flake8 for theano/tensor/nnet/sigm.py

theano/tensor/nnet/sigm.py

@@ -7,7 +7,6 @@ from __future__ import print_function
 import warnings
 
 import numpy
-from six.moves import xrange
 
 import theano
 from theano import config, gof, printing, scalar
@@ -129,9 +128,8 @@ class ScalarSigmoid(scalar.UnaryScalarOp):
         """
         This method was used to generate the graph: sigmoid_prec.png in the doc
         """
-        import matplotlib
         data = numpy.arange(-15, 15, .1)
-        val = 1/(1+numpy.exp(-data))
+        val = 1 / (1 + numpy.exp(-data))
 
         def hard_sigmoid(x):
             return theano.tensor.nnet.hard_sigmoid(x)
@@ -167,7 +165,7 @@ sigmoid_inplace = elemwise.Elemwise(
     ScalarSigmoid(scalar.transfer_type(0)),
     inplace_pattern={0: 0},
     name='sigmoid_inplace',
-        )
+)
 
 pprint.assign(sigmoid, printing.FunctionPrinter('sigmoid'))
 
@@ -240,7 +238,7 @@ pprint.assign(ultra_fast_sigmoid,
               printing.FunctionPrinter('ultra_fast_sigmoid'))
 
 
-#@opt.register_uncanonicalize
+# @opt.register_uncanonicalize
 @gof.local_optimizer([sigmoid])
 def local_ultra_fast_sigmoid(node):
     """
@@ -290,7 +288,7 @@ def hard_sigmoid(x):
     return x
 
 
-#@opt.register_uncanonicalize
+# @opt.register_uncanonicalize
 @gof.local_optimizer([sigmoid])
 def local_hard_sigmoid(node):
     if (isinstance(node.op, tensor.Elemwise) and
@@ -439,7 +437,8 @@ def is_1pexp(t):
     return None
 
 
-AddConfigVar('warn.identify_1pexp_bug',
+AddConfigVar(
+    'warn.identify_1pexp_bug',
     'Warn if Theano versions prior to 7987b51 (2011-12-18) could have '
     'yielded a wrong result due to a bug in the is_1pexp function',
     BoolParam(theano.configdefaults.warn_default('0.4.1')),
@@ -892,7 +891,7 @@ def local_1msigmoid(node):
         if sub_r.owner and sub_r.owner.op == sigmoid:
             try:
                 val_l = opt.get_scalar_constant_value(sub_l)
-            except Exception as e:
+            except Exception:
                 return
             if numpy.allclose(numpy.sum(val_l), 1):
                 return [sigmoid(-sub_r.owner.inputs[0])]
@@ -921,7 +920,6 @@ if 0:
         print(sigm_canonicalize(node))
 
     def sigm_canonicalize(node):
-        add = tensor.add
         mul = tensor.mul
         div = tensor.true_div
 

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/sigm.py",
     "tensor/nnet/ConvGrad3D.py",
     "tensor/nnet/conv3d2d.py",
     "tensor/nnet/conv.py",