You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

export.py 1.8 kB

5 years ago
123456789101112131415161718192021222324252627282930313233343536373839404142
  1. # Copyright 2020 Huawei Technologies Co., Ltd
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. # ============================================================================
  15. """export checkpoint file into air models"""
  16. import argparse
  17. import numpy as np
  18. from mindspore import Tensor, context, load_checkpoint, load_param_into_net, export
  19. from src.warpctc import StackedRNN
  20. from src.config import config
  21. context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
  22. if __name__ == '__main__':
  23. parser = argparse.ArgumentParser(description='warpctc_export')
  24. parser.add_argument('--ckpt_file', type=str, default='', help='warpctc ckpt file.')
  25. parser.add_argument('--output_file', type=str, default='', help='warpctc output air name.')
  26. args_opt = parser.parse_args()
  27. captcha_width = config.captcha_width
  28. captcha_height = config.captcha_height
  29. batch_size = config.batch_size
  30. hidden_size = config.hidden_size
  31. net = StackedRNN(captcha_height * 3, batch_size, hidden_size)
  32. param_dict = load_checkpoint(args_opt.ckpt_file)
  33. load_param_into_net(net, param_dict)
  34. net.set_train(False)
  35. image = Tensor(np.zeros([batch_size, 3, captcha_height, captcha_width], np.float16))
  36. export(net, image, file_name=args_opt.output_file, file_format="AIR")