Flake8 issue corrected.

theano/tensor/blas_headers.py

@@ -736,7 +736,7 @@ def blas_header_text():
     if not config.blas.ldflags:
         # Include the Numpy version implementation of [sd]gemm_.
         current_filedir = dirname(__file__)
-        gemm_common_filepath   = normpath(current_filedir + "/alt_gemm_common.c")
+        gemm_common_filepath = normpath(current_filedir + "/alt_gemm_common.c")
         gemm_template_filepath = normpath(current_filedir + "/alt_gemm_template.c")
         common_code = ""
         sgemm_code = ""
@@ -745,8 +745,8 @@ def blas_header_text():
             common_code = code.read()
         with open(gemm_template_filepath) as code:
             template_code = code.read()
-            sgemm_code = template_code % {"float_type":"float",  "float_size":4, "npy_float":"NPY_FLOAT32", "name":"sgemm_"}
-            dgemm_code = template_code % {"float_type":"double", "float_size":8, "npy_float":"NPY_FLOAT64", "name":"dgemm_"}
+            sgemm_code = template_code % {"float_type": "float", "float_size": 4, "npy_float": "NPY_FLOAT32", "name": "sgemm_"}
+            dgemm_code = template_code % {"float_type": "double", "float_size": 8, "npy_float": "NPY_FLOAT64", "name": "dgemm_"}
         if not common_code or not sgemm_code:
             raise IOError("Unable to load NumPy implementation of gemm code from C source files.")
         else:

theano/tensor/nnet/opt.py

@@ -98,7 +98,7 @@ def local_abstractconv_gemm(node):
 def local_abstractconv3d_gemm(node):
     # If theano.config.blas.ldflags is empty, Theano will use
     # a NumPy C implementation of [sd]gemm_.
-    if theano.config.cxx == "": # or not theano.config.blas.ldflags:
+    if theano.config.cxx == "":  # or not theano.config.blas.ldflags:
         return
     if not isinstance(node.op, AbstractConv3d):
         return None
@@ -145,7 +145,7 @@ def local_abstractconv_gradweight_gemm(node):
 
 @local_optimizer([AbstractConv3d_gradWeights])
 def local_abstractconv3d_gradweight_gemm(node):
-    if theano.config.cxx == "": # or not theano.config.blas.ldflags:
+    if theano.config.cxx == "":  # or not theano.config.blas.ldflags:
         return
     if not isinstance(node.op, AbstractConv3d_gradWeights):
         return None
@@ -193,7 +193,7 @@ def local_abstractconv_gradinputs_gemm(node):
 
 @local_optimizer([AbstractConv3d_gradInputs])
 def local_abstractconv3d_gradinputs_gemm(node):
-    if theano.config.cxx == "": # or not theano.config.blas.ldflags:
+    if theano.config.cxx == "":  # or not theano.config.blas.ldflags:
         return
     if not isinstance(node.op, AbstractConv3d_gradInputs):
         return None

theano/tensor/nnet/tests/test_abstract_conv.py

@@ -918,7 +918,7 @@ class TestBilinearUpsampling(unittest.TestCase):
     if theano.config.mode == "FAST_COMPILE":
         compile_mode = compile_mode.excluding("conv_gemm")
         compile_mode = compile_mode.excluding('AbstractConvCheck')
-    elif not theano.config.cxx: # not theano.config.blas.ldflags or 
+    elif not theano.config.cxx:  # not theano.config.blas.ldflags or
         compile_mode = compile_mode.excluding('AbstractConvCheck')
 
     def numerical_kernel_1D(self, ratio):

theano/tensor/nnet/tests/test_corr.py

@@ -131,7 +131,7 @@ class TestCorr2D(utt.InferShapeTester):
                                 icol:icol + dil_fil_shape2d[1]:filter_dilation[1]] * filter2d[::-1, ::-1]
                             ).sum()
 
-        #utt.assert_allclose(theano_output, ref_output)
+        # utt.assert_allclose(theano_output, ref_output)
         utt.assert_allclose(ref_output, theano_output)
 
         # TEST GRADIENT