Added DistributedSampler to the train_dataloader

demo-notebooks/guided-demos/pytorch_lightning.py

@@ -2,7 +2,7 @@
 import tempfile
 
 import torch
-from torch.utils.data import DataLoader
+from torch.utils.data import DataLoader, DistributedSampler
 from torchvision.models import resnet18
 from torchvision.datasets import FashionMNIST
 from torchvision.transforms import ToTensor, Normalize, Compose
@@ -74,10 +74,19 @@ def train_func():
     train_data = FashionMNIST(
         root=data_dir, train=True, download=True, transform=transform
     )
-    train_dataloader = DataLoader(train_data, batch_size=128, shuffle=True)
 
     # Training
     model = ImageClassifier()
+
+    sampler = DistributedSampler(
+        train_data,
+        num_replicas=ray.train.get_context().get_world_size(),
+        rank=ray.train.get_context().get_world_rank(),
+    )
+
+    train_dataloader = DataLoader(
+        train_data, batch_size=128, shuffle=False, sampler=sampler
+    )
     # [1] Configure PyTorch Lightning Trainer.
     trainer = pl.Trainer(
         max_epochs=10,