Bump lightning[pytorch-extra] from 2.4.0 to 2.5.0 in /requirements

[dependabot]

Bumps lightning[pytorch-extra] from 2.4.0 to 2.5.0.

Release notes

Sourced from lightning[pytorch-extra]'s releases.

Lightning v2.5

Lightning AI ⚡ is excited to announce the release of Lightning 2.5.

Lightning 2.5 comes with improvements on several fronts, with zero API changes. Our users love it stable, we keep it stable 😄.

Talking about love ❤️, the lightning, pytorch-lightning and lightning-fabric packages are collectively getting more than 10M downloads per month 😮, for a total of over 180M downloads 🤯 since the early days . It's incredible to see PyTorch Lightning getting such a strong adoption across the industry and the sciences.

Release 2.5 embraces PyTorch 2.5, and it marks some of its more recent directions as officially supported, namely tensor subclass-based APIs like Distributed Tensors and TorchAO, in combination with torch.compile.

Here's a couple of examples:

Full example here

import lightning as L
import torch
import torch.nn as nn
import torch.nn.functional as F
from lightning.pytorch.demos import Transformer, WikiText2
from lightning.pytorch.strategies import ModelParallelStrategy
from torch.distributed._composable.fsdp.fully_shard import fully_shard
from torch.utils.data import DataLoader
from torchao.float8 import Float8LinearConfig, convert_to_float8_training
class LanguageModel(L.LightningModule):
def init(self, vocab_size):
super().init()
self.vocab_size = vocab_size
self.model = None
def configure_model(self):
    if self.model is not None:
        return
with torch.device("meta"):
    model = Transformer(
        vocab_size=self.vocab_size,
        nlayers=16,
        nhid=4096,
        ninp=1024,
        nhead=32,
    )

float8_config = Float8LinearConfig(
    # pip install -U --index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/Triton-Nightly/pypi/simple/ triton-nightly  # noqa
    pad_inner_dim=True,
)


</tr></table>

... (truncated)

Commits

• c45c3c9 docker: fix setting tags (#20504)
• f9babd1 ci: build docs once you prepare release (#20507)
• 61a8391 docs: bump habana (#20506)
• 0324a20 Prepare Lightning 2.5.0 release (#20505)
• 4c0eb3a Update (ci): github action's artifact upgrade v4 (#20500)
• 110d621 Bump to 2.5.0rc0 (#20493)
• 1129d4c Add step parameter to TensorBoardLogger.log_hyperparams (#20176)
• a9125c2 Fix LightningCLI failing when both module and data module save hyperparameter...
• 60289d7 Force hook standalone tests to single device (#20491)
• 9709c64 Add str method to datamodule (#20301)
• Additional commits viewable in compare view

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[adamjstewart]

• mypy failing due to Cannot import OptimizerLRSchedulerConfig or OptimizerLRSchedulerConfigDict  Lightning-AI/pytorch-lightning#20511
• pytest failing due to Patch jsonargparse for Python >= 3.12.8 Lightning-AI/pytorch-lightning#20479 (comment)

[lantiga]

Quoting from Lightning-AI/pytorch-lightning#20511 (comment)

the return type for configure_optimizers hasn't been actually changed, it was OptimizerLRScheduler before and it still is. However that is a composite type and I renamed it in a PR: it was OptimizerLRSchedulerConfig and it now is OptimizerLRSchedulerConfigType thinking that it would not be impactful downstream but apparently it is.

So you can fix the above by doing
from lightning.pytorch.utilities.types import OptimizerLRSchedulerConfigType
but I'm thinking we could just quickly go back to the previous name and avoid breaking the contract

What do you think @adamjstewart

[adamjstewart]

Going back to the previous name, or at least providing a deprecated alias for the old name, would be least impactful. Especially in a release that boasts no API changes 😉

We're also fine with adding a try-except on that import as needed. We just finished a 0.6.2 release yesterday so might not see a new release to fix support for lightning 2.5+ for a while though.

[lantiga]

We had no intention to break the contract, the rename just happened and it ultimately flew under the radar (and on top of that it was all my fault :-) )

[adamjstewart]

Yep, no worries, type hints are a very minor part of the API for most users, I don't expect this impacts individual lightning users as much as it impacts the libraries that depend on lightning.

[lantiga]

Release is out: https://github.com/Lightning-AI/pytorch-lightning/releases/tag/2.5.0.post0
feel free to bump to lightning[pytorch-extra]==2.5.0.post0

[dependabot]

Superseded by #2489.