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# SPDX-FileCopyrightText: Copyright (c) 2023 - 2025 NVIDIA CORPORATION & AFFILIATES.
# SPDX-FileCopyrightText: All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from datetime import datetime
import torch
from physicsnemo.distributed import DistributedManager
def create_ddp_group_tag(group_name: str = None) -> str:
"""Creates a common group tag for logging
For some reason this does not work with multi-node. Seems theres a bug in PyTorch
when one uses a distributed util before DDP
Parameters
----------
group_name : str, optional
Optional group name prefix. If None will use ``"DDP_Group_"``, by default None
Returns
-------
str
Group tag
"""
dist = DistributedManager()
if dist.rank == 0:
# Store time stamp as int tensor for broadcasting
def tint(x):
return int(datetime.now().strftime(f"%{x}"))
time_index = torch.IntTensor(
[tint(x) for x in ["m", "d", "y", "H", "M", "S"]]
).to(dist.device)
else:
time_index = torch.IntTensor([0, 0, 0, 0, 0, 0]).to(dist.device)
if torch.distributed.is_available():
# Broadcast group ID to all processes
torch.distributed.broadcast(time_index, src=0)
time_string = f"{time_index[0]}/{time_index[1]}/{time_index[2]}_\
{time_index[3]}-{time_index[4]}-{time_index[5]}"
if group_name is None:
group_name = "DDP_Group"
return group_name + "_" + time_string
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