Rename an optimization to have it more clear and more consistent.

theano/sandbox/cuda/opt.py

@@ -141,7 +141,7 @@ def local_gpu_elemwise_0(node):
     if isinstance(node.op, tensor.Elemwise) and dtype_in_elemwise_supported(node.op):
         if numpy.any([i.owner and isinstance(i.owner.op, HostFromGpu) for i in node.inputs]):
             if numpy.all([o.type.dtype == 'float32' for o in node.outputs]):
-                #don't set any inplace pattern. gpu_insert_inplace_optimizer will do it later
+                #don't set any inplace pattern. gpu_inplace_optimizer will do it later
                 new_op = GpuElemwise(node.op.scalar_op)
 
                 #   first establish that float32 can store all inputs
@@ -184,7 +184,7 @@ def local_gpu_elemwise_1(node):
             dtype_in_elemwise_supported(node.op)):
 
             elemwise_node = host_i.owner
-            #don't set any inplace pattern. gpu_insert_inplace_optimizer will do it later
+            #don't set any inplace pattern. gpu_inplace_optimizer will do it later
             new_op = GpuElemwise(elemwise_node.op.scalar_op)
             if all([i.dtype=='float32' for i in elemwise_node.inputs]):
                 gpu_elemwise = new_op(*[gpu_from_host(i) for i in elemwise_node.inputs])
@@ -993,10 +993,10 @@ else:
     compile.optdb.register('gpu_elemwise_fusion', tensor.opt.FusionOptimizer(gpu_local_elemwise_fusion), 71.00, 'fusion', 'local_elemwise_fusion')
 
 #GpuElemwise inplace
-gpu_insert_inplace_optimizer = tensor.opt.insert_inplace_optimizer_op(
+gpu_inplace_elemwise_optimizer = tensor.opt.inplace_elemwise_optimizer_op(
         GpuElemwise)
-compile.optdb.register('gpu_inplace_opt', gpu_insert_inplace_optimizer, 75,
-        'fast_run', 'inplace','gpu_inplace')
+optdb.register('gpu_inplace_elemwise_opt', gpu_inplace_elemwise_optimizer, 75,
+               'fast_run', 'inplace','gpu_inplace', 'gpu')
 
 @register_opt()
 @local_optimizer([tensor.Alloc])

theano/tensor/opt.py

@@ -107,14 +107,14 @@ theano.configparser.AddConfigVar('tensor.insert_inplace_optimizer_validate_nb',
         theano.configparser.IntParam(-1),
         in_c_key=False)
 
-def insert_inplace_optimizer_op(OP):
+def inplace_elemwise_optimizer_op(OP):
     """
     We parametrise it to make it work for Elemwise and GpuElemwise op.
     """
     @gof.optimizer
-    def insert_inplace_optimizer(env):
+    def inplace_elemwise_optimizer(env):
         """
-        Usage: inplace_optimizer.optimize(env)
+        Usage: inplace_elemwise_optimizer.optimize(env)
 
         Attempts to replace all Broadcast ops by versions of them
         that operate inplace. It operates greedily: for each Broadcast
@@ -193,7 +193,7 @@ def insert_inplace_optimizer_op(OP):
 
                         for r,new_r in zip(node.outputs,new.outputs):
                             env.replace(r,new_r,
-                                        reason="insert_inplace_optimizer")
+                                        reason="inplace_elemwise_optimizer")
                         nb_change_no_validate +=1
                         if nb_change_no_validate >= validate_each_change:
                             env.validate()
@@ -218,11 +218,11 @@ def insert_inplace_optimizer_op(OP):
                 if not raised_warning:
                     print >> sys.stderr, "Their was some inplace optimization that was not done due to unexpected error"
                 env.revert(chk)
-    return insert_inplace_optimizer
+    return inplace_elemwise_optimizer
 
-insert_inplace_optimizer = insert_inplace_optimizer_op(T.Elemwise)
+inplace_elemwise_optimizer = inplace_elemwise_optimizer_op(T.Elemwise)
 
-compile.optdb.register('inplace_opt', insert_inplace_optimizer, 75, 'fast_run', 'inplace')
+compile.optdb.register('inplace_opt', inplace_elemwise_optimizer, 75, 'fast_run', 'inplace')
 
 def register_canonicalize(lopt, *tags, **kwargs):
     name = (kwargs and kwargs.pop('name')) or lopt.__name__