diff options
Diffstat (limited to 'gnu/packages/machine-learning.scm')
| -rw-r--r-- | gnu/packages/machine-learning.scm | 168 |
1 files changed, 165 insertions, 3 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index 67ea736284..ba7772f66b 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -10,6 +10,7 @@ ;;; Copyright © 2018 Fis Trivial <ybbs.daans@hotmail.com> ;;; Copyright © 2018 Julien Lepiller <julien@lepiller.eu> ;;; Copyright © 2018 Björn Höfling <bjoern.hoefling@bjoernhoefling.de> +;;; Copyright © 2019 Nicolas Goaziou <mail@nicolasgoaziou.fr> ;;; ;;; This file is part of GNU Guix. ;;; @@ -53,6 +54,7 @@ #:use-module (gnu packages dejagnu) #:use-module (gnu packages gcc) #:use-module (gnu packages glib) + #:use-module (gnu packages graphviz) #:use-module (gnu packages gstreamer) #:use-module (gnu packages image) #:use-module (gnu packages linux) @@ -67,6 +69,7 @@ #:use-module (gnu packages python-web) #:use-module (gnu packages python-xyz) #:use-module (gnu packages serialization) + #:use-module (gnu packages sphinx) #:use-module (gnu packages statistics) #:use-module (gnu packages sqlite) #:use-module (gnu packages swig) @@ -668,7 +671,7 @@ geometric models.") `(#:configure-flags (list ,@(match (%current-system) ((or "x86_64-linux" "i686-linux") - '("-DCMAKE_CXX_FLAGS=-msse4.1")) + '("-DCMAKE_CXX_FLAGS=-msse2")) (_ '()))) #:phases (modify-phases %standard-phases @@ -792,7 +795,7 @@ computing environments.") (define-public python-scikit-learn (package (name "python-scikit-learn") - (version "0.20.1") + (version "0.20.3") (source (origin (method git-fetch) @@ -802,7 +805,7 @@ computing environments.") (file-name (git-file-name name version)) (sha256 (base32 - "0fkhwg3xn1s7ln9q1szq6kwc4jhwvjh8w4kmv9wcrqy7cq3lbv0d")))) + "08aaby5zphfxy83mggg35bwyka7wk91l2qijh8kk0bl08dikq8dl")))) (build-system python-build-system) (arguments `(#:phases @@ -1753,3 +1756,162 @@ API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.") (license license:asl2.0))) + +(define-public python-iml + (package + (name "python-iml") + (version "0.6.2") + (source + (origin + (method url-fetch) + (uri (pypi-uri "iml" version)) + (sha256 + (base32 + "1k8szlpm19rcwcxdny9qdm3gmaqq8akb4xlvrzyz8c2d679aak6l")))) + (build-system python-build-system) + (propagated-inputs + `(("ipython" ,python-ipython) + ("nose" ,python-nose) + ("numpy" ,python-numpy) + ("pandas" ,python-pandas) + ("scipy" ,python-scipy))) + (home-page "http://github.com/interpretable-ml/iml") + (synopsis "Interpretable Machine Learning (iML) package") + (description "Interpretable ML (iML) is a set of data type objects, +visualizations, and interfaces that can be used by any method designed to +explain the predictions of machine learning models (or really the output of +any function). It currently contains the interface and IO code from the Shap +project, and it will potentially also do the same for the Lime project.") + (license license:expat))) + +(define-public python-keras-applications + (package + (name "python-keras-applications") + (version "1.0.8") + (source + (origin + (method url-fetch) + (uri (pypi-uri "Keras_Applications" version)) + (sha256 + (base32 + "1rcz31ca4axa6kzhjx4lwqxbg4wvlljkj8qj9a7p9sfd5fhzjyam")))) + (build-system python-build-system) + ;; The tests require Keras, but this package is needed to build Keras. + (arguments '(#:tests? #f)) + (propagated-inputs + `(("python-h5py" ,python-h5py) + ("python-numpy" ,python-numpy))) + (native-inputs + `(("python-pytest" ,python-pytest) + ("python-pytest-cov" ,python-pytest-cov) + ("python-pytest-pep8" ,python-pytest-pep8) + ("python-pytest-xdist" ,python-pytest-xdist))) + (home-page "https://github.com/keras-team/keras-applications") + (synopsis "Reference implementations of popular deep learning models") + (description + "This package provides reference implementations of popular deep learning +models for use with the Keras deep learning framework.") + (license license:expat))) + +(define-public python-keras-preprocessing + (package + (name "python-keras-preprocessing") + (version "1.1.0") + (source + (origin + (method url-fetch) + (uri (pypi-uri "Keras_Preprocessing" version)) + (sha256 + (base32 + "1r98nm4k1svsqjyaqkfk23i31bl1kcfcyp7094yyj3c43phfp3as")))) + (build-system python-build-system) + (propagated-inputs + `(("python-numpy" ,python-numpy) + ("python-six" ,python-six))) + (native-inputs + `(("python-pandas" ,python-pandas) + ("python-pillow" ,python-pillow) + ("python-pytest" ,python-pytest) + ("python-pytest-cov" ,python-pytest-cov) + ("python-pytest-xdist" ,python-pytest-xdist) + ("tensorflow" ,tensorflow))) + (home-page "https://github.com/keras-team/keras-preprocessing/") + (synopsis "Data preprocessing and augmentation for deep learning models") + (description + "Keras Preprocessing is the data preprocessing and data augmentation +module of the Keras deep learning library. It provides utilities for working +with image data, text data, and sequence data.") + (license license:expat))) + +(define-public python-keras + (package + (name "python-keras") + (version "2.2.4") + (source + (origin + (method url-fetch) + (uri (pypi-uri "Keras" version)) + (sha256 + (base32 + "1j8bsqzh49vjdxy6l1k4iwax5vpjzniynyd041xjavdzvfii1dlh")))) + (build-system python-build-system) + (arguments + `(#:phases + (modify-phases %standard-phases + (add-after 'unpack 'remove-tests-for-unavailable-features + (lambda _ + (delete-file "keras/backend/theano_backend.py") + (delete-file "keras/backend/cntk_backend.py") + (delete-file "tests/keras/backend/backend_test.py") + + ;; FIXME: This doesn't work because Tensorflow is missing the + ;; coder ops library. + (delete-file "tests/keras/test_callbacks.py") + #t)) + (replace 'check + (lambda _ + ;; These tests attempt to download data files from the internet. + (delete-file "tests/integration_tests/test_datasets.py") + (delete-file "tests/integration_tests/imagenet_utils_test.py") + + (setenv "PYTHONPATH" + (string-append (getcwd) "/build/lib:" + (getenv "PYTHONPATH"))) + (invoke "py.test" "-v" + "-p" "no:cacheprovider" + "--ignore" "keras/utils")))))) + (propagated-inputs + `(("python-h5py" ,python-h5py) + ("python-keras-applications" ,python-keras-applications) + ("python-keras-preprocessing" ,python-keras-preprocessing) + ("python-numpy" ,python-numpy) + ("python-pydot" ,python-pydot) + ("python-pyyaml" ,python-pyyaml) + ("python-scipy" ,python-scipy) + ("python-six" ,python-six) + ("tensorflow" ,tensorflow) + ("graphviz" ,graphviz))) + (native-inputs + `(("python-pandas" ,python-pandas) + ("python-pytest" ,python-pytest) + ("python-pytest-cov" ,python-pytest-cov) + ("python-pytest-pep8" ,python-pytest-pep8) + ("python-pytest-timeout" ,python-pytest-timeout) + ("python-pytest-xdist" ,python-pytest-xdist) + ("python-sphinx" ,python-sphinx) + ("python-requests" ,python-requests))) + (home-page "https://github.com/keras-team/keras") + (synopsis "High-level deep learning framework") + (description "Keras is a high-level neural networks API, written in Python +and capable of running on top of TensorFlow. It was developed with a focus on +enabling fast experimentation. Use Keras if you need a deep learning library +that: + +@itemize +@item Allows for easy and fast prototyping (through user friendliness, + modularity, and extensibility). +@item Supports both convolutional networks and recurrent networks, as well as + combinations of the two. +@item Runs seamlessly on CPU and GPU. +@end itemize\n") + (license license:expat))) |