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| author | Felix Gruber <felgru@posteo.net> | 2023-11-04 15:07:10 +0000 |
|---|---|---|
| committer | Ludovic Courtès <ludo@gnu.org> | 2023-12-06 23:50:04 +0100 |
| commit | 0399d5b6101522901b69b985010736505fdf9354 (patch) | |
| tree | 9e2abe8a188c34fc27b43bb74d4cf49cc6d4d827 | |
| parent | 8da64e88108bf8620a3da20f028059fda438754d (diff) | |
| download | guix-0399d5b6101522901b69b985010736505fdf9354.tar.gz | |
gnu: python-autograd: Update to 1.5.
* gnu/packages/machine-learning.scm (python-autograd): Update to 1.5. [build-system]: Use pyproject-build-system. [arguments]: Remove custom 'check phase. Change-Id: Ic76510b94d268d5dba6e9b0e057fcfca125e424f Signed-off-by: Ludovic Courtès <ludo@gnu.org>
| -rw-r--r-- | gnu/packages/machine-learning.scm | 13 |
1 files changed, 4 insertions, 9 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index 38e586232b..c100e0be6e 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -1968,9 +1968,9 @@ Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for Python.") (license license:expat))) (define-public python-autograd - (let* ((commit "442205dfefe407beffb33550846434baa90c4de7") + (let* ((commit "c6d81ce7eede6db801d4e9a92b27ec5d409d0eab") (revision "0") - (version (git-version "0.0.0" revision commit))) + (version (git-version "1.5" revision commit))) (package (name "python-autograd") (home-page "https://github.com/HIPS/autograd") @@ -1981,19 +1981,14 @@ Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for Python.") (commit commit))) (sha256 (base32 - "189sv2xb0mwnjawa9z7mrgdglc1miaq93pnck26r28fi1jdwg0z4")) + "04kljgydng42xlg044h6nbzxpban1ivd6jzb8ydkngfq88ppipfk")) (file-name (git-file-name name version)))) (version version) - (build-system python-build-system) + (build-system pyproject-build-system) (native-inputs (list python-nose python-pytest)) (propagated-inputs (list python-future python-numpy)) - (arguments - `(#:phases (modify-phases %standard-phases - (replace 'check - (lambda _ - (invoke "py.test" "-v")))))) (synopsis "Efficiently computes derivatives of NumPy code") (description "Autograd can automatically differentiate native Python and NumPy code. It can handle a large subset of Python's features, including loops, |