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-rw-r--r--gnu/packages/machine-learning.scm33
1 files changed, 17 insertions, 16 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm
index 11c9b0207e..85460aebfb 100644
--- a/gnu/packages/machine-learning.scm
+++ b/gnu/packages/machine-learning.scm
@@ -2521,24 +2521,26 @@ with image data, text data, and sequence data.")
(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))
+ (delete-file "tests/keras/test_callbacks.py")))
(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")
- ;; Backport https://github.com/keras-team/keras/pull/12479.
- (substitute* "tests/keras/engine/test_topology.py"
- (("np.ones\\(\\(3, 2\\)\\)")
- "1."))
- (invoke "python" "-m" "pytest"
- ;; The following test fail only in the build container;
- ;; skip it.
- "-k" "not test_selu"))))))
+ (lambda* (#:key tests? #:allow-other-keys)
+ (when tests?
+ ;; 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")
+ ;; Backport https://github.com/keras-team/keras/pull/12479.
+ (substitute* "tests/keras/engine/test_topology.py"
+ (("np.ones\\(\\(3, 2\\)\\)")
+ "1."))
+ (invoke "python" "-m" "pytest" "tests"
+ "-p" "no:pep8"
+ ;; FIXME: python-build-system lacks PARALLEL-TESTS?
+ "-n" (number->string (parallel-job-count))
+ ;; The following test fail only in the build container;
+ ;; skip it.
+ "-k" "not test_selu")))))))
(propagated-inputs
`(("python-h5py" ,python-h5py)
("python-keras-applications" ,python-keras-applications)
@@ -2565,7 +2567,6 @@ with image data, text data, and sequence data.")
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).