fix

x2paddle/core/program.py

@@ -285,12 +285,12 @@ 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:
+#             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

x2paddle/op_mapper/dygraph/pytorch2paddle/aten.py

@@ -1310,7 +1310,6 @@ def aten_dim(mapper, graph, node):
     """
     scope_name = mapper.normalize_scope_name(node)
     output_name = mapper._get_outputs_name(node)[0]
-    layer_outputs = [output_name]
     layer_inputs = {}
     inputs_name, inputs_node = mapper._get_inputs_name(node)
     # 获取当前节点输出的list
@@ -1322,9 +1321,9 @@ def aten_dim(mapper, graph, node):
     current_inputs = list(layer_inputs.values())
 
     graph.add_layer(
-        "prim.shape", inputs=layer_inputs, outputs=layer_outputs, scope_name=scope_name)
+        "prim.shape", inputs=layer_inputs, outputs=[output_name], scope_name=scope_name)
     graph.add_layer(
-        "prim.len", inputs={"input": output_name}, outputs=layer_outputs, scope_name=scope_name)
+        "prim.len", inputs={"input": output_name}, outputs=[output_name], scope_name=scope_name)
     return current_inputs, current_outputs
 
 
@@ -4512,10 +4511,10 @@ def aten_upsample_bilinear2d(mapper, graph, node):
                             current_outputs, scope_name)
         layer_inputs["align_corners"] = inputs_name[2]
         current_inputs.append(inputs_name[2])
-    if "size" in layer_attrs and layer_attrs["size"] is None:
-        mapper._check_input(graph, inputs_node[3], inputs_name[3],
-                            current_outputs, scope_name)
-        layer_inputs["scale_factor"] = inputs_name[3]
+#     if "size" in layer_attrs and layer_attrs["size"] is None:
+#     mapper._check_input(graph, inputs_node[3], inputs_name[3],
+#                         current_outputs, scope_name)
+#     layer_inputs["scale_factor"] = inputs_name[3]
     layer_attrs["align_mode"] = 0
     layer_attrs["mode"] = string("bilinear")
     graph.add_layer(

x2paddle/op_mapper/dygraph/pytorch2paddle/prim2code.py

@@ -471,7 +471,7 @@ def prim_str(layer, indent=1, init_func=[], forward_func=[], layer_id=None, diff
 
 
 def prim_sub(layer, indent=1, init_func=[], forward_func=[], layer_id=None, different_attrs=None):
-    if int(get_value(layer, "alpha", different_attrs)) == 1:
+    if int(float(get_value(layer, "alpha", different_attrs))) == 1:
         line = "{} = {} - {}".format(layer.outputs[0],
                                      get_value(layer, "x", different_attrs), 
                                      get_value(layer, "y", different_attrs))

x2paddle/optimizer/fusion/dygraph/interpolate_bilinear_fuser.py

@@ -186,6 +186,7 @@ class DygraphInterpolateBilinearFuser(FuseBase):
             inputs={
                 "input": "interpolate-input-0",
                 "size": "interpolate-input-3",
+#                 "scale_factor": gen_name(21)
             },
             outputs=[gen_name(23)])
         pattern_block_block.add_layer(

x2paddle/optimizer/optimizer.py

@@ -28,11 +28,11 @@ class GraphOptimizer(object):
                     "dygraph_constant_fuse_pass", 
                     "dygraph_batchnorm2d_fuse_pass",
                     "dygraph_interpolate_bilinear_fuse_pass", 
-                    "dygraph_fc_fuse_pass",
-                    "dygraph_adaptive_pool2d_fuse_pass", 
-                    "dygraph_reshape_fuse_pass",
-                    "dygraph_dropout_fuse_pass",
-                    "dygraph_if_fuse_pass"
+#                     "dygraph_fc_fuse_pass",
+#                     "dygraph_adaptive_pool2d_fuse_pass", 
+#                     "dygraph_reshape_fuse_pass",
+#                     "dygraph_dropout_fuse_pass",
+#                     "dygraph_if_fuse_pass"
                 ]
         elif source_frame == "caffe":
             if paddle_type == "dygraph":

x2paddle/optimizer/pattern_matcher.py

@@ -130,6 +130,8 @@ class PatternMatcher(object):
                                 if is_pop:
                                     subgraph_id2layers.pop(layer_id)
                                     continue
+                    if layer_id not in subgraph_id2layers:
+                        continue
                     # 当为控制流时的处理
                     if layer.kernel == "prim.if" or layer.kernel == "prim.loop":
                         if len(pattern_layer.blocks) != len(layer.blocks):
@@ -154,6 +156,7 @@ class PatternMatcher(object):
                             if pattern_index == 0 or is_subblock:
                                 return False
                             else:
+                                print(subgraph_id2layers.keys())
                                 index = list(subgraph_id2layers.keys()).index(
                                     layer_id)
                                 for key in list(subgraph_id2layers.keys())[