updated tests for cusolver solve

theano/gpuarray/linalg.py

@@ -17,6 +17,7 @@ except (ImportError, OSError, RuntimeError, pkg_resources.DistributionNotFound):
 
 cusolver_handle = None
 
+
 class GpuCusolverSolve(Op):
     """
     CUSOLVER GPU solver OP.
@@ -108,9 +109,9 @@ class GpuCusolverSolve(Op):
             ldb = max(1, k, m)
 
             # We copy A and b as cusolver operates inplace
+            b = gpuarray.array(b, copy=True, order='F')
             if not self.inplace:
                 A = gpuarray.array(A, copy=True)
-                b = gpuarray.array(b, copy=True, order='F')
             A_ptr = A.gpudata
             b_ptr = b.gpudata
 

theano/gpuarray/tests/test_linalg.py

@@ -16,19 +16,22 @@ if not cusolver_available:
 
 
 class TestCusolver(unittest.TestCase):
-    def run_gpu_solve(self, A_val, x_val, trans='N'):
-        if trans == 'N':
-            b_val = numpy.dot(A_val, x_val)
-        else:
-            b_val = numpy.dot(A_val.T, x_val)
+    def run_gpu_solve(self, A_val, x_val):
+        b_val = numpy.dot(A_val, x_val)
+        b_val_trans = numpy.dot(A_val.T, x_val)
+
         A = theano.tensor.matrix("A", dtype="float32")
         b = theano.tensor.matrix("b", dtype="float32")
+        b_trans = theano.tensor.matrix("b", dtype="float32")
 
-        solver = gpu_solve(A, b, trans)
-        fn = theano.function([A, b], [solver], mode=mode_with_gpu)
-        res = fn(A_val, b_val)
+        solver = gpu_solve(A, b)
+        solver_trans = gpu_solve(A, b_trans, trans='T')
+        fn = theano.function([A, b, b_trans], [solver, solver_trans], mode=mode_with_gpu)
+        res = fn(A_val, b_val, b_val_trans)
         x_res = numpy.array(res[0])
+        x_res_trans = numpy.array(res[1])
         utt.assert_allclose(x_res, x_val)
+        utt.assert_allclose(x_res_trans, x_val)
 
     def test_diag_solve(self):
         numpy.random.seed(1)
@@ -60,10 +63,3 @@ class TestCusolver(unittest.TestCase):
         x_val = numpy.random.uniform(-0.4, 0.4,
                                      (A_val.shape[1], 4)).astype("float32")
         self.run_gpu_solve(A_val, x_val)
-
-    def test_uni_rand_solve_transpose(self):
-        numpy.random.seed(1)
-        A_val = numpy.random.uniform(-0.4, 0.4, (5, 5)).astype("float32")
-        x_val = numpy.random.uniform(-0.4, 0.4,
-                                     (A_val.shape[1], 4)).astype("float32")
-        self.run_gpu_solve(A_val, x_val, trans='T')