Merge pull request #3125 from harlouci/flake8_v7

theano/misc/check_blas.py

@@ -7,13 +7,6 @@
 # a,b scalar
 from __future__ import print_function
 
-s = """
-result for shapes=(2000,2000) and iters=100
-GTX 470 7.22s
-GTX 285, 6.84s
-GTX 480 5.83s
-"""
-
 import os
 import sys
 import time
@@ -52,14 +45,14 @@ def execute(execute=True, verbose=True, M=2000, N=2000, K=2000,
         print('    OMP_NUM_THREADS=', os.getenv('OMP_NUM_THREADS'))
         print('    GOTO_NUM_THREADS=', os.getenv('GOTO_NUM_THREADS'))
         print()
-        print ('Numpy config: (used when the Theano flag'
-               ' "blas.ldflags" is empty)')
+        print('Numpy config: (used when the Theano flag'
+              ' "blas.ldflags" is empty)')
         numpy.show_config()
         print('Numpy dot module:', numpy.dot.__module__)
         print('Numpy location:', numpy.__file__)
         print('Numpy version:', numpy.__version__)
         if (theano.config.device.startswith("gpu") or
-            theano.config.init_gpu_device.startswith("gpu")):
+                theano.config.init_gpu_device.startswith("gpu")):
             print('nvcc version:')
             subprocess.call((theano.sandbox.cuda.nvcc_compiler.nvcc_path,
                              "--version"))
@@ -116,8 +109,8 @@ def test():
 
 
 parser = OptionParser(
-        usage='%prog <options>\nCompute time needed to perform BLAS gemm '
-              'computations between matrices of size (M, N) and (N, K).')
+    usage='%prog <options>\nCompute time needed to perform BLAS gemm '
+    'computations between matrices of size (M, N) and (N, K).')
 
 parser.add_option('-q', '--quiet', action='store_true', dest='quiet',
                   default=False,
@@ -255,25 +248,25 @@ if __name__ == "__main__":
         K40                             0.88s
         K20m/ECC
         K20/NOECC
-        M2090   
-        C2075             
-        M2075             
-        M2070             
-        M2070-Q           
-        M2050(Amazon)     
-        C1060             
-        K600              
-
-        GTX Titan Black   
+        M2090
+        C2075
+        M2075
+        M2070
+        M2070-Q
+        M2050(Amazon)
+        C1060
+        K600
+
+        GTX Titan Black
         GTX Titan(D15U-50)
-        GTX 780           
-        GTX 980           
-        GTX 970           
-        GTX 680           
-        GRID K520         
-        GTX 580           
-        GTX 480           
-        GTX 750 Ti        
+        GTX 780
+        GTX 980
+        GTX 970
+        GTX 680
+        GRID K520
+        GTX 580
+        GTX 480
+        GTX 750 Ti
         """)
 
     if options.M == 0:
@@ -306,7 +299,6 @@ if __name__ == "__main__":
         print()
         print('Total execution time: %.2fs on %s.' % (t, impl))
         print()
-        print ('Try to run this script a few times. Experience shows that'
-               ' the first time is not as fast as followings calls. The'
-               ' difference is not big, but consistent.')
-
+        print('Try to run this script a few times. Experience shows that'
+              ' the first time is not as fast as followings calls. The'
+              ' difference is not big, but consistent.')

theano/misc/check_duplicate_key.py

 from __future__ import print_function
+
 import six.moves.cPickle as pickle
-import os, sys
+import os
+import sys
 
 import theano
 from six import iteritems, itervalues
@@ -90,6 +92,6 @@ useless = total - uniq
 print("mod.{cpp,cu} total:", total)
 print("mod.{cpp,cu} uniq:", uniq)
 print("mod.{cpp,cu} with more than 1 copy:", more_than_one)
-print("mod.{cpp,cu} useless:", useless, float(useless)/total*100, "%")
+print("mod.{cpp,cu} useless:", useless, float(useless) / total * 100, "%")
 
 print("nb directory", len(dirs))

theano/misc/cudamat_utils.py

@@ -7,15 +7,20 @@ WARNING: In the test of this file there is a transpose that is used...
          So there can be problem with shape and stride order...
 """
 
+import six
+
 try:
     import cudamat
 
     cudamat_available = True
 
     import theano.sandbox.cuda as cuda
-    if cuda.cuda_available == False:
+    if cuda.cuda_available is False:
         raise ImportError('Optional theano package cuda disabled')
 
+    if six.PY3:
+        long = int
+
     def cudandarray_to_cudamat(x, copyif=False):
         """ take a CudaNdarray and return a cudamat.CUDAMatrix object.
 
@@ -43,7 +48,7 @@ try:
             # Check if it is c contiguous
             size = 1
             c_contiguous = True
-            for i in range(x.ndim-1, -1, -1):
+            for i in range(x.ndim - 1, -1, -1):
                 if x.shape[i] == 1:
                     continue
                 if x._strides[i] != size:
@@ -73,11 +78,10 @@ try:
             cm_mat.data_device = ctypes.cast(x.gpudata, ctypes.POINTER(ctypes.c_float))
 
             px = cudamat.CUDAMatrix(cm_mat)
-
             px._base = x  # x won't be __del__'ed as long as px is around.
 
-            px.mat_on_host = False  # let cudamat know that we don't have a numpy
-                                   # array attached.
+            # let cudamat know that we don't have a numpy array attached.
+            px.mat_on_host = False
             return px
 
     def cudamat_to_cudandarray(x):
@@ -86,12 +90,12 @@ try:
         if not isinstance(x, cudamat.CUDAMatrix):
             raise ValueError("We can transfer only cudamat.CUDAMatrix to CudaNdarray")
         # elif x.dtype != "float32":
-        #     raise ValueError("CudaNdarray support only float32")
+        # raise ValueError("CudaNdarray support only float32")
         # We don't need this, because cudamat is always float32.
         else:
             strides = [1]
             for i in x.shape[::-1][:-1]:
-                strides.append(strides[-1]*i)
+                strides.append(strides[-1] * i)
             strides = tuple(strides[::-1])
 
             import ctypes

theano/misc/elemwise_openmp_speedup.py

@@ -51,5 +51,5 @@ if __name__ == '__main__':
         costlySpeedstring = "slowdown"
 
     print("Fast op time without openmp %fs with openmp %fs %s %2.2f" % (cheapTime, cheapTimeOpenmp, cheapSpeedstring, cheapSpeed))
-    
+
     print("Slow op time without openmp %fs with openmp %fs %s %2.2f" % (costlyTime, costlyTimeOpenmp, costlySpeedstring, costlySpeed))

theano/misc/gh_api.py

@@ -19,31 +19,31 @@ token = None
 
 def get_auth_token():
     global token
-    
+
     if token is not None:
         return token
-    
+
     import keyring
     token = keyring.get_password('github', fake_username)
     if token is not None:
         return token
-    
+
     print("Please enter your github username and password. These are not "
-           "stored, only used to get an oAuth token. You can revoke this at "
-           "any time on Github.")
+          "stored, only used to get an oAuth token. You can revoke this at "
+          "any time on Github.")
     user = input("Username: ")
     pw = getpass.getpass("Password: ")
-    
+
     auth_request = {
-      "scopes": [
-        "public_repo",
-        "gist"
-      ],
-      "note": "IPython tools",
-      "note_url": "https://github.com/ipython/ipython/tree/master/tools",
+        "scopes": [
+            "public_repo",
+            "gist"
+        ],
+        "note": "IPython tools",
+        "note_url": "https://github.com/ipython/ipython/tree/master/tools",
     }
     response = requests.post('https://api.github.com/authorizations',
-                            auth=(user, pw), data=json.dumps(auth_request))
+                             auth=(user, pw), data=json.dumps(auth_request))
     response.raise_for_status()
     token = json.loads(response.text)['token']
     keyring.set_password('github', fake_username, token)
@@ -57,40 +57,40 @@ def make_auth_header():
 def post_issue_comment(project, num, body):
     url = 'https://api.github.com/repos/{project}/issues/{num}/comments'.format(project=project, num=num)
     payload = json.dumps({'body': body})
-    r = requests.post(url, data=payload, headers=make_auth_header())
+    requests.post(url, data=payload, headers=make_auth_header())
 
 
 def post_gist(content, description='', filename='file', auth=False):
     """Post some text to a Gist, and return the URL."""
     post_data = json.dumps({
-      "description": description,
-      "public": True,
-      "files": {
-        filename: {
-          "content": content
+        "description": description,
+        "public": True,
+        "files": {
+            filename: {
+                "content": content
+            }
         }
-      }
     }).encode('utf-8')
-    
+
     headers = make_auth_header() if auth else {}
     response = requests.post("https://api.github.com/gists", data=post_data, headers=headers)
     response.raise_for_status()
     response_data = json.loads(response.text)
     return response_data['html_url']
-    
+
 
 def get_pull_request(project, num, github_api=3):
     """get pull request info  by number
 
     github_api : version of github api to use
     """
-    if github_api == 2 :
+    if github_api == 2:
         url = "http://github.com/api/v2/json/pulls/{project}/{num}".format(project=project, num=num)
     elif github_api == 3:
         url = "https://api.github.com/repos/{project}/pulls/{num}".format(project=project, num=num)
     response = requests.get(url)
     response.raise_for_status()
-    if github_api == 2 :
+    if github_api == 2:
         return json.loads(response.text)['pull']
     return json.loads(response.text)
 
@@ -100,12 +100,12 @@ def get_pulls_list(project, github_api=3):
 
     github_api : version of github api to use
     """
-    if github_api == 3 :
+    if github_api == 3:
         url = "https://api.github.com/repos/{project}/pulls".format(project=project)
-    else :
+    else:
         url = "http://github.com/api/v2/json/pulls/{project}".format(project=project)
     response = requests.get(url)
     response.raise_for_status()
-    if github_api == 2 :
+    if github_api == 2:
         return json.loads(response.text)['pulls']
     return json.loads(response.text)

theano/misc/gnumpy_utils.py

@@ -2,6 +2,8 @@
 This code can only work if gnumpy and theano are initialized on the
 same gpu as theano.
 """
+
+import six
 from six.moves import reduce
 
 try:
@@ -12,9 +14,12 @@ try:
     ___const_garray = gnumpy.rand(1)
 
     import theano.sandbox.cuda as cuda
-    if cuda.cuda_available == False:
+    if cuda.cuda_available is False:
         raise ImportError('Optional theano package cuda disabled')
 
+    if six.PY3:
+        long = int
+
     def cudandarray_to_garray(x, copyif=False):
         """ take a CudaNdarray and return a gnumpy.garray object.
 
@@ -38,7 +43,7 @@ try:
             # Check if it is c contiguous
             size = 1
             c_contiguous = True
-            for i in range(x.ndim-1, -1, -1):
+            for i in range(x.ndim - 1, -1, -1):
                 if x.shape[i] == 1:
                     continue
                 if x._strides[i] != size:
@@ -57,7 +62,7 @@ try:
             # a cudamat object with no data_host.
             cm_mat = cudamat.cudamat()
 
-            cm_mat.size[0] = reduce(lambda x, y: x*y, x.shape, 1)
+            cm_mat.size[0] = reduce(lambda x, y: x * y, x.shape, 1)
             cm_mat.size[1] = 1
             cm_mat.on_host = 0
             cm_mat.on_device = 1
@@ -72,8 +77,8 @@ try:
 
             px._base = x  # x won't be freed if the cudamat object isn't freed.
 
-            px.mat_on_host = False  # let cudamat know that we don't have a numpy
-                                   # array attached.
+            # let cudamat know that we don't have a numpy array attached.
+            px.mat_on_host = False
 
             # Note how gnumpy tracks its cudamat objects: it moves things to the
             # _cmsReuseCache when the gnumpy array is deleted, thus the arrays
@@ -100,7 +105,7 @@ try:
         else:
             strides = [1]
             for i in x.shape[::-1][:-1]:
-                strides.append(strides[-1]*i)
+                strides.append(strides[-1] * i)
             strides = strides[::-1]
             for i in range(len(strides)):
                 if x.shape[i] == 1:

theano/misc/latence_gpu_transfert.py

 from __future__ import print_function
+
 import time
 
 import numpy
@@ -13,8 +14,12 @@ print(f1.maker.fgraph.toposort())
 print(f2.maker.fgraph.toposort())
 for i in [1, 10, 100, 1000, 10000, 100000, 1000000, 10000000]:
     o = numpy.zeros(i, dtype='float32')
-    t0 = time.time(); f1(o); t1 = time.time();
-    tf1 = t1-t0
-    t0 = time.time(); f2(); t1 = time.time();
+    t0 = time.time()
+    f1(o)
+    t1 = time.time()
+    tf1 = t1 - t0
+    t0 = time.time()
+    f2()
+    t1 = time.time()
 
-    print("%8i %6.1f ns %7.1f ns"%(i, tf1*1e6, (t1-t0)*1e6))
+    print("%8i %6.1f ns %7.1f ns" % (i, tf1 * 1e6, (t1 - t0) * 1e6))

theano/misc/may_share_memory.py

@@ -3,8 +3,6 @@ Function to detect memory sharing for ndarray AND sparse type AND CudaNdarray.
 numpy version support only ndarray.
 """
 
-__docformat__ = "restructuredtext en"
-
 import numpy
 from theano.tensor.basic import TensorType
 
@@ -20,6 +18,8 @@ except ImportError:
         return False
 
 from theano.sandbox import cuda
+from theano.sandbox import gpuarray
+
 if cuda.cuda_available:
     from theano.sandbox.cuda.type import CudaNdarrayType
 
@@ -29,8 +29,9 @@ else:
     def _is_cuda(a):
         return False
 
+__docformat__ = "restructuredtext en"
+
 
-from theano.sandbox import gpuarray
 if gpuarray.pygpu:
     def _is_gpua(a):
         return isinstance(a, gpuarray.pygpu.gpuarray.GpuArray)
@@ -56,7 +57,7 @@ def may_share_memory(a, b, raise_other_type=True):
     a_sparse = _is_sparse(a)
     b_sparse = _is_sparse(b)
     if (not(a_ndarray or a_sparse or a_cuda or a_gpua) or
-        not(b_ndarray or b_sparse or b_cuda or b_gpua)):
+            not(b_ndarray or b_sparse or b_cuda or b_gpua)):
         if raise_other_type:
             raise TypeError("may_share_memory support only ndarray"
                             " and scipy.sparse, CudaNdarray or GpuArray type")

theano/misc/ordered_set.py

 from __future__ import print_function
+
 from collections import MutableSet
-from theano.compat import OrderedDict
 import types
+import weakref
 
 from six import string_types
 
@@ -37,7 +38,7 @@ def check_deterministic(iterable):
 # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
 # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 # {{{ http://code.activestate.com/recipes/576696/ (r5)
-import weakref
+
 
 class Link(object):
     # This make that we need to use a different pickle protocol
@@ -61,6 +62,7 @@ class Link(object):
         if len(state) == 3:
             self.key = state[2]
 
+
 class OrderedSet(MutableSet):
     'Set the remembers the order elements were added'
     # Big-O running times for all methods are the same as for regular sets.
@@ -179,10 +181,10 @@ class OrderedSet(MutableSet):
         elif isinstance(other, set):
             # Raise exception to avoid confusion.
             raise TypeError(
-                    'Cannot compare an `OrderedSet` to a `set` because '
-                    'this comparison cannot be made symmetric: please '
-                    'manually cast your `OrderedSet` into `set` before '
-                    'performing this comparison.')
+                'Cannot compare an `OrderedSet` to a `set` because '
+                'this comparison cannot be made symmetric: please '
+                'manually cast your `OrderedSet` into `set` before '
+                'performing this comparison.')
         else:
             return NotImplemented
 

theano/misc/pycuda_example.py

@@ -33,16 +33,14 @@ from theano.sandbox.cuda.basic_ops import (as_cuda_ndarray_variable,
 from theano.sandbox.cuda.opt import gpu_seqopt
 from theano.tensor.utils import hash_from_dict
 
-from . import pycuda_init
-if not pycuda_init.pycuda_available:
-    raise Exception("No pycuda available. You can't load pycuda_example.py")
-
 import pycuda
-from pycuda.elementwise import ElementwiseKernel
 from pycuda.compiler import SourceModule
-from pycuda.tools import VectorArg
 import pycuda.gpuarray
 
+from . import pycuda_init
+if not pycuda_init.pycuda_available:
+    raise Exception("No pycuda available. You can't load pycuda_example.py")
+
 
 def _replace_npy_types(c_arg):
     c_arg = c_arg.replace('npy_float32', 'float')
@@ -235,12 +233,11 @@ class PycudaElemwiseSourceModuleOp(GpuOp):
         c_code = self.scalar_op.c_code(out_node, "some_name",
                                        tuple([n + "[i]" for n in in_name]),
                                        tuple(n + "[i]" for n in out_name), {})
-        c_code_param = ", ".join([
-            _replace_npy_types(var.type.dtype_specs()[1]) + " *" + name
-                               for var, name in chain(izip(inputs, in_name),
-                                                      izip(out_node.outputs,
-                                                           out_name))
-        ] + ["int size"])
+        c_code_param = ", ".join(
+            [_replace_npy_types(var.type.dtype_specs()[1]) + " *" + name
+             for var, name in chain(izip(inputs, in_name),
+                                    izip(out_node.outputs, out_name))] +
+            ["int size"])
         mod = SourceModule("""
   __global__ void %s(%s)
   {
@@ -259,8 +256,8 @@ class PycudaElemwiseSourceModuleOp(GpuOp):
         # TODO assert all input have the same shape
         z, = out
         if (z[0] is None or
-            z[0].shape != inputs[0].shape or
-            not z[0].is_c_contiguous()):
+                z[0].shape != inputs[0].shape or
+                not z[0].is_c_contiguous()):
             z[0] = theano.sandbox.cuda.CudaNdarray.zeros(inputs[0].shape)
         if inputs[0].shape != inputs[1].shape:
             raise TypeError("PycudaElemwiseSourceModuleOp:"
@@ -329,8 +326,8 @@ class PycudaElemwiseSourceModuleMakeThunkOp(Op):
         c_code_param = ", ".join(
             [_replace_npy_types(var.type.dtype_specs()[1]) + " *" + name
              for var, name in chain(izip(node.inputs, in_name),
-                                    izip(node.outputs, out_name))]
-            + ["int size"])
+                                    izip(node.outputs, out_name))] +
+            ["int size"])
 
         mod = SourceModule("""
   __global__ void %s(%s)
@@ -349,8 +346,8 @@ class PycudaElemwiseSourceModuleMakeThunkOp(Op):
         def thunk():
             z = outputs[0]
             if (z[0] is None or
-                z[0].shape != inputs[0][0].shape or
-                not z[0].is_c_contiguous()):
+                    z[0].shape != inputs[0][0].shape or
+                    not z[0].is_c_contiguous()):
                 z[0] = theano.sandbox.cuda.CudaNdarray.zeros(
                     inputs[0][0].shape)
             if inputs[0][0].shape != inputs[1][0].shape:
@@ -363,9 +360,9 @@ class PycudaElemwiseSourceModuleMakeThunkOp(Op):
             else:
                 grid = (1, 1)
                 block = (inputs[0][0].shape[0], inputs[0][0].shape[1], 1)
-            out = pycuda_fct(inputs[0][0], inputs[1][0], z[0],
-                             numpy.intc(inputs[1][0].size), block=block,
-                             grid=grid)
+            pycuda_fct(inputs[0][0], inputs[1][0], z[0],
+                       numpy.intc(inputs[1][0].size), block=block,
+                       grid=grid)
         thunk.inputs = inputs
         thunk.outputs = outputs
         thunk.lazy = False
@@ -384,7 +381,7 @@ def local_pycuda_gpu_elemwise(node):
     """
     if isinstance(node.op, GpuElemwise):
         if (not any([any(i.type.broadcastable) for i in node.inputs]) and
-            all([i.ndim <= 2 for i in node.inputs])):
+                all([i.ndim <= 2 for i in node.inputs])):
             new_op = PycudaElemwiseSourceModuleOp(node.op.scalar_op,
                                                   node.op.inplace_pattern)(
                                                       *node.inputs)
@@ -393,12 +390,12 @@ def local_pycuda_gpu_elemwise(node):
 pycuda_optimizer.register("local_pycuda_gpu_elemwise",
                           local_pycuda_gpu_elemwise)
 
-
+"""
 @local_optimizer([GpuElemwise])
 def local_pycuda_gpu_elemwise_kernel(node):
-    """
+    ""
        GpuElemwise -> PycudaElemwiseKernelOp
-    """
+    ""
     if isinstance(node.op, GpuElemwise):
         if not any([any(i.type.broadcastable) for i in node.inputs]):
             new_op = PycudaElemwiseKernelOp(node.op.scalar_op,
@@ -408,3 +405,4 @@ def local_pycuda_gpu_elemwise_kernel(node):
 
 pycuda_optimizer.register("local_pycuda_gpu_elemwise_kernel",
                           local_pycuda_gpu_elemwise_kernel, 1.5)
+"""

theano/misc/pycuda_init.py

@@ -23,7 +23,7 @@ pycuda_available = False
 # If theano.sandbox.cuda don't exist, it is because we are importing
 # it and it try to import this file! This mean we must init the device.
 if (not hasattr(theano.sandbox, 'cuda') or
-    theano.sandbox.cuda.use.device_number is None):
+        theano.sandbox.cuda.use.device_number is None):
     try:
         import pycuda
         import pycuda.autoinit

theano/misc/pycuda_utils.py

-import numpy
 import pycuda.gpuarray
 
 from theano.sandbox import cuda
-if cuda.cuda_available == False:
+if cuda.cuda_available is False:
     raise ImportError('Optional theano package cuda disabled')
 
 
@@ -29,7 +28,7 @@ def to_gpuarray(x, copyif=False):
         # Check if it is c contiguous
         size = 1
         c_contiguous = True
-        for i in range(x.ndim-1, -1, -1):
+        for i in range(x.ndim - 1, -1, -1):
             if x.shape[i] == 1:
                 continue
             if x._strides[i] != size:
@@ -59,7 +58,7 @@ def to_cudandarray(x):
     else:
         strides = [1]
         for i in x.shape[::-1][:-1]:
-            strides.append(strides[-1]*i)
+            strides.append(strides[-1] * i)
         strides = tuple(strides[::-1])
         ptr = int(x.gpudata)  # in pycuda trunk, y.ptr also works, which is a little cleaner
         z = cuda.from_gpu_pointer(ptr, x.shape, strides, x)

theano/misc/safe_asarray.py

@@ -2,12 +2,12 @@
 Helper function to safely convert an array to a new data type.
 """
 
-__docformat__ = "restructuredtext en"
-
 import numpy
 
 import theano
 
+__docformat__ = "restructuredtext en"
+
 
 def _asarray(a, dtype, order=None):
     """Convert the input to a Numpy array.
@@ -45,11 +45,13 @@ def _asarray(a, dtype, order=None):
             return rval.view(dtype=dtype)
         else:
             # Unexpected mismatch: better know what is going on!
-            raise TypeError('numpy.array did not return the data type we '
-                    'asked for (%s %s #%s), instead it returned type '
-                    '%s %s #%s: function '
-                    'theano._asarray may need to be modified to handle this '
-                    'data type.' %
-                    (dtype, dtype.str, dtype.num, rval.dtype, rval.str, rval.dtype.num))
+            raise TypeError(
+                'numpy.array did not return the data type we '
+                'asked for (%s %s #%s), instead it returned type '
+                '%s %s #%s: function '
+                'theano._asarray may need to be modified to handle this '
+                'data type.' %
+                (dtype, dtype.str, dtype.num, rval.dtype, rval.str,
+                 rval.dtype.num))
     else:
         return rval

theano/misc/strutil.py

-import warnings
 from six.moves import xrange
 
 
@@ -26,7 +25,8 @@ def render_string(string, sub):
                 finalCode = string[0:i] % sub
             except Exception as F:
                 if str(F) == str(E):
-                    raise Exception(string[0:i]+"<<<< caused exception "+str(F))
+                    raise Exception(
+                        string[0:i] + "<<<< caused exception " + str(F))
             i += 1
         assert False
     return finalCode
@@ -35,7 +35,7 @@ def render_string(string, sub):
 def pretty_format(string):
     lines = string.split('\n')
 
-    lines = [ strip_leading_white_space(line) for line in lines ]
+    lines = [strip_leading_white_space(line) for line in lines]
 
     indent = 0
     for i in xrange(len(lines)):
@@ -43,7 +43,7 @@ def pretty_format(string):
         if indent < 0:
             indent = 0
         #
-        lines[i] = ('    '*indent) + lines[i]
+        lines[i] = ('    ' * indent) + lines[i]
         indent += lines[i].count('{')
     #
 

theano/tests/test_flake8.py

@@ -184,20 +184,6 @@ whitelist_flake8 = [
     "scan_module/scan_opt.py",
     "scan_module/tests/test_scan.py",
     "scan_module/tests/test_scan_opt.py",
-    "misc/elemwise_openmp_speedup.py",
-    "misc/gh_api.py",
-    "misc/check_blas.py",
-    "misc/latence_gpu_transfert.py",
-    "misc/cudamat_utils.py",
-    "misc/pycuda_utils.py",
-    "misc/pycuda_example.py",
-    "misc/ordered_set.py",
-    "misc/strutil.py",
-    "misc/gnumpy_utils.py",
-    "misc/may_share_memory.py",
-    "misc/safe_asarray.py",
-    "misc/pycuda_init.py",
-    "misc/check_duplicate_key.py",
     "misc/tests/test_may_share_memory.py",
     "misc/tests/test_pycuda_theano_simple.py",
     "misc/tests/test_gnumpy_utils.py",