pytorch
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We keep this issue open to collect feature requests from users and hear your voice. Our monthly release plan is also available here.
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I am training 5-fold CV with PyTorch Lightning in a for loop. I am also logging all the results to wandb. I want wanbd to reinitalize the run after each fold, but it seems to continue with the same run and it logs all the results to the same run. I also tried passing kwargs in the WandbLogger as mentioned in the docs [here](https://pytorch-lightning.readthedocs.io/en/stable/extensions/generated/py
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Change tensor.data
to tensor.detach()
due to
pytorch/pytorch#6990 (comment)
tensor.detach()
is more robust than tensor.data
.
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New Operator
Describe the operator
Why is this operator necessary? What does it accomplish?
This is a frequently used operator in tensorflow/keras
Can this operator be constructed using existing onnx operators?
If so, why not add it as a function?
I don't know.
Is this operator used by any model currently? Which one?
Are you willing to contribute it?
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Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict
command opens the file and reads lines for the Predictor
. This fails when it tries to load data from my compressed files.
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https://github.com/huggingface/transformers/blob/546dc24e0883e5e9f5eb06ec8060e3e6ccc5f6d7/src/transformers/models/gpt2/modeling_gpt2.py#L698
Assertions can't be relied upon for control flow because they can be disabled, as per the following: