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# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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.
import torch
from nemo.utils.env_var_parsing import get_envint
def is_global_rank_zero():
""" Helper function to determine if the current process is global_rank 0 (the main process)
"""
# Try to get the pytorch RANK env var
# RANK is set by torch.distributed.launch
rank = get_envint("RANK", None)
if rank is not None:
return rank == 0
# Try to get the SLURM global rank env var
# SLURM_PROCID is set by SLURM
slurm_rank = get_envint("SLURM_PROCID", None)
if slurm_rank is not None:
return slurm_rank == 0
# if neither pytorch and SLURM env vars are set
# check NODE_RANK/GROUP_RANK and LOCAL_RANK env vars
# asume global_rank is zero if undefined
node_rank = get_envint("NODE_RANK", get_envint("GROUP_RANK", 0))
local_rank = get_envint("LOCAL_RANK", 0)
return node_rank == 0 and local_rank == 0
def get_rank():
""" Helper function that returns torch.distributed.get_rank() if DDP has been initialized otherwise it returns 0.
"""
if is_global_rank_zero():
return 0
else:
return torch.distributed.get_rank()
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