rm params

x2paddle/optimizer/fusion/trace_fc_fuser.py

@@ -113,11 +113,13 @@ class TraceFcFuser(FuseBase):
         attrs["out_features"] = parameters[weight_name].shape[0]
         linear_name = "linear{}".format(self.linear_index)
         self.linear_index += 1
-        weight_numpy = parameters.pop(weight_name)
+        weight_numpy = parameters[weight_name]
         parameters["{}.weight".format(linear_name)] = weight_numpy.transpose(
             (1, 0))
-        bias_numpy = parameters.pop(bias_name)
+        self.rm_params.add(weight_name)
+        bias_numpy = parameters[bias_name]
         parameters["{}.bias".format(linear_name)] = np.squeeze(bias_numpy)
+        self.rm_params.add(bias_name)
         new_layer = PaddleLayer(
             layers_id[0],
             "paddle.nn.Linear",

x2paddle/optimizer/pattern_matcher.py

@@ -325,6 +325,7 @@ class FuseBase(object):
     def __init__(self):
         self.pattern = PaddleGraph()
         self.patterns = list()
+        self.rm_params = set()
 
     def operate(self, graph, match_kind="topo"):
         parameters = graph.parameters
@@ -335,6 +336,8 @@ class FuseBase(object):
             subgraph = get_subgraph("", first_layer_id, graph)
             self.insert_new_layer(subgraph, parameters, match)
         self.delete_match(graph)
+        for param_name in self.rm_params:
+            parameters.pop(param_name)
         graph.build()
 
     def perform_pattern_matcher(self, graph, match_kind="topo"):