File size: 1,432 Bytes
7b7527a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 |
# Copyright (c) 2022 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.
from ppdet.core.workspace import create
from ppdet.utils.logger import setup_logger
logger = setup_logger('ppdet.engine')
from . import Trainer
__all__ = ['TrainerCot']
class TrainerCot(Trainer):
"""
Trainer for label-cotuning
calculate the relationship between base_classes and novel_classes
"""
def __init__(self, cfg, mode='train'):
super(TrainerCot, self).__init__(cfg, mode)
self.cotuning_init()
def cotuning_init(self):
num_classes_novel = self.cfg['num_classes']
self.load_weights(self.cfg.pretrain_weights)
self.model.eval()
relationship = self.model.relationship_learning(self.loader, num_classes_novel)
self.model.init_cot_head(relationship)
self.optimizer = create('OptimizerBuilder')(self.lr, self.model)
|