fix the tf bug

x2paddle/optimizer/elimination/dygraph/transpose_elimination.py

@@ -101,7 +101,7 @@ class DygraphTransposeElimination(FuseBase):
                         if _graph.layers[out].outputs[ouput_index] in _graph.outputs:
                             can_be_optimized = False
                             break
-                        if _graph.layers[out].attrs.get('keepdim', False):
+                        if not _graph.layers[out].attrs.get('keepdim', False):
                             can_be_optimized = False
                             break
                         propagate_layers.append(out)
@@ -148,7 +148,7 @@ class DygraphTransposeElimination(FuseBase):
                             if _graph.layers[out].outputs[output_index] in _graph.outputs:
                                 can_be_optimized = False
                                 break
-                            if _graph.layers[out].attrs.get('keepdim',
+                            if not _graph.layers[out].attrs.get('keepdim',
                                                                 False):
                                 can_be_optimized = False
                                 break
@@ -219,7 +219,7 @@ class DygraphTransposeElimination(FuseBase):
                             if _graph.layers[ipt].outputs[output_index] in _graph.outputs:
                                 can_be_optimized = False
                                 break
-                            if _graph.layers[ipt].attrs.get('keepdim',
+                            if not _graph.layers[ipt].attrs.get('keepdim',
                                                                 False):
                                 can_be_optimized = False
                                 break
@@ -252,7 +252,7 @@ class DygraphTransposeElimination(FuseBase):
                     continue
 
                 for l in transpose_layers:
-                    _graph.delete_layer(l)
+                    _graph.del_layer(l)
 
                 optimized_transpose_layers.extend(transpose_layers)
                 optimized_reduce_layers.extend(reduce_layers)
@@ -268,21 +268,22 @@ class DygraphTransposeElimination(FuseBase):
         while strip_transpose(opt_graph):
             pass
 
-        
         for layer_id in list(set(optimized_transpose_layers)):
-            self.delete_layer_with_associated(graph, layer_id)
+            graph.del_layer(layer_id)
         for layer_id in list(set(optimized_reduce_layers)):
-            dim = graph.layers[layer_id].attrs.get('dim', None)
+            dim = graph.layers[layer_id].attrs.get('axis', None)
             if dim is not None:
                 for i in range(len(dim)):
                     dim[i] = [0, 2, 3, 1][dim[i]]
-                graph.layers[layer_id].attrs['dim'] = dim
+                graph.layers[layer_id].attrs['axis'] = dim
         for layer_id in list(set(optimized_concat_layers)):
             axis = graph.layers[layer_id].attrs.get('axis', 0)
             graph.layers[layer_id].attrs['axis'] = [0, 2, 3, 1][axis]
         for layer_id in list(set(optimized_elementwise_layers)):
             axis = graph.layers[layer_id].attrs.get('axis', -1)
             graph.layers[layer_id].attrs['axis'] = [0, 2, 3, 1][axis]
+            if graph.layers[layer_id].kernel == "paddle.add":
+                graph.layers[layer_id].kernel = "fluid.layers.elementwise_add"
 
         current_transpose_num = self.get_transpose_num(graph)
         print(

x2paddle/optimizer/fusion/dygraph/tf_batchnorm_fuser.py

@@ -24,6 +24,7 @@ class DygraphTFBatchNormFuser(FuseBase):
     def __init__(self):
         self.bn_index = 0
         super(DygraphTFBatchNormFuser, self).__init__(graph_type="dygraph")
+        self.patterns = list()
 
     def build_pattern(self):
         """ 描述需要替换的batchnorm图结构。
@@ -34,57 +35,111 @@ class DygraphTFBatchNormFuser(FuseBase):
         def gen_name(id):
             return "x" + str(id)
 
-        self.pattern.add_layer(
+        pattern = PaddleGraph(graph_type="dygraph")
+        pattern.add_layer(
             "self.create_parameter",
             inputs={},
             outputs=[gen_name(0)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.full",
             inputs={},
             outputs=[gen_name(1)],
             shape=[1])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.add",
             inputs={"x": gen_name(0), "y": gen_name(1)},
             outputs=[gen_name(2)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.rsqrt",
             inputs={"x": gen_name(2)},
             outputs=[gen_name(3)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "self.create_parameter",
             inputs={},
             outputs=[gen_name(4)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.multiply",
             inputs={"x": gen_name(3), "y": gen_name(4)},
             outputs=[gen_name(5)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "self.create_parameter",
             inputs={},
             outputs=[gen_name(6)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.multiply",
             inputs={"x": gen_name(6), "y": gen_name(5)},
             outputs=[gen_name(7)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "self.create_parameter",
             inputs={},
             outputs=[gen_name(8)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "fluid.layers.elementwise_sub",
             inputs={"x": gen_name(8), "y": gen_name(7)},
             outputs=[gen_name(9)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.multiply",
             inputs={"x": "bn-input-0", "y": gen_name(5)},
             outputs=[gen_name(10)])
-        self.pattern.add_layer(
+        pattern.add_layer(
             "paddle.add",
             inputs={"x": gen_name(10), "y": gen_name(9)},
             outputs=[gen_name(11)])
-        self.pattern.build(inputs={"input-0": "bn-input-0", })
+        pattern.build(inputs={"input-0": "bn-input-0", })
+        self.patterns.append(pattern)
         
+        pattern = PaddleGraph(graph_type="dygraph")
+        pattern.add_layer(
+            "self.create_parameter",
+            inputs={},
+            outputs=[gen_name(0)])
+        pattern.add_layer(
+            "paddle.full",
+            inputs={},
+            outputs=[gen_name(1)],
+            shape=[1])
+        pattern.add_layer(
+            "paddle.add",
+            inputs={"x": gen_name(0), "y": gen_name(1)},
+            outputs=[gen_name(2)])
+        pattern.add_layer(
+            "paddle.rsqrt",
+            inputs={"x": gen_name(2)},
+            outputs=[gen_name(3)])
+        pattern.add_layer(
+            "self.create_parameter",
+            inputs={},
+            outputs=[gen_name(4)])
+        pattern.add_layer(
+            "paddle.multiply",
+            inputs={"x": gen_name(3), "y": gen_name(4)},
+            outputs=[gen_name(5)])
+        pattern.add_layer(
+            "paddle.multiply",
+            inputs={"x": "bn-input-0", "y": gen_name(5)},
+            outputs=[gen_name(10)])
+        pattern.add_layer(
+            "self.create_parameter",
+            inputs={},
+            outputs=[gen_name(6)])
+        pattern.add_layer(
+            "paddle.multiply",
+            inputs={"x": gen_name(6), "y": gen_name(5)},
+            outputs=[gen_name(7)])
+        pattern.add_layer(
+            "self.create_parameter",
+            inputs={},
+            outputs=[gen_name(8)])
+        pattern.add_layer(
+            "fluid.layers.elementwise_sub",
+            inputs={"x": gen_name(8), "y": gen_name(7)},
+            outputs=[gen_name(9)])
+        pattern.add_layer(
+            "paddle.add",
+            inputs={"x": gen_name(10), "y": gen_name(9)},
+            outputs=[gen_name(11)])
+        pattern.build(inputs={"input-0": "bn-input-0", })
+        self.patterns.append(pattern)
 
     def insert_new_layer(self, graph, parameters, matches):
         new_layers, last_layer_id = self.gen_new_layer(matches, parameters, graph)