Bump pytorch-lightning from 2.1.2 to 2.2.0 in /runtimes/mlflow

[dependabot]

Bumps pytorch-lightning from 2.1.2 to 2.2.0.

Release notes

Sourced from pytorch-lightning's releases.

Lightning 2.2

Lightning AI is excited to announce the release of Lightning 2.2 ⚡

Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.

While our previous release was packed with many big new features, this time around we're rolling out mainly improvements based on feedback from the community. And of course, as the name implies, this release fully supports the latest PyTorch 2.2 🎉

• Highlights
  • Monitoring Throughput
  • Improved Handling of Evaluation Mode
  • Converting FSDP Checkpoints
  • Improvements to Compiling DDP/FSDP in Fabric
  • Saving and Loading DataLoader State
  • Non-strict Checkpoint Loading in Trainer
• Notable Changes
• Full Changelog
  • PyTorch Lightning
  • Lightning Fabric
• Contributors

Highlights

Monitoring Throughput

Lightning now has built-in utilities to measure throughput metrics such as batches/sec, samples/sec and Model FLOP Utilization (MFU) (#18848).

Trainer:

For the Trainer, this comes in form of a ThroughputMonitor callback. In order to track samples/sec, you need to provide a function to tell the monitor how to extract the batch dimension from your input. Furthermore, if you want to track MFU, you can provide a sample forward pass and the ThroughputMonitor will automatically estimate the utilization based on the hardware you are running on:

import lightning as L
from lightning.pytorch.callbacks import ThroughputMonitor
from lightning.fabric.utilities.throughput import measure_flops
class MyModel(LightningModule):
def setup(self, stage):
with torch.device("meta"):
model = MyModel()
    def sample_forward():
        batch = torch.randn(..., device="meta")
        return model(batch)
self.flops_per_batch = measure_flops(model, sample_forward, loss_fn=torch.Tensor.sum)


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Commits

• bc56630 Release Lightning 2.2 (#19399)
• 4510351 Delay Precision.convert_module until configure_model has run (#19061)
• db2cc8a Fix CLI docs typo (#19426)
• 78b7a39 Update throughput docs (#19415)
• 28a8023 Add support for tif (#19421)
• c80226d map & operator: Add lightning.ai account creation info (#19418)
• 0d8208f Bump peter-evans/create-pull-request from 5 to 6 (#19407)
• 130b05f Fix dead link in docs (#19387)
• 285da64 Data Processor: Give instructions to the users when the dependencies doesn't ...
• 7a56ac5 Support shortcut name for DeepSpeed stage 1 offload (#19075)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #1571.