Update broadcast.py

broadcast.py

@@ -0,0 +1,20 @@
+import torch
+import torch.distributed as dist
+
+def init_process():
+    dist.init_process_group(backend="nccl")
+    torch.cuda.set_device(dist.get_rank())
+
+def example_broadcast():
+    if dist.get_rank() == 0:
+        tensor = torch.tensor([1, 2, 3, 4], dtype=torch.float32).cuda()
+    else:
+        tensor = torch.zeros(4, dtype=torch.float32).cuda()
+
+    print(f"Before broadcast on rank {dist.get_rank()}: {tensor}")
+    dist.broadcast(tensor, src=0)
+    print(f"After broadcast on rank {dist.get_rank()}: {tensor}")
+
+init_process()
+example_broadcast()
+dist.destroy_process_group()