--- Begin Message ---
|
Subject: |
[PATCH] gnu: Add python-autograd |
|
Date: |
Sat, 28 Apr 2018 03:47:03 +0000 |
* gnu/packages/machine-learning.scm (python-autograd, python2-autograd): New
variables.
---
gnu/packages/machine-learning.scm | 44 +++++++++++++++++++++++++++++++++++++++
1 file changed, 44 insertions(+)
diff --git a/gnu/packages/machine-learning.scm
b/gnu/packages/machine-learning.scm
index 12384a103..e2b113a70 100644
--- a/gnu/packages/machine-learning.scm
+++ b/gnu/packages/machine-learning.scm
@@ -6,6 +6,7 @@
;;; Copyright © 2018 Tobias Geerinckx-Rice <address@hidden>
;;; Copyright © 2018 Mark Meyer <address@hidden>
;;; Copyright © 2018 Ben Woodcroft <address@hidden>
+;;; Copyright © 2018 Fis Trivial <address@hidden>
;;;
;;; This file is part of GNU Guix.
;;;
@@ -688,3 +689,46 @@ mining and data analysis.")
(define-public python2-scikit-learn
(package-with-python2 python-scikit-learn))
+
+(define-public python-autograd
+ (let* ((commit "442205dfefe407beffb33550846434baa90c4de7")
+ (revision "0")
+ (version (git-version "0.0.0" revision commit)))
+ (package
+ (name "python-autograd")
+ (home-page "https://github.com/HIPS/autograd";)
+ (source (origin
+ (method git-fetch)
+ (uri (git-reference
+ (url home-page)
+ (commit commit)))
+ (sha256
+ (base32
+ "189sv2xb0mwnjawa9z7mrgdglc1miaq93pnck26r28fi1jdwg0z4"))
+ (file-name (git-file-name name version))))
+ (version version)
+ (build-system python-build-system)
+ (native-inputs
+ `(("python-nose" ,python-nose)
+ ("python-pytest" ,python-pytest)))
+ (propagated-inputs
+ `(("python-future" ,python-future)
+ ("python-numpy" ,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
+, ifs, recursion and closures, and it can even take derivatives of derivatives
+of derivatives. It supports reverse-mode differentiation
+(a.k.a. backpropagation), which means it can efficiently take gradients of
+scalar-valued functions with respect to array-valued arguments, as well as
+forward-mode differentiation, and the two can be composed arbitrarily. The
+main intended application of Autograd is gradient-based optimization.")
+ (license license:expat))))
+
+(define-public python2-autograd
+ (package-with-python2 python-autograd))
--
2.14.3
--- End Message ---
--- Begin Message ---
|
Subject: |
Re: [bug#31293] [PATCH] gnu: Add python-autograd |
|
Date: |
Sat, 28 Apr 2018 23:33:20 +0200 |
|
User-agent: |
Gnus/5.13 (Gnus v5.13) Emacs/25.3 (gnu/linux) |
Fis Trivial <address@hidden> skribis:
> * gnu/packages/machine-learning.scm (python-autograd, python2-autograd): New
> variables.
Applied with the changes below. Thank you!
Ludo’.
diff --git a/gnu/packages/machine-learning.scm
b/gnu/packages/machine-learning.scm
index e2b113a70..d3af35e17 100644
--- a/gnu/packages/machine-learning.scm
+++ b/gnu/packages/machine-learning.scm
@@ -719,10 +719,10 @@ mining and data analysis.")
(replace 'check
(lambda _
(invoke "py.test" "-v"))))))
- (synopsis "Efficiently computes derivatives of numpy code")
+ (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
-, ifs, recursion and closures, and it can even take derivatives of derivatives
+NumPy code. It can handle a large subset of Python's features, including
loops,
+ifs, recursion and closures, and it can even take derivatives of derivatives
of derivatives. It supports reverse-mode differentiation
(a.k.a. backpropagation), which means it can efficiently take gradients of
scalar-valued functions with respect to array-valued arguments, as well as
--- End Message ---