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Diff for: README.md

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The results of scikit-learn asv benchmarks are automatically published every day on the following dashboard:
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https://scikit-learn.org/scikit-learn-benchmarks/
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### Major changes
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- May 22nd 2023: switch from conda default channel to conda-forge; upgrade Python version from 3.8 to latest. A consequence is that for these benchmarks Scikit-learn now uses OpenBLAS (previously MKL) which explains the discrpency in the timeline.

Diff for: run-benchmark.sh

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sudo apt-get install --assume-yes make
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# install Conda
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wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ${HOME}/miniconda.sh
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wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh -O ${HOME}/miniconda.sh
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bash ${HOME}/miniconda.sh -b -p ${HOME}/miniconda
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PATH=${HOME}/miniconda/bin:${PATH}
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# Create a conda env and install asv
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conda create -y -n skl_benchmark python=3.8
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conda create -y -n skl_benchmark python=* asv
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source ${HOME}/miniconda/etc/profile.d/conda.sh
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conda activate skl_benchmark
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pip install asv==0.5.1
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# Create the .asv-machine.json file.
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cat <<EOT >> ${HOME}/.asv-machine.json
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git add .
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git commit -m "new result [$COMMIT_TO_BENCH]"
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git push origin gh-pages
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