File size: 1,662 Bytes
8b306b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | # Copyright (c) 2025 ByteDance Ltd. and/or its affiliates.
#
# 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.
# coding: utf-8
import os
import torch
import torch.distributed as dist
def get_global_rank() -> int:
"""
Get the global rank, the global index of the GPU.
"""
return int(os.environ.get("RANK", "0"))
def get_local_rank() -> int:
"""
Get the local rank, the local index of the GPU.
"""
return int(os.environ.get("LOCAL_RANK", "0"))
def get_world_size() -> int:
"""
Get the world size, the total amount of GPUs.
"""
return int(os.environ.get("WORLD_SIZE", "1"))
def is_master():
"""
Check if the current process is the master process (rank 0).
"""
if not dist.is_available() or not dist.is_initialized():
return True
return dist.get_rank() == 0
def get_device() -> torch.device:
"""
Get current rank device.
"""
return torch.device("cuda", get_local_rank())
def barrier_if_distributed(*args, **kwargs):
"""
Synchronizes all processes if under distributed context.
"""
if dist.is_initialized():
return dist.barrier(*args, **kwargs)
|