fix2pass.py

import onnx
import onnx_graphsurgeon as gs
from collections import OrderedDict

encoder = onnx.load("model/encoder.onnx")
graph = gs.import_onnx(encoder)
Unsqueeze_29 = Not_30 = Slice_79 = Slice_84 = None
for node in graph.nodes:
    if node.op == 'Unsqueeze' and node.name == "Unsqueeze_29":
        Unsqueeze_29 = node
    if node.op == 'Not' and node.name == 'Not_30':
        Not_30 = node
    if node.op == 'Slice' and node.name == "Slice_79":
        Slice_79 = node
    if node.op == 'Slice' and node.name == "Slice_84":
        Slice_84 = node
start_node = Unsqueeze_29.outputs[0]
Unsqueeze_29_Cast_output = gs.Variable(name="Unsqueeze_29_Cast_output", dtype=None, shape=None)
attrs_dict = {}
attrs_dict['to'] = 6
newNode = gs.Node(name="Slice_79_Cast", op="Cast", inputs=[start_node],
                  outputs=[Unsqueeze_29_Cast_output], attrs=attrs_dict)
graph.nodes.append(newNode)  # 记得把新节点加入计算图中

Slice_79.inputs[0] = Unsqueeze_29_Cast_output
Slice_84_outputs = Not_30.outputs[0]
end_node = Slice_84.outputs[0]
Not_30.outputs[0] = end_node
Slice_84.outputs[0] = Slice_84_outputs
Not_30.inputs[0] = Slice_84.outputs[0]

Slice_84_Cast_output = gs.Variable(name="Slice_84_Cast_output", dtype=None, shape=None)
newNode = gs.Node(name="Slice_84_Cast", op="Cast", inputs=[Slice_84_outputs],
                  outputs=[Slice_84_Cast_output], attrs=OrderedDict(to=9))
graph.nodes.append(newNode)  # 记得把新节点加入计算图中
Not_30.inputs[0] = Slice_84_Cast_output
graph.cleanup().toposort()
onnx.save(gs.export_onnx(graph), "./encoder_fix_for_pass.onnx")