Early Stopping in PyTorch

vision
1

Where can I find Early Stopping in PyTorch 0.4. Please point me ?
Thanks

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2

Torchsample provides an implementation of early stopping.

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3

Is it available in 0.4 ?
I am getting "ModuleNotFoundError: No module named ‘torchsample’ " error.
I couldn’t find it in documentation either, please point me to the documentation if it is available.
Thank you.

4

No, it was a standalone repo, but it seems to be abandoned.

EDIT: Ignite seems to have an implementation of early stopping here.

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5

Here is my implementation, it should be easy to read and customize it.

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6

I’ve implemented early stopping for PyTorch and made an example that shows how to use it; you can check it out here.

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7

Thank you for your script. It works well. I was wondering what if the loss validation is decreasing very slightly over epochs ( ie delta validation loss < 1e-4 for instance). Does the model stop learning in your case?

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8

You are welcome! No, it does not have this functionality. Feel free to submit a pull request if you implement this feature.

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9

useful and very easy to use.

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10

Is there any official implementation in pytorch1.x?

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11

Hi, I have a suggestion for your implementation.

Wouldn’t it be more apt to store context as well along with the model during saving & loading a general checkpoint for inference and/or resuming training?

torch.save({
            'epoch': epoch,
            'model_state_dict': model.state_dict(),
            'optimizer_state_dict': optimizer.state_dict(),
            'loss': loss,
            ...
            }, PATH)
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13

Yes, I totally agree, feel free to submit a pull request if you implement this feature.

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14

Just implemented this feature and made a pull request. Thank you for writing the original library, it definitely came in handy!

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15

can you please add setup.by to your script so others can install it via pip?