Speeding up tests

tensorly · Aug 22, 2017 · 24ba475 · 24ba475
1 parent 83f5101
commit 24ba475
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Showing 2 changed files with 12 additions and 9 deletions.
diff --git a/.travis.yml b/.travis.yml
@@ -7,9 +7,12 @@ python:
 install: 
     - pip install -r requirements.txt
     - pip install coveralls
+env:
+    matrix:
+        - BACKEND=numpy
+        - BACKEND=mxnet
 # command to run tests
 script:
     - travis_wait make BACKEND=numpy test-coverage
-    - travis_wait make BACKEND=mxnet test-coverage
 after_success:
     - coveralls
diff --git a/tensorly/decomposition/tests/test_candecomp_parafac.py b/tensorly/decomposition/tests/test_candecomp_parafac.py
@@ -5,16 +5,15 @@
 from ...random import check_random_state
 from ... import backend as T
 
-
 def test_parafac():
     """Test for the CANDECOMP-PARAFAC decomposition
     """
     rng = check_random_state(1234)
     tol_norm_2 = 10e-2
     tol_max_abs = 10e-2
     tensor = T.tensor(rng.random_sample((3, 4, 2)))
-    factors_svd = parafac(tensor, rank=4, n_iter_max=200, init='svd')
-    factors_random = parafac(tensor, rank=4, n_iter_max=200, init='random', random_state=1234, verbose=1)
+    factors_svd = parafac(tensor, rank=4, n_iter_max=200, init='svd', tol=10e-5)
+    factors_random = parafac(tensor, rank=4, n_iter_max=200, init='random', tol=10e-5, random_state=1234, verbose=0)
     rec_svd = kruskal_to_tensor(factors_svd)
     rec_random = kruskal_to_tensor(factors_random)
     error = T.norm(rec_svd - tensor, 2)
@@ -44,9 +43,9 @@ def test_non_negative_parafac():
     tol_norm_2 = 10e-1
     tol_max_abs = 1
     rng = check_random_state(1234)
-    tensor = T.tensor(rng.random_sample((3, 3, 3))*2)
+    tensor = T.tensor(rng.random_sample((3, 3, 3))+1)
     factors = parafac(tensor, rank=3, n_iter_max=120)
-    nn_factors = non_negative_parafac(tensor, rank=3, n_iter_max=500, init='svd', verbose=1)
+    nn_factors = non_negative_parafac(tensor, rank=3, n_iter_max=100, tol=10e-4, init='svd', verbose=0)
 
     # Make sure all components are positive
     for factor in nn_factors:
@@ -63,10 +62,10 @@ def test_non_negative_parafac():
     T.assert_(T.max(T.abs(reconstructed_tensor - nn_reconstructed_tensor)) < tol_max_abs,
             'abs norm of reconstruction error higher than tol')
 
-    factors_svd = non_negative_parafac(tensor, rank=3, n_iter_max=100,
+    factors_svd = non_negative_parafac(tensor, rank=3, n_iter_max=100, tol=10e-4,
                                        init='svd')
-    factors_random = non_negative_parafac(tensor, rank=3, n_iter_max=100,
-                                          init='random', random_state=1234, verbose=1)
+    factors_random = non_negative_parafac(tensor, rank=3, n_iter_max=100, tol=10e-4,
+                                          init='random', random_state=1234, verbose=0)
     rec_svd = kruskal_to_tensor(factors_svd)
     rec_random = kruskal_to_tensor(factors_random)
     error = T.norm(rec_svd - rec_random, 2)
@@ -75,3 +74,4 @@ def test_non_negative_parafac():
             'norm 2 of difference between svd and random init too high')
     T.assert_(T.max(T.abs(rec_svd - rec_random)) < tol_max_abs,
             'abs norm of difference between svd and random init too high')
+