Integrate Lightning Fabric for scalable multi-GPU training #3
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Runs pytest against Python 3.9-3.12 matrix on: - Pull requests to main - Pushes to main Excludes slow tests (pretrained model downloads) for fast CI.
- Added tests/test_train_fabric.py - Added tests/test_cli_train.py - Updated tests/test_train.py to use CPU explicitly - Added VideoRateDistortionLoss to tinify/losses for correct video training support in CLI
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Summary
Integrated PyTorch Lightning Fabric to enable scalable multi-GPU training and simplify device management across the codebase.
Key Changes
lightning>=2.0.0topyproject.toml.examples/train.py,examples/train_video.py,examples/train_elic_cifar10.py, andtinify/cli/train.pyto use Fabric..to(device)) andCustomDataParallelwrapper.fabric.backward()andfabric.clip_gradients().--accelerator,--devices,--strategy, and--precisionarguments to training scripts for flexible hardware configuration.Benefits