remove extra code of onnx_optimizer

x2paddle/optimizer/onnx_optimizer.py

@@ -29,65 +29,3 @@ class ONNXOptimizer(object):
                 omit_freq = self.op_mapper.omit_nodes.count(node_name)
                 if len(node.outputs) <= omit_freq:
                     node.fluid_code.clear()
-
-    # TODO activation merge
-    def merge_activation(self):
-        act_nodes = list()
-        for node_name in self.graph.topo_sort:
-            node = self.graph.get_node(node_name)
-            if node.layer_type in self.activation_ops:
-                act_nodes.append(node_name)
-
-        for act_node_name in act_nodes:
-            node = self.graph.get_node(act_node_name)
-            input = self.graph.get_node(node.inputs[0])
-            if input.layer_type not in self.layers_with_act:
-                continue
-            if len(input.fluid_code.layers) == 0:
-                continue
-            if 'act' in input.fluid_code.layers[
-                    -1].param_attr and input.fluid_code.layers[-1].param_attr[
-                        'act'] is not None:
-                continue
-            if len(input.outputs) != 1:
-                continue
-            input.fluid_code.layers[-1].param_attr['act'] = string(
-                self.activation_ops[node.layer_type])
-            input.fluid_code.layers[-1].output = node.fluid_code.layers[
-                0].output
-            self.graph.remove_node(act_node_name)
-
-    # TODO bias merge
-    def merge_bias(self):
-        for node_name in self.graph.topo_sort:
-            node = self.graph.get_node(node_name)
-            if node.layer_type == "BiasAdd":
-                input = self.graph.get_node(node.inputs[0])
-                if input.layer_type not in self.layers_with_bias:
-                    continue
-                if len(input.outputs) != 1:
-                    continue
-                if len(input.fluid_code.layers) == 0:
-                    continue
-                bias_with_act = False
-                if 'act' in node.fluid_code.layers[-1].param_attr:
-                    bias_with_act = True
-                layer_with_act = False
-                if 'act' in input.fluid_code.layers[
-                        -1].param_attr and input.fluid_code.layers[
-                            -1].param_attr['act'] is not None:
-                    layer_with_act = True
-
-                if bias_with_act and layer_with_act:
-                    continue
-                if not input.fluid_code.layers[-1].param_attr['bias_attr']:
-                    bias_name = node.inputs[1]
-                    input.fluid_code.layers[-1].param_attr[
-                        'bias_attr'] = string(bias_name)
-                    input.fluid_code.layers[-1].output = node.fluid_code.layers[
-                        0].output
-                    if bias_with_act:
-                        input.fluid_code.layers[-1].param_attr[
-                            'act'] = node.fluid_code.layers[-1].param_attr[
-                                'act']
-                    node.fluid_code.clear()