pep8

theano/sandbox/linalg/ops.py

@@ -879,6 +879,7 @@ class A_Xinv_b(Op):
         gb = matrix_dot(ix.T, a.T, gz)
         return [ga, gX, gb]
 
+
 class Eig(Op):
     """Compute the eigenvalues and right eigenvectors of a square array.
 
@@ -916,24 +917,27 @@ class Eig(Op):
 
     def infer_shape(self, node, shapes):
         n = shapes[0][0]
-        return [(n,), (n,n)]
+        return [(n,), (n, n)]
 
     def __str__(self):
         return self._numop.__name__.capitalize()
 
 eig = Eig()
 
+
 def _zero_disconnected(outputs, grads):
     return [o.zeros_like()
             if isinstance(g.type, DisconnectedType) else g
             for o, g in zip(outputs, grads)]
 
+
 class Eigh(Eig):
     """
     Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix.
 
     """
     _numop = staticmethod(numpy.linalg.eigh)
+
     def __init__(self, UPLO='L'):
         self.UPLO = UPLO
 
@@ -962,7 +966,6 @@ class Eigh(Eig):
         except numpy.linalg.LinAlgError:
             logger.debug('Failed to find %s of %s' % (self._numop.__name__,
                                                       node.inputs[0]))
-                                                      
             raise
 
     def grad(self, inputs, g_outputs):
@@ -994,9 +997,11 @@ class Eigh(Eig):
         gw, gv = _zero_disconnected([w, v], g_outputs)
         return [EighGrad(self.UPLO)(x, w, v, gw, gv)]
 
+
 def eigh(a, UPLO='L'):
     return Eigh(UPLO)(a)
 
+
 class EighGrad(Op):
     """Gradient of an eigensystem of a Hermitian matrix.
 
@@ -1022,7 +1027,6 @@ class EighGrad(Op):
     def __str__(self):
         return 'EighGrad{%s}' % self.UPLO
 
-
     def make_node(self, x, w, v, gw, gv):
         x, w, v, gw, gv = map(as_tensor_variable, (x, w, v, gw, gv))
         return Apply(self, [x, w, v, gw, gv], [x.type()])
@@ -1036,9 +1040,9 @@ class EighGrad(Op):
         N = x.shape[0]
         outer = numpy.outer
 
-        G = lambda n: sum(v[:,m]*V.T[n].dot(v[:,m])/(w[n]-w[m])
+        G = lambda n: sum(v[:, m] * V.T[n].dot(v[:, m]) / (w[n] - w[m])
                           for m in xrange(N) if m != n)
-        g = sum(outer(v[:,n], v[:,n]*W[n] + G(n))
+        g = sum(outer(v[:, n], v[:, n] * W[n] + G(n))
                 for n in xrange(N))
 
         # Numpy's eigh(a, 'L') (eigh(a, 'U')) is a function of tril(a)
@@ -1053,4 +1057,3 @@ class EighGrad(Op):
 
     def infer_shape(self, node, shapes):
         return [shapes[0]]
-