flake8

theano/gpuarray/opt.py

@@ -430,7 +430,6 @@ class GraphToGPU(Optimizer):
 
             for old_output, new_output in zip(node.outputs, outputs):
                 copy_stack_trace(old_output, new_output)
-                new_output.tag.tracefrom = old_output
 
             if new_ops:
                 node_created[lopt] += len(graph.ops([mapping[i] for i in node.inputs], outputs))
@@ -2407,7 +2406,7 @@ def local_gpu_elemwise_careduce(node):
         props["pre_scalar_op"] = scalar.basic.sqr
         out = GpuCAReduceCuda(**props)(inp)
         with inherit_stack_trace(node.outputs):
-        return out
+            return out
 
 
 @local_optimizer(None)

theano/tensor/blas.py

@@ -1628,16 +1628,12 @@ def local_dot_to_dot22(node):
     if y.type.dtype in ['float16', 'float32', 'float64', 'complex64', 'complex128']:
         with inherit_stack_trace(node.outputs):
             if x.ndim == 2 and y.ndim == 2:
-                # print "local_dot_to_dot22: MM"
                 return [_dot22(*node.inputs)]
             if x.ndim == 2 and y.ndim == 1:
-                # print "local_dot_to_dot22: MV"
                 return [_dot22(x, y.dimshuffle(0, 'x')).dimshuffle(0)]
             if x.ndim == 1 and y.ndim == 2:
-                # print "local_dot_to_dot22: VM"
                 return [_dot22(x.dimshuffle('x', 0), y).dimshuffle(1)]
             if x.ndim == 1 and y.ndim == 1:
-                # print "local_dot_to_dot22: VV"
                 return [_dot22(x.dimshuffle('x', 0),
                                y.dimshuffle(0, 'x')).dimshuffle()]