"""
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 argparse
import torch.nn.parallel
import torch.utils.data
import sys
sys.path.append('./pointnet.pytorch')
from pointnet.model import PointNetCls


def pth2onnx(opt):
    classifier = PointNetCls(k=opt.num_classes, feature_transform=opt.feature_transform, device=opt.device)
    if opt.model != '':
        classifier.load_state_dict(torch.load(opt.model, map_location='cpu')['model_state_dict'])
    classifier.eval()

    input_names = ["input"]
    output_names = ["class"]
    dynamic_axes = {'input': {0: '-1'}, 'class': {0: '-1'}}

    dummy_input = torch.randn(1, 3, 2500)

    torch.onnx.export(
        classifier, dummy_input, opt.output_file, dynamic_axes=dynamic_axes,
        input_names=input_names, output_names=output_names, verbose=True, opset_version=11)


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--device', type=str, default='cpu')
    parser.add_argument('--num_classes', type=int, default=16)
    parser.add_argument('--model', type=str, default='./checkpoint_79_epoch.pkl', help='model path')
    parser.add_argument('--output_file', type=str, default='./pointnet.onnx', help='output path')
    parser.add_argument('--feature_transform', type=bool, default=True, help="use feature transform")
    opt = parser.parse_args()
    pth2onnx(opt)