The preferred way to install this package is by using the Python package index:
pip install aihwkit
During the initial beta stage, we do not provide pip wheels (as in, pre-compiled binaries) for all the possible platform, version and architecture combinations (in particular, only CPU versions are provided).
Please refer to the Advanced installation guide page for instruction on how to compile the library for your environment in case you encounter errors during installing from pip.
The package require the following runtime libraries to be installed in your system:
Please note that the current pip wheels are only compatible with
1.6.0. If you need to use a different
PyTorch version, please
refer to the Advanced installation guide section in order to compile a custom
version. More details about the
PyTorch compatibility can be found in
The package contains optional functionality that is not installed as part of
the default installed. In order to install the extra dependencies, the
recommended way is by specifying the extra
pip install aihwkit[visualization]
Verifying the installation¶
If the library was installed correctly, you can use the following snippet for creating an analog layer and predicting the output:
from torch import Tensor from aihwkit.nn import AnalogLinear model = AnalogLinear(2, 2) model(Tensor([[0.1, 0.2], [0.3, 0.4]]))
If you encounter any issues during the installation or executing the snippet, please refer to the Advanced installation guide section for more details and don’t hesitate on using the issue tracker for additional support.