Corrections, flake8 corrections and re-testing.

theano/gpuarray/elemwise.py

@@ -2603,7 +2603,7 @@ class GpuErfinv(Erfinv):
         return "%(z)s = (%(x)s <= -1) ? erfinv(-1.0): ((%(x)s >= 1) ? erfinv(1.0): erfinv(%(x)s));" % locals()
 
 
-class GpuErfcinv(Erfinv):
+class GpuErfcinv(Erfcinv):
     """
     Inverse complementary error function for GPU.
 
@@ -2626,6 +2626,7 @@ class GpuErfcinv(Erfinv):
 gpu_erfinv = GpuErfinv(upgrade_to_float_no_complex, name='gpu_erfinv')
 gpu_erfcinv = GpuErfcinv(upgrade_to_float_no_complex, name='gpu_erfcinv')
 
+
 # Caching GpuCAReduceCuda
 def gpu_ca_reduce_cuda(scalar_op, axis=None, reduce_mask=None, dtype=None, acc_dtype=None,
                        pre_scalar_op=None):

theano/gpuarray/tests/test_elemwise.py

@@ -63,7 +63,7 @@ class TestMathErrorFunctions(TestCase):
     def setUp(self):
         # NB: erfinv is defined in ]-1;1[, and erfcinv is defined in ]0;2[,
         # so we just take some values in an interval that covers both domains
-        #  (this will also allow to test some values outside the domains).
+        # (this will also allow to test some values outside the domains).
         # We take [-5;5[ by default and we concatenate it 1000 times
         # to have the GPU ops run on large data.
         default_array = [x / 10.0 for x in range(-50, 50)] * 1000
@@ -132,6 +132,7 @@ class TestMathErrorFunctions(TestCase):
             self.compute_erfcinv_host(dtype)
             self.compute_erfcinv_gpu(dtype)
 
+
 class test_float16():
     def test_composite_elemwise_float16(self):
         w = theano.tensor.bvector()