flake8 for theano/tensor/nnet/neighbours.py

theano/tensor/nnet/Conv3D.py

@@ -3,9 +3,6 @@ from __future__ import print_function
 import numpy as N
 from six.moves import xrange
 
-from . import ConvGrad3D
-from . import ConvTransp3D
-
 import theano
 from theano.tensor import basic as T
 # from util import strutil
@@ -623,3 +620,6 @@ def computeH(V, W, b, d):
                                         #    print 'setting H[0] += '+str(w*v)+'   W['+str((j,z,k,l,m))+']='+str(w)+'   V['+str((i,d[0]*x+k,d[1]*y+l,d[2]*t+m,z))+']='+str(v)
                                         H[i, x, y, t, j] += w * v
     return H
+    
+from . import ConvGrad3D
+from . import ConvTransp3D

theano/tensor/nnet/neighbours.py

@@ -2,15 +2,15 @@
 TODO: implement Images2Neibs.infer_shape() methods
 
 """
-from six.moves import xrange
+
+import numpy
+
 import theano
 from theano import Op, Apply
 import theano.tensor as T
 from theano.gradient import grad_not_implemented
 from theano.gradient import grad_undefined
 
-import numpy
-
 
 class Images2Neibs(Op):
 
@@ -543,7 +543,6 @@ def neibs2images(neibs, neib_shape, original_shape, mode='valid'):
        :func:`images2neibs <theano.sandbox.neigbours.neibs2images>` for
        gradient computation.
 
-
     Example, which uses a tensor gained in example for
     :func:`images2neibs <theano.sandbox.neigbours.neibs2images>`:
 

theano/tests/test_flake8.py

@@ -89,7 +89,6 @@ whitelist_flake8 = [
     "tensor/signal/tests/test_conv.py",
     "tensor/signal/tests/test_downsample.py",
     "tensor/nnet/__init__.py",
-    "tensor/nnet/neighbours.py",
     "tensor/nnet/tests/test_conv.py",
     "tensor/nnet/tests/test_neighbours.py",
     "tensor/nnet/tests/test_nnet.py",