e6ec是最后一版可以使用的，在onnx_modifier.py中必须有import parse_tensor才行，不然下载不了修改的模型，windows上的exe没有试不知道，再增加一个resort脚本，必须过一遍，不然会出错

onnx_resort_node.py

@@ -0,0 +1,76 @@
+
+import onnx
+from onnx import helper
+from onnx import AttributeProto, TensorProto, GraphProto
+import time
+import sys
+
+def check_update_model(model):
+    if (model.graph.name == ''):
+        model.graph.name = 'tackle_checker_error'
+        
+    try:
+        onnx.checker.check_model(model)
+    except onnx.checker.ValidationError as e:
+        print("model is invalid: %s"%(e))
+        # 目前只考虑这个错误“ Nodes in a graph must be topologically sorted, however input ...”，
+        # 就是模型的节点顺序有问题，onnxruntime 是可以推断的，为了其他引擎比如 trt可以推断，调整一下节点顺序。
+    else:
+        time.sleep(1)
+        print("模型正常，返回原模型")
+        return model
+            
+    print('update model ...')
+    new_model = onnx.ModelProto(ir_version=model.ir_version,
+                                producer_name=model.producer_name,
+                                producer_version=model.producer_version,
+                                opset_import=model.opset_import)
+    
+    new_model.graph.name = model.graph.name
+    # 只考虑模型是单输入单输出的情况。
+    # 这里不需要 copy.deepcopy(model.graph.input[0]), python 是写时copy。\
+    list_total_input_name = []
+    for inp in model.graph.input:
+        new_model.graph.input.append(inp)
+        list_total_input_name.append(inp.name)
+    for oup in model.graph.output:
+        new_model.graph.output.append(oup)
+    
+
+    for weight in model.graph.initializer:
+        new_model.graph.initializer.append(weight)
+        list_total_input_name.append(weight.name)
+        
+    list_nodes_invalid = []
+    for node in model.graph.node:
+        node_invalid = False
+        for node_input_name in node.input:
+            if (list_total_input_name.count(node_input_name) == 0):
+                list_nodes_invalid.append(node)
+                node_invalid = True
+                break
+        if (node_invalid):
+            continue
+        for node_output_name in node.output:
+            list_total_input_name.append(node_output_name)
+        new_model.graph.node.append(node)
+    
+    for node in list_nodes_invalid:
+        for node_input_name in node.input:
+            assert list_total_input_name.count(node_input_name) > 0
+        for node_output_name in node.output:
+            list_total_input_name.append(node_output_name)
+        new_model.graph.node.append(node)
+        
+    return new_model
+
+
+if __name__ == "__main__":  
+    onnx_in_name = sys.argv[1]
+    onnx_out_name = sys.argv[2]
+
+    onnx_model = onnx.load(onnx_in_name)
+    new_model = check_update_model(onnx_model)
+    onnx.checker.check_model(new_model)
+
+    onnx.save(new_model, onnx_out_name)