flake8 for nlinalg, four E left

theano/tensor/nlinalg.py

 from __future__ import print_function
+
 import logging
-import theano
 
-logger = logging.getLogger(__name__)
 import numpy
 from six.moves import xrange
 
+import theano
+from theano.tensor import as_tensor_variable
 from theano.gof import Op, Apply
-
-from theano.tensor import as_tensor_variable, dot, DimShuffle, Dot
-from theano.tensor.blas import Dot22
-from theano.tensor.opt import (register_stabilize,
-        register_specialize, register_canonicalize)
-from theano.gof import local_optimizer
-from theano.gof.opt import Optimizer
 from theano.gradient import DisconnectedType
 from theano.tensor import basic as tensor
 
+logger = logging.getLogger(__name__)
+
 
 class MatrixPinv(Op):
     """Computes the pseudo-inverse of a matrix :math:`A`.
@@ -427,8 +423,10 @@ 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])
-                          for m in xrange(N) if m != n)
+        def G(n):
+            return 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))
                 for n in xrange(N))
 
@@ -670,9 +668,6 @@ class lstsq(Op):
                              theano.tensor.lscalar(), theano.tensor.dvector()])
 
     def perform(self, node, inputs, outputs):
-        x = inputs[0]
-        y = inputs[1]
-        rcond = inputs[2]
         zz = numpy.linalg.lstsq(inputs[0], inputs[1], inputs[2])
         outputs[0][0] = zz[0]
         outputs[1][0] = zz[1]
@@ -703,7 +698,7 @@ def norm(x, ord):
             return x[x.nonzero()].shape[0]
         else:
             try:
-                z = tensor.sum(abs(x**ord))**(1./ord)
+                z = tensor.sum(abs(x**ord))**(1. / ord)
             except TypeError:
                 raise ValueError("Invalid norm order for vectors.")
             return z

theano/tests/test_flake8.py

@@ -58,7 +58,6 @@ whitelist_flake8 = [
     "typed_list/tests/test_opt.py",
     "typed_list/tests/test_basic.py",
     "tensor/__init__.py",
-    "tensor/nlinalg.py",
     "tensor/blas_c.py",
     "tensor/elemwise_cgen.py",
     "tensor/blas_scipy.py",