# Copyright 2021 Huawei Technologies Co., Ltd

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#     http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.





import numpy as np

from auto_optimizer import OnnxGraph

import argparse





parser = argparse.ArgumentParser(description='pth to onnx')

parser.add_argument('--model', type=str, default='d0_bs8_sim.onnx', metavar='N',

                    help='onnx model')

parser.add_argument('--out', type=str, default='d0_bs8_modify.onnx', metavar='N',



                    help='modified onnx')



args = parser.parse_args()

g = OnnxGraph.parse(args.model)

new_ini = g.add_initializer('new_ini', np.array(0).astype(np.float16))

node=g.get_nodes('Pad')[0]

g[node.inputs[2]] = new_ini

g.save(args.out)