basically a copy of Lightning-AI/torchmetrics#744 which was addressed in Lightning-AI/torchmetrics#749

🚀 Feature

see suggestion in Lightning-AI/torchmetrics#740 (comment)

Motivation

most of the deprecations in TM are meant to users not developers

Pitch

Replace DeprecationWarning with FutureWarning defined at:
https://github.com/PyTorchLightning/pytorch-lightning/blob/033dba1494a177954e8ca59bc74b1635e83b9efa/pytorch_lightning/utilities/warnings.py#L44
and remove:
https://github.com/PyTorchLightning/pytorch-lightning/blob/033dba1494a177954e8ca59bc74b1635e83b9efa/pytorch_lightning/utilities/warnings.py#L48-L49

Alternatives

Keep using DeprecationWarning.

Additional context

• exception DeprecationWarning Base class for warnings about deprecated features when those warnings are intended for other Python developers. Ignored by the default warning filters, except in the __main__ module (PEP 565). Enabling the Python Development Mode shows this warning.

• exception FutureWarning Base class for warnings about deprecated features when those warnings are intended for end users of applications that are written in Python.

If you enjoy Lightning, check out our other projects! ⚡

• Metrics: Machine learning metrics for distributed, scalable PyTorch applications.

• Lite: enables pure PyTorch users to scale their existing code on any kind of device while retaining full control over their own loops and optimization logic.

• Flash: The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, fine-tuning, 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.

cc @Borda