fix Issue #481, ASSET tries to use a backend that is not present in the environment (#485)

* added coverage to MPI runner, removed MPI from pip added function get_opencl_capability() to utils, to detect openCL devices

* updated docstring, changed return logic

* added unittest, regression Issue #481

Co-authored-by: Cristiano Köhler <c.koehler@fz-juelich.de>

Author: Moritz-Alexander-Kern

elephant/asset/asset.py

@@ -136,7 +136,7 @@
 
 import elephant.conversion as conv
 from elephant import spike_train_surrogates
-from elephant.utils import get_cuda_capability_major
+from elephant.utils import get_cuda_capability_major, get_opencl_capability
 
 try:
     from mpi4py import MPI
@@ -513,9 +513,11 @@ def _choose_backend(self):
         use_cuda = int(os.getenv("ELEPHANT_USE_CUDA", '1'))
         use_opencl = int(os.getenv("ELEPHANT_USE_OPENCL", '1'))
         cuda_detected = get_cuda_capability_major() != 0
+        opencl_detected = get_opencl_capability()
+
         if use_cuda and cuda_detected:
             return self.pycuda
-        if use_opencl:
+        if use_opencl and opencl_detected:
             return self.pyopencl
         return self.cpu
 

elephant/test/test_asset.py

@@ -33,7 +33,7 @@
 
 try:
     import pyopencl
-    HAVE_PYOPENCL = True
+    HAVE_PYOPENCL = asset.get_opencl_capability()
 except ImportError:
     HAVE_PYOPENCL = False
 
@@ -393,6 +393,39 @@ def test_intersection_matrix(self):
                           spiketrains_i=[st1, st2], bin_size=bin_size,
                           t_stop_j=5 * pq.ms)
 
+    #  regression test Issue #481
+    #  see: https://github.com/NeuralEnsemble/elephant/issues/481
+    def test_asset_choose_backend_opencl(self):
+        class TestClassBackend(asset._GPUBackend):
+
+            def __init__(self):
+                super().__init__()
+                self.backend = self._choose_backend()
+
+            def cpu(self):
+                return "cpu"
+
+            def pycuda(self):
+                return "cuda"
+
+            def pyopencl(self):
+                return "opencl"
+
+        # check which backend is chosen if environment variable for opencl
+        # is not set
+        os.environ.pop('ELEPHANT_USE_OPENCL', None)
+        # create object of TestClass
+        backend_obj = TestClassBackend()
+
+        if HAVE_PYOPENCL:
+            self.assertEqual(backend_obj.backend(), 'opencl')
+        else:
+            # if environment variable is not set and no module pyopencl or
+            # device is found: choose cpu backend
+            self.assertEqual(backend_obj.backend(), 'cpu')
+
+        os.environ['ELEPHANT_USE_OPENCL'] = '0'
+
 
 @unittest.skipUnless(HAVE_SKLEARN, 'requires sklearn')
 class TestJSFUniformOrderStat3D(unittest.TestCase):

elephant/utils.py

@@ -340,3 +340,25 @@ def get_cuda_capability_major():
                                    ctypes.byref(cc_minor),
                                    device)
     return cc_major.value
+
+
+def get_opencl_capability():
+    """
+    Return a list of available OpenCL devices.
+
+    Returns
+    -------
+    bool
+        True: if openCL platform detected and at least one device is found,
+        False: if OpenCL is not found or if no OpenCL devices are found
+    """
+    try:
+        import pyopencl
+        platforms = pyopencl.get_platforms()
+
+        if len(platforms) == 0:
+            return False
+        # len(platforms) is > 0, if it is not == 0
+        return True
+    except ImportError:
+        return False