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named aikit-tf with this version: conda create -n aikit-tf -c intel intel-aikit-tensorflow If the repo contains an outdated version of a required component, get a newer one by installing via the command line or GUI. but you will not yet be able to use modules like NumPy, PyPlot, or SciPy. Not all packages in the Anaconda repository are up to date with the current release. To install Anaconda from the command line, first, download Miniconda. If you don't want to learn how to deal with this mess, the simplest thing to do is to always use python -m pip in place of pip. A list of available packages is located at. 1 Most likely you have (at least) two separate copies of Python installed on your system, and python runs one, but pip is for the other on. Install the AI Kit oneAPI packages in a new environment using conda create. Click the button below to download the suggested installer for your platform. for Anaconda on Windows, see Anaconda Windows Batch File section below. To instal the AI Kit via Conda, complete the following steps:Īctivate your existing python conda environment located in : source /bin/activate pip install numpy pip install matplotlib OR perhaps. 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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