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| author | Guillaume Le Vaillant <glv@posteo.net> | 2020-06-07 10:40:48 +0200 |
|---|---|---|
| committer | Guillaume Le Vaillant <glv@posteo.net> | 2020-06-07 10:46:58 +0200 |
| commit | 5dc04da4dfa5330cd634f7a6dddc3fcdfe102f8a (patch) | |
| tree | ef1494bbc9cd4c5275ca20e52eec9e80f632d048 | |
| parent | 388a89750ec60a320dd7b6a0b0f174cbed4f50c6 (diff) | |
gnu: sbcl-cl-random-forest: Remove obsolete fix.
* gnu/packages/machine-learning.scm (sbcl-cl-random-forest)[arguments]: Remove
'add-sb-cltl2-dependency' phase.
| -rw-r--r-- | gnu/packages/machine-learning.scm | 15 |
1 files changed, 2 insertions, 13 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index e26768267b..4be165f390 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -11,7 +11,7 @@ ;;; Copyright © 2018 Julien Lepiller <julien@lepiller.eu> ;;; Copyright © 2018 Björn Höfling <bjoern.hoefling@bjoernhoefling.de> ;;; Copyright © 2019 Nicolas Goaziou <mail@nicolasgoaziou.fr> -;;; Copyright © 2019 Guillaume Le Vaillant <glv@posteo.net> +;;; Copyright © 2019, 2020 Guillaume Le Vaillant <glv@posteo.net> ;;; Copyright © 2019 Brett Gilio <brettg@gnu.org> ;;; Copyright © 2020 Konrad Hinsen <konrad.hinsen@fastmail.net> ;;; Copyright © 2020 Edouard Klein <edk@beaver-labs.com> @@ -2067,18 +2067,7 @@ online linear classification written in Common Lisp.") ("cl-online-learning" ,sbcl-cl-online-learning) ("lparallel" ,sbcl-lparallel))) (arguments - `(;; The tests download data from the Internet - #:tests? #f - #:phases - (modify-phases %standard-phases - (add-after 'unpack 'add-sb-cltl2-dependency - (lambda _ - ;; sb-cltl2 is required by lparallel when using sbcl, but it is - ;; not loaded automatically. - (substitute* "cl-random-forest.asd" - (("\\(in-package :cl-user\\)") - "(in-package :cl-user) #+sbcl (require :sb-cltl2)")) - #t))))) + `(#:tests? #f)) ; The tests download data from the Internet (synopsis "Random Forest and Global Refinement for Common Lisp") (description "CL-random-forest is an implementation of Random Forest for multiclass |