![]() ![]() LightningModule ): def _init_ ( self ): super (). ![]() ![]() Step 1: Add these imports import os import torch from torch import nn import torch.nn.functional as F from torchvision.datasets import MNIST from import DataLoader, random_split from torchvision import transforms import pytorch_lightning as pl Step 2: Define a LightningModule (nn.Module subclass)Ī LightningModule defines a full system (ie: a GAN, autoencoder, BERT or a simple Image Classifier). Simple installation from PyPI pip install pytorch-lightning Current build statuses System / PyTorch ver. Lightning is rigorously tested across multiple CPUs, GPUs, TPUs, IPUs, and HPUs and against major Python and PyTorch versions. Once you do this, you can train on multiple-GPUs, TPUs, CPUs, IPUs, HPUs and even in 16-bit precision without changing your code! Data (use PyTorch DataLoaders or organize them into a LightningDataModule).Non-essential research code (logging, etc.Engineering code (you delete, and is handled by the Trainer).Lightning forces the following structure to your code which makes it reusable and shareable: ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |