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| author | Vinicius Monego <monego@posteo.net> | 2023-05-21 15:08:40 -0300 |
|---|---|---|
| committer | Vinicius Monego <monego@posteo.net> | 2023-07-29 14:25:10 -0300 |
| commit | 6b28b9a0201f0d06ecab6414be2ed6bfa2642fc3 (patch) | |
| tree | 6b3aa0181a4912a8a13f19f4e807f613c4ab28d9 /gnu/packages/machine-learning.scm | |
| parent | c03b65fc7fafc460e9c0cead21e293c13249c253 (diff) | |
gnu: Add python-deepxde.
* gnu/packages/machine-learning.scm (python-deepxde): New variable.
Diffstat (limited to 'gnu/packages/machine-learning.scm')
| -rw-r--r-- | gnu/packages/machine-learning.scm | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index 897bf9f82a..3923573d57 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -1995,6 +1995,39 @@ optimization over awkward search spaces, which may include real-valued, discrete, and conditional dimensions.") (license license:bsd-3))) +(define-public python-deepxde + (package + (name "python-deepxde") + (version "1.9.2") + (source (origin + (method url-fetch) + (uri (pypi-uri "DeepXDE" version)) + (sha256 + (base32 + "07bz3d7d698l0fhznw5l8p16b22d4ly7xq99vrgv48c722qr2r5b")))) + (build-system pyproject-build-system) + (arguments + (list #:tests? #f ; there are no tests + #:phases #~(modify-phases %standard-phases + (add-before 'sanity-check 'writable-home + ;; sanity-check writes ~/.deepxde/config.json to set + ;; the default backend. + (lambda _ + (setenv "HOME" "/tmp")))))) + ;; DeepXDE supported backends are TensorFlow (v1 and v2), PyTorch, JAX and + ;; PaddlePaddle. We test with PyTorch because we have it up to date. + (native-inputs (list python-pytorch python-setuptools-scm)) + (propagated-inputs (list python-matplotlib python-numpy + python-scikit-learn python-scikit-optimize + python-scipy)) + (home-page "https://deepxde.readthedocs.io/en/latest/") + (synopsis "Library for scientific machine learning") + (description "DeepXDE is a library for scientific machine learning and +physics-informed learning. It includes implementations for the PINN +(physics-informed neural networks), DeepONet (deep operator network) and +MFNN (multifidelity neural network) algorithms.") + (license license:lgpl2.1+))) + ;; There have been no proper releases yet. (define-public kaldi (let ((commit "be22248e3a166d9ec52c78dac945f471e7c3a8aa") |