evaluator.py 1.8 KB

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  1. # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
  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. import os
  15. from pathlib import Path
  16. from ..base import BaseEvaluator
  17. from .model_list import MODELS
  18. class SegEvaluator(BaseEvaluator):
  19. """ Semantic Segmentation Model Evaluator """
  20. entities = MODELS
  21. def update_config(self):
  22. """update evalution config
  23. """
  24. self.pdx_config.update_dataset(self.global_config.dataset_dir,
  25. "SegDataset")
  26. self.pdx_config.update_pretrained_weights(None, is_backbone=True)
  27. def get_config_path(self, weight_path):
  28. """
  29. get config path
  30. Args:
  31. weight_path (str): The path to the weight
  32. Returns:
  33. config_path (str): The path to the config
  34. """
  35. config_path = Path(weight_path).parent.parent / "config.yaml"
  36. return config_path
  37. def get_eval_kwargs(self) -> dict:
  38. """get key-value arguments of model evalution function
  39. Returns:
  40. dict: the arguments of evaluation function.
  41. """
  42. device = self.get_device()
  43. # XXX:
  44. os.environ.pop("FLAGS_npu_jit_compile", None)
  45. return {"weight_path": self.eval_config.weight_path, "device": device}