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Metrics: Machine learning metrics for distributed, scalable PyTorch applications.
Flash: The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning
Bolts: Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Lightning Transformers: Flexible interface for high performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.
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Thanks @carmocca
I have a branch where I started the dataloader removal a while ago.
Have you already started? This one is going to be a bit of effort. Saved it for last.
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Proposed refactoring or deprecation
See title
Motivation
The
InternalDebugger
is legacy and lets us to write bad code. The code should be structured in a way that enables testing.Pitch
InternalDebugger.track_lr_schedulers_update
#9653InternalDebugger.track_event
#9654InternalDebugger.track_load_dataloader_call
#9675InternalDebugger
#9680Additional context
Discussed in #8895
If you enjoy Lightning, check out our other projects! ⚡
Metrics: Machine learning metrics for distributed, scalable PyTorch applications.
Flash: The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning
Bolts: Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Lightning Transformers: Flexible interface for high performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.
The text was updated successfully, but these errors were encountered: