Fix inaccurate note in DistributedDataParallel (#47156)
Summary:
Sorry for my previous inaccurate [PR](https://github.com/pytorch/pytorch/pull/42471#issue-462329192 ).
Here are some toy code to illustrate my point:
* non-DistributedDataParallel version
```python
import torch
if __name__ == "__main__":
torch.manual_seed(0)
inp = torch.randn(1,16)
inp = torch.cat([inp, inp], dim=0)
model = torch.nn.Linear(16, 2)
loss_func = torch.nn.CrossEntropyLoss()
opti = torch.optim.SGD(model.parameters(), lr=0.001)
opti.zero_grad()
loss = loss_func(model(inp), torch.tensor([0, 0]))
loss.backward()
opti.step()
print("grad:", model.weight.grad)
print("updated weight:\n", model.weight)
```
* DistributedDataParallel version
```python
import os
import torch
import torch.nn as nn
import torch.distributed as dist
from torch.multiprocessing import Process
def run(rank, size):
torch.manual_seed(0)
x = torch.randn(1,16)
model = torch.nn.Linear(16, 2)
model = torch.nn.parallel.DistributedDataParallel(model)
loss_func = torch.nn.CrossEntropyLoss()
opti = torch.optim.SGD(model.parameters(), lr=0.001)
opti.zero_grad()
y = model(x)
label = torch.tensor([0])
loss = loss_func(y, label)
loss.backward()
opti.step()
if rank == 0:
print("grad:", model.module.weight.grad)
print("updated weight:\n", model.module.weight)
def init_process(rank, size, fn, backend="gloo"):
os.environ['MASTER_ADDR'] = '127.0.0.1'
os.environ['MASTER_PORT'] = '29500'
dist.init_process_group(backend, rank=rank, world_size=size)
fn(rank, size)
if __name__ == "__main__":
size = 2
process = []
for rank in range(size):
p = Process(target=init_process, args=(rank, size, run))
p.start()
process.append(p)
for p in process:
p.join()
```
Both of these two pieces of code have the same output.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47156
Reviewed By: mruberry
Differential Revision: D24675199
Pulled By: mrshenli
fbshipit-source-id: 1238a63350a32a824b4b8c0018dc80454ea502bb
