Comments (6)
You can take this up surely. It's up for grabs !
LR finder is a standard technique whose implementation I have pointed out. Most code is going to be edit of that.
Seems simple, make sure you write the implementation and tests for it as well. Use pytest for tests.
This goes in a separate file called lr_finder.py since it is not role of trainer exactly.
Have a go. I will review it. You can discuss your solution and implementation before hacktober.
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I would stick to PyTorch. This library has to work with torch.
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Hey! I'd like to take this up. I've just familiarized myself with Deep Learning concepts, this seems like a good way to learn. Any suggestions?
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Hey, so this: https://github.com/davidtvs/pytorch-lr-finder shows two methods of how LR finder is used.
We take the model from /pytorch_cnn_trainer/model_factory.py and make it work on our implementation of LR finder in this repository. That should work, right?
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Yes, I guess you get the point. But let me clarify what exactly can be done.
It has a class for LR finder on this line.
I want that to be working with models in this repository, I think the LinearLR
and ExponentialLR
can be used directly from PyTorch itself. Here is source code from PyTorch
It can be used as from torch.optim.lr_schedular import EponentialLR
so we can avoid that code.
Make sure that implementation works with PyTorch 1.6 + as this repository is built for 1.6 + only.
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Alright got it. However, the Arguments for both linearLR and ExponentialLR are different, as shown in https://github.com/davidtvs/pytorch-lr-finder/blob/master/torch_lr_finder/lr_finder.py#L578
and here:
https://github.com/pytorch/pytorch/blob/master/torch/optim/lr_scheduler.py#L434
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Related Issues (18)
- Gradient Penalty for Mixed precision Training
- Move examples to docs
- Pass **kwargs at places
- Add Stochastic Weighted Average (SWA)
- Add Examples for New Features
- Feature Explainable CNNs
- Add Support for multi label classification
- Follow Best Practices while training.
- Turn off NVIDIA Profilers
- PyTorch Lightning trainer
- Train and Valid split for CSVDataset HOT 5
- CSVDataset attributes
- Add history like object as in Keras for plotting
- error when calculate top5_acc with 2 classes HOT 2
- Refactor Tests HOT 1
- Mixed precision training using PyTorch 1.6 HOT 1
- Better Documentation and Testing
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