renamed optimizer to be more consistent with what other opt name.

theano/sandbox/cuda/opt.py

@@ -611,7 +611,7 @@ def gpu_print_wrapper(op, cnda):
 
 @register_opt()
 @local_optimizer([])
-def local_print_op(node):
+def local_gpu_print_op(node):
     if isinstance(node.op, tensor.printing.Print):
         x, = node.inputs
         if x.owner and x.owner.op == host_from_gpu:

theano/sandbox/multinomial.py

@@ -288,7 +288,7 @@ class GpuMultinomialFromUniform(MultinomialFromUniform):
         """ % locals()
 
 @local_optimizer()
-def use_gpu_multinomial(node):
+def local_gpu_multinomial(node):
     if type(node.op) is MultinomialFromUniform:
         p, u = node.inputs
         m, = node.outputs
@@ -309,5 +309,5 @@ def use_gpu_multinomial(node):
             return [gpu_from_host(ret)]
 
 if cuda_available:
-    register_opt()(use_gpu_multinomial)
+    register_opt()(local_gpu_multinomial)
     pass

theano/sandbox/test_multinomial.py

@@ -12,7 +12,7 @@ def get_mode(gpu):
     mode = get_default_mode()
     mode = copy.copy(mode)
     if gpu:
-        mode = mode.including('gpu', 'gpu_local_optimizations', 'local_cut_gpu_host_gpu', 'use_gpu_multinomial')
+        mode = mode.including('gpu', 'gpu_local_optimizations', 'local_cut_gpu_host_gpu', 'local_gpu_multinomial')
     if isinstance(mode.linker, theano.gof.PerformLinker):
         mode.linker = predefined_linkers['c|py']
     return mode