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Add CUDA availability check to distributed initializer #153

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Add CUDA availability check to distributed initializer #153

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19 changes: 10 additions & 9 deletions gpt_oss/torch/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,22 +2,18 @@
import torch
import torch.distributed as dist


def suppress_output(rank):
"""Suppress printing on the current device. Force printing with `force=True`."""
import builtins as __builtin__
builtin_print = __builtin__.print

def print(*args, **kwargs):
force = kwargs.pop('force', False)
if force:
builtin_print("rank #%d:" % rank, *args, **kwargs)
elif rank == 0:
builtin_print(*args, **kwargs)

__builtin__.print = print


def init_distributed() -> torch.device:
"""Initialize the model for distributed inference."""
# Initialize distributed inference
Expand All @@ -27,14 +23,19 @@ def init_distributed() -> torch.device:
dist.init_process_group(
backend="nccl", init_method="env://", world_size=world_size, rank=rank
)
torch.cuda.set_device(rank)
device = torch.device(f"cuda:{rank}")


# Check if CUDA is available before setting device
if torch.cuda.is_available():
torch.cuda.set_device(rank)
device = torch.device(f"cuda:{rank}")
else:
device = torch.device("cpu")

# Warm up NCCL to avoid first-time latency
if world_size > 1:
x = torch.ones(1, device=device)
dist.all_reduce(x)
torch.cuda.synchronize(device)

if torch.cuda.is_available():
torch.cuda.synchronize(device)
suppress_output(rank)
return device