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Copy file name to clipboardexpand all lines: README.md
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You need to have Python 3.8 or newer installed on your system. If you don't have
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Python installed, we recommend installing [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge).
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For the moment, no PyPI implementation is available. Falkon must be installed prior to installing Sobolev Alignment. The installation notice for Falkon is available on the [FalkonML documentation](https://falkonml.github.io/falkon/install.html).
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For the moment, no PyPI implementation is available (coming soon). The installation can be done in two steps.
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Once Falkon has been installed, the following command will automatically install sobolev_alignment, alongside the remaining dependencies (i.e., scvi-tools):
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### 1. Install Sobolev Alignment
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You can install Sobolev Alignment and (almost) all dependencies using the following command:
The resulting package is ready to use, but will use scikit-learn instead of Falkon, resulting in largely sub-optimal performances.
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### 2. Install Falkon
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To employ large-scale GPU-accelerated kernel methods, we turn to Falkon. The installation notice for Falkon is available on the [FalkonML documentation](https://falkonml.github.io/falkon/install.html). The previous installation procedure has already taken care of the various dependencies required for Falkon (i.e., cython, scipy and torch.)
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## Frequent issues
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Due to incompatibilities between g++, gcc and cuda, the installation of FalkonML sometimes fails. The following elements can help alleviate potential issues:
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- Prior to installing Falkon, re-install torch 1.11.
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- Check compatibility between your cuda version and the one installed with torch.
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- Using cxx-compiler=1.2.0 (available on conda-forge) is compatible with cuda 11.3.
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Please feel free to contact the development team by e-mail or by creating an issue.
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<!--
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1) Install the latest release of `sobolev_alignment` from `PyPI <https://pypi.org/project/sobolev_alignment/>`_:
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