fix3

x2paddle/core/program.py

@@ -285,14 +285,14 @@ class PaddleGraph(object):
             hierarchical_tree.save_source_files(save_dir)
             self.dump_dygraph_parameter(save_dir)
         else:
-            if self.source_type == "pytorch":
-                from x2paddle.optimizer.pytorch_code_optimizer import ModuleGraph
-                module_graph = ModuleGraph(self)
-                module_graph.save_source_files(save_dir)
-                self.dump_dygraph_parameter(save_dir)
-            else:
-                self.gen_dygraph_code(save_dir)
-                self.dump_dygraph_parameter(save_dir)
+#             if self.source_type == "pytorch":
+#                 from x2paddle.optimizer.pytorch_code_optimizer import ModuleGraph
+#                 module_graph = ModuleGraph(self)
+#                 module_graph.save_source_files(save_dir)
+#                 self.dump_dygraph_parameter(save_dir)
+#             else:
+            self.gen_dygraph_code(save_dir)
+            self.dump_dygraph_parameter(save_dir)
         # 动转静
         code_path = osp.join(osp.abspath(save_dir), "x2paddle_code.py")
         print("Exporting inference model from python code ('{}')... \n".format(code_path))

x2paddle/op_mapper/dygraph/pytorch2paddle/prim2code.py

@@ -182,7 +182,7 @@ def prim_equal(layer, indent=1, init_func=[], forward_func=[], layer_id=None, di
 
 
 def prim_exception(layer, indent=1, init_func=[], forward_func=[], layer_id=None, different_attrs=None):
-    line = "raise RaiseException({})".format(get_value(layer, "input", different_attrs))
+    line = "raise Exception({})".format(get_value(layer, "input", different_attrs))
     forward_func.extend(gen_codes([line], indent=indent))
 
 
@@ -458,10 +458,12 @@ def prim_slice(layer, indent=1, init_func=[], forward_func=[], layer_id=None, di
     forward_func.extend(gen_codes([line], indent=indent))
     
     
-def prim_startswith(layer, indent=1, init_func=[], forward_func=[], layer_id=None, different_attrs=None):
+def prim_startswith(layer, indent=1, init_func=[], forward_func=[], layer_id=None, different_attrs=None, is_return_line=False):
     line = "{} = {}.startswith({})".format(layer.outputs[0],
                                            get_value(layer, "input", different_attrs),
                                            get_value(layer, "start_str", different_attrs))
+    if is_return_line:
+        return line.split(" = ")[1]
     forward_func.extend(gen_codes([line], indent=indent))
 
 

x2paddle/optimizer/fusion/dygraph/if_fuser.py

@@ -41,13 +41,21 @@ class DygraphIfFuser(FuseBase):
             return 
         for id in graph.edges_in[layer_id]:
             input_layer = graph.layers[id]
+            input_layer_id = id
             if input_layer.outputs == [layer.inputs["input"]]:
                 if input_layer.kernel == "prim.if":
                     matches.pop(layer_id)
                     return
                 input_id = id
                 break
+        if list(layer.inputs.values()).count(input_layer.outputs[0]) > 1 or \
+               (input_layer_id in graph.edges_out and len(graph.edges_out[input_layer_id]) > 1):
+            matches.pop(layer_id)
+            return
         func_name = input_layer.kernel.replace(".", "_")
+        if func_name in ["prim_if", "prim_loop"]:
+            matches.pop(layer_id)
+            return
         from x2paddle.op_mapper.dygraph.pytorch2paddle import prim2code
         func = getattr(prim2code, func_name)
         line = func(input_layer, is_return_line=True)