[pytorch]

# after installing bigdl-nano, you can run the following command to setup a few environment variables.
source bigdl-nano-init

The bigdl-nano-init scripts will export a few environment variable according to your hardware to maximize performance.

In a conda environment, when you run source bigdl-nano-init manually, this command will also be added to $CONDA_PREFIX/etc/conda/activate.d/, which will automaticly run when you activate your current environment.

Install in pure pip environment#

In a pure pip environment, you need to run source bigdl-nano-init every time you open a new shell to get optimal performance and run source bigdl-nano-unset-env if you want to unset these environment variables.

Other PyTorch/Tensorflow Version Support#

We support a wide range of PyTorch and Tensorflow. We only care the MAJOR.MINOR in Semantic Versioning. If you have a specific PyTorch/Tensorflow version want to use, e.g. PyTorch 1.11.0+cpu, you may select corresponding MAJOR.MINOR (i.e., PyTorch 1.11 in this case) and install PyTorch again after installing nano.

Python Version#

bigdl-nano is validated on Python 3.8-3.10.

Operating System#

Some specific note should be awared of when installing bigdl-nano.`

Install on Linux#

For Linux, Ubuntu (22.04/20.04) is recommended.

Install on Windows (experimental support)#

For Windows OS, users could only run bigdl-nano-init every time they open a new cmd terminal.

We recommend using Windows Subsystem for Linux 2 (WSL2) to run BigDL-Nano. Please refer to Nano Windows install guide for instructions.

Install on MacOS (experimental support)#

MacOS with Intel Chip#

Same usage as Linux, while some of the funcions now rely on lower version dependencies.

MacOS with M-series chip#

Currently, only tensorflow is supported for M-series chip Mac.

# any way to install tensorflow on macos

pip install --pre --upgrade bigdl-nano[tensorflow]