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PyKeOps: Difference between revisions
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The [https://www.kernel-operations.io/keops/index.html KeOps] library lets you compute reductions of large arrays whose entries are given by a mathematical formula or a neural network. It combines efficient C++ routines with an automatic differentiation engine and can be used with [[Python]] (NumPy, [[PyTorch]]), [[MATLAB]] and [[R]]. | The [https://www.kernel-operations.io/keops/index.html KeOps] library lets you compute reductions of large arrays whose entries are given by a mathematical formula or a neural network. It combines efficient C++ routines with an automatic differentiation engine and can be used with [[Python]] (NumPy, [[PyTorch]]), [[MATLAB]] and [[R]]. | ||
= Available versions = | = Available versions = <!--T:2--> | ||
PyKeOps is available on our clusters as prebuilt Python packages (wheels). You can list available versions with <code>avail_wheels</code>. | PyKeOps is available on our clusters as prebuilt Python packages (wheels). You can list available versions with <code>avail_wheels</code>. | ||
{{Command | {{Command | ||
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}} | }} | ||
= Installing PyKeOps in a [[Python#Creating_and_using_a_virtual_environment | Python virtual environment]] = | = Installing PyKeOps in a [[Python#Creating_and_using_a_virtual_environment | Python virtual environment]] = <!--T:3--> | ||
1. Load runtime dependencies. | 1. Load runtime dependencies. | ||
{{Command|module load StdEnv/2023 python/3.11}} | {{Command|module load StdEnv/2023 python/3.11}} | ||
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}} | }} | ||
= Running KeOps = | = Running KeOps = <!--T:9--> | ||
You can run PyKeOps on CPU or GPU. | You can run PyKeOps on CPU or GPU. | ||
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You can do a quick test in an [[Running_jobs#Interactive_jobs|interactive job]]. | You can do a quick test in an [[Running_jobs#Interactive_jobs|interactive job]]. | ||
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3. Submit your job to the scheduler. | 3. Submit your job to the scheduler. | ||
{{Command | {{Command | ||