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Trainer — PyTorch Lightning 1.9.6 documentation


Trainer — PyTorch Lightning 1.9.6 documentation

Once you've organized your PyTorch code into a LightningModule, the Trainer automates everything else.

PyTorch Lightning 1.9.6 documentation - Trainer

Runs the full optimization routine. Run inference on your data. This will call the model forward function to compute predictions.

PyTorch Lightning 1.9.6 documentation

PyTorch Lightning is the deep learning framework for professional AI researchers and machine learning engineers who need maximal flexibility without ...

Train a model (basic) — PyTorch Lightning 1.9.6 documentation

Audience: Users who need to train a model without coding their own training loops. Add imports. Add the relevant imports at the top of the file. import os ...

LightningModule — PyTorch Lightning 1.9.6 documentation

The PyTorch code IS NOT abstracted - just organized. All the other code that's not in the LightningModule has been automated for you by the Trainer.

Manual Optimization — PyTorch Lightning 1.9.6 documentation

optimizers() to access your optimizers (one or multiple). optimizer.zero_grad() to clear the gradients from the previous training step. self.manual_backward( ...

LightningModule — PyTorch Lightning 1.9.6 documentation

clip_gradients(opt, gradient_clip_val=0.5, gradient_clip_algorithm="norm") manually in the training step. Parameters. optimizer ( Optimizer ) – Current ...

Source code for pytorch_lightning.trainer.trainer - PyTorch Lightning

Source code for pytorch_lightning.trainer.trainer ... Built with Sphinx using a theme provided by Read the Docs. To analyze traffic and optimize your experience, ...

API Reference — PyTorch Lightning 1.9.6 documentation

Base class for all plugins handling the precision-specific parts of the training. DoublePrecision. Plugin for training with double ( torch.float64 ) precision.

PyTorch Lightning 1.4.9 documentation - Read the Docs

Best practices. Speed up model training · Managing Data · Style guide · Lightning project template · Benchmark with vanilla PyTorch. Lightning API.

Multiple dataloaders in training #8410 - GitHub

I'm trying to use integrate pytorch lightning into my current pipeline. But I'm having some difficulties in using multiple dataloaders.

Lightning in 15 minutes — PyTorch Lightning 1.9.6 documentation

PyTorch Lightning is the deep learning framework with “batteries included” for professional AI researchers and machine learning engineers who need maximal ...

Registration of custom callbacks in LightningCLI (PL 1.9.0) #17602

This is explained at https://lightning.ai/docs/pytorch/stable/cli ... Lightning Trainer API: Trainer, LightningModule, LightningDataModule.

pytorch-lightning - PyPI

PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.

LightningCLI — PyTorch Lightning 1.9.6 documentation

A full configuration yaml would be parsed from PL_CONFIG if set. Individual settings are so parsed from variables named for example PL_TRAINER__MAX_EPOCHS . For ...

[P] An elegant and strong PyTorch Trainer : r/MachineLearning

The documentation instructs that the network model should inherit from the LightningModule. ... Pytorch lightning used to be "lightweight ...

lightning - PyPI

Examples. Explore various types of training possible with PyTorch Lightning. ... Read the PyTorch Lightning docs. Lightning Fabric: Expert control. Run on any ...

pytorch_lightning.cli — PyTorch Lightning 1.9.6 documentation

Args: lightning_class: A callable or any subclass of {Trainer, LightningModule, LightningDataModule, Callback}. nested_key: Name of the nested namespace to ...

example of doing simple prediction with pytorch-lightning

LightningModule is a subclass of torch.nn.Module so the same model class will work for both inference and training.

Pytorch Lightning Trainer Documentation | Restackio

The PyTorch Lightning Trainer simplifies the training process, allowing you to focus on model development. By leveraging its features, you can efficiently ...