flake8 for tensor/fourier.py

theano/tensor/fourier.py

@@ -87,8 +87,8 @@ class Fourier(gof.Op):
         if len(shape_a) == 1:
             return [(n,)]
         elif isinstance(axis, tensor.TensorConstant):
-            out_shape = list(shape_a[0: axis.data.item()]) + [n] +\
-            list(shape_a[axis.data + 1:])
+            out_shape = (list(shape_a[0: axis.data.item()]) + [n] +
+                         list(shape_a[axis.data + 1:]))
         else:
             l = len(shape_a)
             shape_a = tensor.stack(*shape_a)
@@ -136,7 +136,8 @@ class Fourier(gof.Op):
         flip_shape = list(numpy.arange(0, a.ndim)[::-1])
         res = res.dimshuffle(flip_shape)
         res = tensor.switch(tensor.lt(n, tensor.shape(a)[axis]),
-                    tensor.set_subtensor(res[n::, ], 0, False, False), res)
+                            tensor.set_subtensor(res[n::, ], 0, False, False),
+                            res)
         res = res.dimshuffle(flip_shape)
 
         # insures that gradient shape conforms to input shape:

theano/tests/test_flake8.py

@@ -57,7 +57,6 @@ whitelist_flake8 = [
     "typed_list/tests/test_type.py",
     "typed_list/tests/test_opt.py",
     "typed_list/tests/test_basic.py",
-    "tensor/fourier.py",
     "tensor/__init__.py",
     "tensor/opt_uncanonicalize.py",
     "tensor/blas.py",