FIX workaround bug in numpy 1.9 (scikit-learn#6856)

Also use dtype with explicit precision (as a good practice) although
this does not impact the outcome of this test.

Author: ogrisel

sklearn/model_selection/tests/test_validation.py

@@ -5,6 +5,7 @@
 import warnings
 import tempfile
 import os
+from time import sleep
 
 import numpy as np
 from scipy.sparse import coo_matrix, csr_matrix
@@ -62,6 +63,12 @@
 from sklearn.model_selection.tests.test_split import MockClassifier
 
 
+try:
+    WindowsError
+except NameError:
+    WindowsError = None
+
+
 class MockImprovingEstimator(BaseEstimator):
     """Dummy classifier to test the learning curve"""
     def __init__(self, n_max_train_sizes):
@@ -781,12 +788,20 @@ def test_score_memmap():
     tf = tempfile.NamedTemporaryFile(mode='wb', delete=False)
     tf.write(b'Hello world!!!!!')
     tf.close()
-    scores = np.memmap(tf.name, dtype=float)
-    score = np.memmap(tf.name, shape=(), mode='w+', dtype=float)
+    scores = np.memmap(tf.name, dtype=np.float64)
+    score = np.memmap(tf.name, shape=(), mode='r', dtype=np.float64)
     try:
         cross_val_score(clf, X, y, scoring=lambda est, X, y: score)
         # non-scalar should still fail
         assert_raises(ValueError, cross_val_score, clf, X, y,
                       scoring=lambda est, X, y: scores)
     finally:
-        os.unlink(tf.name)
+        # Best effort to release the mmap file handles before deleting the
+        # backing file under Windows
+        scores, score = None, None
+        for _ in range(3):
+            try:
+                os.unlink(tf.name)
+                break
+            except WindowsError:
+                sleep(1.)