Wa_cq_url: "/content/www/us/en/docs/oneapi/installation-guide-linux/2023-0/install-intel-ai-analytics-toolkit-via-conda. Wa_audience: "emtaudience:business/btssbusinesstechnologysolutionspecialist/developer/softwaredeveloper", You can create your own Python distribution including the modules and dependencies you want, and bundle it in an APK or AAB along with your own code. Wa_english_title: "Install Intel® AI Analytics Toolkit via Conda*", Sphinx can be installed using Homebrew, MacPorts, or as part of a Python distribution such as Anaconda. python-for-android is a packaging tool for Python apps on Android. But if you want to connect to multiple modules at the same time, you need to run several instances of Thonny simultaneously. Wa_emt_org: "emtorganizationalstructure:satgsoftwareandadvancedtechnologygroup", Thonny can support a variety of different modules. Wa_curated: "curated:donotuseinexternalfilters/productdocumentation", Wa_emtoperatingsystem: "emtoperatingsystem:linux", Wa_emtorganizationalstructure: "emtorganizationalstructure:satgsoftwareandadvancedtechnologygroup", Wa_emttechnology: "emttechnology:inteltechnologies/oneapi", Wa_rsoftware: "rsoftware:inteloneapitoolkits/inteloneapibasetoolkit", Thonny is available for download on Windows, Mac, and Linux distros, and offers a solid experience across all three OSes. We suggest two methods: users can install their own version of Python with Anaconda. Wa_emtprogramminglanguage: "emtprogramminglanguage:cc/dataparallelcdpc", We have received many questions about using Python on the HPCC system. Wa_emtcontenttype: "emtcontenttype:designanddevelopmentreference/developerguide/developergettingstartedguide,emtcontenttype:designanddevelopmentreference/developerguide/installationguides", For example, to activate the python environment created in the previous step, use: conda activate aikit-tf 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 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. To instal the AI Kit via Conda, complete the following steps:Īctivate your existing python conda environment located in : source /bin/activate 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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