"""
Copyright 2020 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 torch
import torchvision
from senet import se_resnet50
import torch.onnx
from collections import OrderedDict


def proc_node_module(checkpoint, AttrName):
    new_state_dict = OrderedDict()
    for k, v in checkpoint[AttrName].items():
        if(k[0:7] == "module."):
            name = k[7:]
        else:
            name = k[0:]
        new_state_dict[name] = v
    return new_state_dict


def convert():
    checkpoint = torch.load("./checkpoint.pth.tar", map_location='cpu')
    checkpoint['state_dict'] = proc_node_module(checkpoint, 'state_dict')
    model = se_resnet50()
    model.load_state_dict(checkpoint['state_dict'])
    model.eval()
    print(model)

    input_names = ["actual_input_1"]
    output_names = ["output1"]
    dummy_input = torch.randn(16, 3, 224, 224)
    torch.onnx.export(model, dummy_input, "se_resnet50_npu_16.onnx"
                     , input_names=input_names, output_names=output_names
                     , opset_version=11)


if __name__ == "__main__":
    convert()