Solved the same data is used for multiple OPs. (#728)

* add scatter mapper

* solve same param is used for multiple OPs

* Add unique_name support

* Simplified code

* Add PR link

* fixed bug for CI

x2paddle/op_mapper/onnx2paddle/opset9/opset.py

@@ -45,7 +45,8 @@ def _const_weight_or_none(node, necessary=False):
 def _rename_or_remove_weight(weights,
                              origin_name,
                              target_name=None,
-                             is_remove=True):
+                             is_remove=True,
+                             rename_mapper=None):
     '''
     Rename parameters by Paddle's naming rule of parameters.
 
@@ -56,13 +57,16 @@ def _rename_or_remove_weight(weights,
             {target_name:weights[origin_name]} to weights, and target_name must follow paddle's
             naming rule of parameters. Default: None.
         is_remove: if is_remove is True, remove origin key-value pair. Default: True.
+        rename_mapper: Solved the same data is used for multiple OPs, key is old_name, value is new_name.
     Returns:
         None
     '''
+    if rename_mapper is not None and origin_name in rename_mapper:
+        origin_name = rename_mapper[origin_name]
+        is_remove = False
     if origin_name not in weights:
         raise KeyError('{} not a key in {}'.format(origin_name, weights.keys()))
     if is_remove:
-        # TODO There may be problems when the same data is used as an argument to multiple OPs.
         # remove weight
         data = weights.pop(origin_name)
     else:
@@ -70,6 +74,7 @@ def _rename_or_remove_weight(weights,
     if target_name is not None:
         # rename weight
         weights[target_name] = data
+        rename_mapper[origin_name] = target_name
 
 
 def _is_static_shape(shape):
@@ -182,6 +187,9 @@ class OpSet9():
         self.weights = dict()
         self.nn_name2id = dict()
         self.done_weight_list = list()
+        # solve for same data is used as an argument to multiple OPs.
+        # PR link(wangjunjie06): https://github.com/PaddlePaddle/X2Paddle/pull/728
+        self.rename_mapper = dict()
 
     @print_mapping_info
     def directly_map(self, node, *args, **kwargs):
@@ -1680,13 +1688,27 @@ class OpSet9():
         epsilon = node.get_attr('epsilon', 1e-5)
         c = val_x.out_shapes[0][1]
 
-        _rename_or_remove_weight(self.weights, val_scale.name,
-                                 op_name + '.weight')
-        _rename_or_remove_weight(self.weights, val_b.name, op_name + '.bias')
-        _rename_or_remove_weight(self.weights, val_var.name,
-                                 op_name + '._variance')
-        _rename_or_remove_weight(self.weights, val_mean.name,
-                                 op_name + '._mean')
+        # solved the same data is used as an argument to multiple OPs.
+        _rename_or_remove_weight(
+            self.weights,
+            val_scale.name,
+            op_name + '.weight',
+            rename_mapper=self.rename_mapper)
+        _rename_or_remove_weight(
+            self.weights,
+            val_b.name,
+            op_name + '.bias',
+            rename_mapper=self.rename_mapper)
+        _rename_or_remove_weight(
+            self.weights,
+            val_var.name,
+            op_name + '._variance',
+            rename_mapper=self.rename_mapper)
+        _rename_or_remove_weight(
+            self.weights,
+            val_mean.name,
+            op_name + '._mean',
+            rename_mapper=self.rename_mapper)
 
         # Attribute: spatial is used in BatchNormalization-1,6,7
         spatial = bool(node.get_attr('spatial'))
@@ -2228,14 +2250,22 @@ class OpSet9():
         remove_weight = True if val_w.name in self.done_weight_list else False
         if remove_weight:
             self.done_weight_list.append(val_w.name)
-        _rename_or_remove_weight(self.weights, val_w.name, op_name + '.weight',
-                                 remove_weight)
+        _rename_or_remove_weight(
+            self.weights,
+            val_w.name,
+            op_name + '.weight',
+            remove_weight,
+            rename_mapper=self.rename_mapper)
         if has_bias:
             remove_bias = True if val_b.name in self.done_weight_list else False
             if remove_bias:
-                self.done_weight_list.append(val_b_name)
-            _rename_or_remove_weight(self.weights, val_b.name,
-                                     op_name + '.bias', remove_bias)
+                self.done_weight_list.append(val_b.name)
+            _rename_or_remove_weight(
+                self.weights,
+                val_b.name,
+                op_name + '.bias',
+                remove_bias,
+                rename_mapper=self.rename_mapper)
         else:
             layer_attrs["bias_attr"] = False
         if reduce(lambda x, y: x * y,
@@ -2355,10 +2385,14 @@ class OpSet9():
         _rename_or_remove_weight(
             self.weights,
             val_w.name,
-            op_name + '.weight', )
+            op_name + '.weight',
+            rename_mapper=self.rename_mapper)
         if val_b is not None:
-            _rename_or_remove_weight(self.weights, val_b.name,
-                                     op_name + '.bias')
+            _rename_or_remove_weight(
+                self.weights,
+                val_b.name,
+                op_name + '.bias',
+                rename_mapper=self.rename_mapper)
         else:
             layer_attrs["bias_attr"] = False
         self.paddle_graph.add_layer(

x2paddle/project_convertor/pytorch/torch2paddle/nn_init.py

@@ -15,7 +15,7 @@
 import math
 from functools import reduce
 import paddle
-from paddle.fluid import framework
+from paddle.fluid import framework, unique_name
 from paddle.fluid.core import VarDesc
 from paddle.fluid.initializer import XavierInitializer, MSRAInitializer
 from paddle.fluid.data_feeder import check_variable_and_dtype