mnist_hogwild manual breaking of gradient sharing removed (pytorch#138)

Author: pfrendl

mnist_hogwild/main.py

@@ -50,7 +50,7 @@ def forward(self, x):
  torch.manual_seed(args.seed)
 
  model = Net()
- model.share_memory()
+ model.share_memory() # gradients are allocated lazily, so they are not shared here
 
  processes = []
  for rank in range(args.num_processes):

mnist_hogwild/train.py

@@ -7,10 +7,6 @@
 
 def train(rank, args, model):
  torch.manual_seed(args.seed + rank)
- for param in model.parameters():
- # Break gradient sharing
- if param.grad is not None:
- param.grad.data = param.grad.data.clone()
 
  train_loader = torch.utils.data.DataLoader(
  datasets.MNIST('../data', train=True, download=True,