flake8 for tensor/type.py ; one E left

theano/tensor/type.py

 import logging
-_logger = logging.getLogger("theano.tensor.type")
+import warnings
 
 import numpy
 
 import theano
 from theano import config
-from theano.gof import Constant, hashtype, Type, Variable
-from theano.gof.utils import MethodNotDefined
+from theano.gof import hashtype, Type, Variable
 from theano import scalar as scal
 
+_logger = logging.getLogger("theano.tensor.type")
+
 
 class TensorType(Type):
     """Symbolic `Type` representing a numpy.ndarray value."""
@@ -39,7 +40,7 @@ class TensorType(Type):
         if self.dtype == 'floatX':
             self.dtype = config.floatX
         # broadcastable is immutable, and all elements are either
-        ###    True or False
+        # True or False
         self.broadcastable = tuple(bool(b) for b in broadcastable)
         self.dtype_specs()  # error checking is done there
         self.name = name
@@ -78,13 +79,13 @@ class TensorType(Type):
                 'maybe you are trying to call a function on a (possibly '
                 'shared) variable instead of a numeric array?')
 
-        if ((type(data) is numpy.ndarray)
-                and (data.dtype == self.numpy_dtype)):
+        if ((type(data) is numpy.ndarray) and
+                (data.dtype == self.numpy_dtype)):
             if data.dtype.num != self.numpy_dtype.num:
                 data = theano._asarray(data, dtype=self.dtype)
             # -- now fall through to ndim check
-        elif((type(data) is numpy.memmap)
-                and (data.dtype == self.numpy_dtype)):
+        elif ((type(data) is numpy.memmap) and
+              (data.dtype == self.numpy_dtype)):
             # numpy.memmap is a "safe" subclass of ndarray,
             # so we can use it whereever we expect a base ndarray.
             # however, casting it would defeat the purpose of not
@@ -98,8 +99,8 @@ class TensorType(Type):
                                 data, type(data))
             if data.dtype != self.numpy_dtype:
                 raise TypeError(("%s expected a ndarray object with "
-                        "dtype = %s (got %s).") % (
-                            self, self.numpy_dtype, data.dtype))
+                                "dtype = %s (got %s).") %
+                                (self, self.numpy_dtype, data.dtype))
             assert False, "This point should never be reached."
         else:
             if allow_downcast:
@@ -210,12 +211,10 @@ class TensorType(Type):
         raise TypeError(
             'Cannot convert Type %(othertype)s '
             '(of Variable %(other)s) into Type %(self)s. '
-                'You can try to manually convert %(other)s into a %(self)s.'
-                % dict(
-                    othertype=other.type,
+            'You can try to manually convert %(other)s into a %(self)s.' %
+            dict(othertype=other.type,
                  other=other,
-                    self=self)
-                )
+                 self=self))
 
     def value_validity_msg(self, a):
         try:
@@ -422,7 +421,7 @@ class TensorType(Type):
 
     def __repr__(self):
         return str(self)
-        #"TensorType{%s, %s}" % (str(self.dtype), str(self.broadcastable))
+        # "TensorType{%s, %s}" % (str(self.dtype), str(self.broadcastable))
 
     def c_declare(self, name, sub, check_input=True):
         """Override `CLinkerType.c_declare` """

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/type.py",
     "tensor/fourier.py",
     "tensor/__init__.py",
     "tensor/opt_uncanonicalize.py",