lr=0.001)# 初始化模型和Lightning模块model=CustomModel()lightning_model=LightningModel(model)# 初始化Trainer并训练模型trainer=pl.Trainer(max_epochs=10,gpus=1)# 使用GPU训练trainer.fit(lightning_model,dataloader)
model=CustomMNIST()trainer=Trainer(max_epochs=5,gpus=1) 如果你在上面的gist代码中看到第27和33行,你会看到training_step和configure_optimators方法,它覆盖了在第2行中扩展的类LightningModule中的方法。这使得pytorch中标准的nn.Module不同于LightningModule,它有一些方法使它与第39行中的Trainer类兼容。 现在,...
batch_size) def test_dataloader(self): return DataLoader(self.mnist_test, batch_size=self.batch_size) setup 函数中的 stage 参数用于区分训练、验证和测试阶段。它是一个 'fit'、'test' 或 None 的字符串。 定义优化器 使用configure_optimizers 来定义优化器。 class MnistModel(pl.LightningModule): #...
classCustomDataModule(pl.LightningDataModule):"""Datamodule wrapping all preparation and dataset creation functionality."""def__init__(self,feature_preprocessor:FeaturePreprocessor,splitter:AbstractSplitter,all_scenarios:List[AbstractScenario],train_fraction:float,val_fraction:float,test_fraction:float,datalo...
PyPI 是 Python 的软件包索引,是安装 pytorch_lightning 的必要前置条件。可以通过以下命令安装 PyPI: pip install pypi 1. 安装完成后,就可以使用 PyPI 来安装 pytorch_lightning 和其他 Python 库。 2.2 安装 pytorch_lighting 的步骤 2.2.1 安装依赖库 ...
PyTorchLightning currently has the ability to replace the sampler for you and make a distributed sampler, but not when it is a custom sampler or when the dataloader has a batch sampler In the code sample above, you, the user, would have to replace the sequential sampler with a DistributedSa...
DataLoader(train_set, batch_size=1024, shuffle=True, num_workers=8, pin_memory=True) device = torch.device("cuda:0") model = Net().cuda(device) criterion = CrossEntropyLoss().cuda(device) optimizer = torch.optim.SGD(model.parameters(), lr=0.001, momentum=0.9) model.train() # ...
DataLoader(train), data.DataLoader(val)) Run the model on your terminal pip install torchvision python main.py Advanced features Lightning has over 40+ advanced features designed for professional AI research at scale. Here are some examples: Train on 1000s of GPUs without code changes Train on...
The LightningModule defines asystemsuch as seq-2-seq, GAN, etc... It can ALSO define a simple classifier such as the example below. To use lightning do 2 things: Define a LightningModule importosimporttorchfromtorch.nnimportfunctionalasFfromtorch.utils.dataimportDataLoaderfromtorchvision.datasetsimp...
nonechucks: Skip bad items in your PyTorch DataLoader, use Transforms as Filters, and more! torchstat: Model analyzer in PyTorch. QNNPACK: Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators. ...