Update test_solve.py

Author: npolina4

tests/third_party/cupy/linalg_tests/test_solve.py

@@ -67,6 +67,9 @@ def test_solve(self):
 
     def check_shape(self, a_shape, b_shape, error_types):
         for xp, error_type in error_types.items():
+            # TODO: to roll back the change once the issue with CUDA support is resolved for random
+            # a = xp.random.rand(*a_shape)
+            # b = xp.random.rand(*b_shape)
             if xp is cupy and cupy.is_cuda_backend():
                 a = xp.asarray(numpy.random.rand(*a_shape))
                 b = xp.asarray(numpy.random.rand(*b_shape))
@@ -149,6 +152,8 @@ def check_x(self, a_shape, dtype):
         testing.assert_array_equal(a_gpu_copy, a_gpu)
 
     def check_shape(self, a_shape):
+        # TODO: to roll back the change once the issue with CUDA support is resolved for random
+        # a = cupy.random.rand(*a_shape)
         a = cupy.asarray(numpy.random.rand(*a_shape))
         with self.assertRaises(cupy.linalg.LinAlgError):
             cupy.linalg.inv(a)
@@ -266,6 +271,9 @@ def check_lstsq_solution(
         return results
 
     def check_invalid_shapes(self, a_shape, b_shape):
+        # TODO: to roll back the change once the issue with CUDA support is resolved for random
+        # a = cupy.random.rand(*a_shape)
+        # b = cupy.random.rand(*b_shape)
         a = cupy.asarray(numpy.random.rand(*a_shape))
         b = cupy.asarray(numpy.random.rand(*b_shape))
         with pytest.raises(cupy.linalg.LinAlgError):
@@ -342,11 +350,15 @@ def check_x(self, a_shape, ind, dtype):
         testing.assert_array_equal(a_gpu_copy, a_gpu)
 
     def check_shape(self, a_shape, ind):
+        # TODO: to roll back the change once the issue with CUDA support is resolved for random
+        # a = cupy.random.rand(*a_shape)
         a = cupy.asarray(numpy.random.rand(*a_shape))
         with self.assertRaises(cupy.linalg.LinAlgError):
             cupy.linalg.tensorinv(a, ind=ind)
 
     def check_ind(self, a_shape, ind):
+        # TODO: to roll back the change once the issue with CUDA support is resolved for random
+        # a = cupy.random.rand(*a_shape)
         a = cupy.asarray(numpy.random.rand(*a_shape))
         with self.assertRaises(ValueError):
             cupy.linalg.tensorinv(a, ind=ind)