Small coding style improvements

theano/tensor/opt.py

@@ -2958,13 +2958,14 @@ for i in range(1,len(p64)): print i, 64[i]-p64[i-1]
 # ###############
 # # Loop fusion #
 # ###############
-def local_elemwise_fusion_op(OP, max_input_fct = lambda node: 1024):
+def local_elemwise_fusion_op(OP, max_input_fct=lambda node: 1024):
     """
-    We parametrise it to make it work for Elemwise and GpuElemwise op.
+    We parametrize it to make it work for Elemwise and GpuElemwise op.
 
     :param OP: GpuElemwise or Elemwise class (the one that we want to fuse)
 
-    :param max_input_fct: a fct that return the maximum number of input that this elemwise can take(usefull for the GpuElemwise)
+    :param max_input_fct: a function that returns the maximum number of inputs
+                          that this elemwise can take (useful for GpuElemwise)
     """
     def local_fuse(node):
         """
@@ -2998,7 +2999,8 @@ def local_elemwise_fusion_op(OP, max_input_fct = lambda node: 1024):
         s_inputs = []#inputs of the new scalar op.
         s_g=[]#graph of scalar, what will by done in the inner loop.
 
-        # There is a hard limit of 256 bytes for the formal argument list to a GPU kernel function.
+        # There is a hard limit of 256 bytes for the formal argument list to a
+        # GPU kernel function.
         max_nb_input = max_input_fct(node)
         #print len(node.inputs),max_nb_input
         new_nb_input = len(node.inputs)
@@ -3008,10 +3010,10 @@ def local_elemwise_fusion_op(OP, max_input_fct = lambda node: 1024):
             catch = False
             tmp_input=[]#used to remove duplicate input.
             tmp_scalar=[]
-            if ((new_nb_input+1)<=max_nb_input
-                and i.owner
-                and isinstance(i.owner.op, OP)
-                and len(i.clients)==1):
+            if ((new_nb_input+1)<=max_nb_input and
+                i.owner and
+                isinstance(i.owner.op, OP) and
+                len(i.clients)==1):
                 #if the scalar_op don't have a c implementation, we skip its fusion to allow the fusion of the other ops.
                 do_fusion=True
                 try:
@@ -3054,7 +3056,7 @@ def local_elemwise_fusion_op(OP, max_input_fct = lambda node: 1024):
 
         #if no inputs have are an elemwise, there is nothing to fuse.
         if new_nb_input==len(node.inputs):
-    #        print "local_elemwise_fusion: no elemwise in inputs. Nothing to fuse."
+            #print "local_elemwise_fusion: no elemwise in inputs. Nothing to fuse."
             return False
 
         assert len(s_inputs)==len(inputs)