Currently, some public classes are not documented anywhere because we didn't create the corresponding doc pages. Those missing pages are:

• Benchmark classes
• Bert Japanese
• Bertweet
• Data collators
• Herbert
• Phoebert

If someone feels like working on one of those, please tag yourself with a comment on this issue. Once the objects are properly documented, they can be removed from th

some recordings have low volume so the output can be sometimes really quiet. how about we add a volume bar so we can make the output louder/quieter?

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Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

🚀 Feature

add/fix typing in all PL codebase, this will yield in multiple PR as we prefer to split the work into smaller peace

Additional context

in #5021 we introduced a new ignore list so after it is merged, take out a single ignored item and fix typing for that part

each item + its fix = one PR

Sections

• pytorch_lightning.callbacks.*
• pytorch_lightning.c

more details at: allenai/allennlp#2264 (comment)

Bug Report

These tests were run on s390x. s390x is big-endian architecture.

Failure log for helper_test.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________

self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>

    def test_make_tensor(self):  # type: () -> None
    

What would you like to be added: As title

Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.

**Without this feature, how does current nni