| 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758 |
- # Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
- #
- # 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 os
- from pathlib import Path
- from ..base import BaseEvaluator
- from .model_list import MODELS
- class SegEvaluator(BaseEvaluator):
- """Semantic Segmentation Model Evaluator"""
- entities = MODELS
- def update_config(self):
- """update evaluation config"""
- self.pdx_config.update_dataset(self.global_config.dataset_dir, "SegDataset")
- self.pdx_config.update_pretrained_weights(None, is_backbone=True)
- def get_config_path(self, weight_path):
- """
- get config path
- Args:
- weight_path (str): The path to the weight
- Returns:
- config_path (str): The path to the config
- """
- config_path = Path(weight_path).parent.parent / "config.yaml"
- return config_path
- def get_eval_kwargs(self) -> dict:
- """get key-value arguments of model evaluation function
- Returns:
- dict: the arguments of evaluation function.
- """
- device = self.get_device()
- # XXX:
- os.environ.pop("FLAGS_npu_jit_compile", None)
- return {"weight_path": self.eval_config.weight_path, "device": device}
|