lightning/tests/base/datamodules.py

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from torch.utils.data import random_split, DataLoader
from pytorch_lightning.core.datamodule import LightningDataModule
from tests.base.datasets import TrialMNIST
class TrialMNISTDataModule(LightningDataModule):
def __init__(self, data_dir: str = './'):
super().__init__()
self.data_dir = data_dir
def prepare_data(self):
TrialMNIST(self.data_dir, train=True, download=True)
TrialMNIST(self.data_dir, train=False, download=True)
def setup(self):
mnist_full = TrialMNIST(root=self.data_dir, train=True, num_samples=64, download=True)
self.mnist_train, self.mnist_val = random_split(mnist_full, [128, 64])
self.dims = tuple(self.mnist_train[0][0].shape)
self.mnist_test = TrialMNIST(root=self.data_dir, train=False, num_samples=32, download=True)
def train_dataloader(self):
return DataLoader(self.mnist_train, batch_size=32)
def val_dataloader(self):
return DataLoader(self.mnist_val, batch_size=32)
def test_dataloader(self):
return DataLoader(self.mnist_test, batch_size=32)