After the toolkit is installed, before accessing the tools, you must activate your python environment and set up environment variables to access the tools. You can also create an AI Kit Modin and machine learning environment named aikit-modin: conda create -n aikit-modin -c intel intel-aikit-modin Similarly, you can create an AI Kit PyTorch environment named aikit-pt: conda create -n aikit-pt -c intel intel-aikit-pytorch If the repository contains the desired version, create an AI Kit Tensorflow* environment named aikit-tf with this version: conda create -n aikit-tf -c intel intel-aikit-tensorflow On the Anaconda download page you can choose between Anaconda with Python 3.x or Python 2.x, however this only affects the root conda environment, which we will. If the specific package you are looking for is available from (formerlly ), you can easily install it and required dependencies by using. If the repo contains an outdated version of a required component, get a newer one by installing via the command line or GUI. Not all packages in the Anaconda repository are up to date with the current release. A list of available packages is located at. Install the AI Kit oneAPI packages in a new environment using conda create. The Definitive Guide to AI Platforms for Open-Source Data Science and ML. Free Download Contact Sales Resource Center. We are a movement of data scientists, data-driven enterprises, and open source communities. THis is the default for Linux users, but also works in the Windows Subsystem for. To instal the AI Kit via Conda, complete the following steps:Īctivate your existing python conda environment located in : source /bin/activate Anaconda is the birthplace of Python data science. To get a more lightweight version, consider installing it via the command line. To get the latest version of the Intel(R) Optimization for TensorFlow*, you must first install Python 3.9, then install the AI Kit through Anaconda.
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