Official implementation for (Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching, AAAI-2021)

Related tags

Deep Learning attention-feature-distillation
Overview

Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching

Official pytorch implementation of "Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching" (AAAI-2021)

Requirements

  • Python3
  • PyTorch (> 1.2.0)
  • torchvision
  • numpy
  • Pillow

Training

We include a trained WRN-40-2 parameters at /trained/wrn40x2/model.pth.
Run main.py with student network as WRN-16-2 and teacher as WRN-40-2 to reproduce experiment result on CIFAR100.

python main.py --data_dir PATH_TO_DATA --data CIFAR100 --trained_dir /trained/wrn40x2/model.pth\
 --model wrn16x2 --model_t wrn40x2 --beta 200

License

Copyright 2021-present NAVER Corp.

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.
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Comments
  • ReLu and identity activation functions

    ReLu and identity activation functions

    Hello! Thank you for opening your implementation <3

    According to the paper:

    Also, we utilize the identity and ReLU function as the activation function of the query and key, respectively. The kernel size and stride are determined according to the size of the student feature and teacher feature

    Which of the activation functions works better? In your code ReLu is disabled, also you have self.relu = nn.ReLU(inplace=False) in LinearTransformStudent class but has never been used

    opened by RedHash 0
Owner
Clova AI Research
Open source repository of Clova AI Research, NAVER & LINE
Clova AI Research
GitHub
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