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# Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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 nnunet.training.network_training.nnUNetTrainerV2 import nnUNetTrainerV2
from nnunet.training.optimizer.ranger import Ranger
class nnUNetTrainerV2_Ranger_lr1en2(nnUNetTrainerV2):
def __init__(self, plans_file, fold, output_folder=None, dataset_directory=None, batch_dice=True, stage=None,
unpack_data=True, deterministic=True, fp16=False):
super().__init__(plans_file, fold, output_folder, dataset_directory, batch_dice, stage, unpack_data,
deterministic, fp16)
self.initial_lr = 1e-2
def initialize_optimizer_and_scheduler(self):
self.optimizer = Ranger(self.network.parameters(), self.initial_lr, k=6, N_sma_threshhold=5,
weight_decay=self.weight_decay)
self.lr_scheduler = None
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