graphstorm.gsf.initialize

graphstorm.gsf.initialize(ip_config=None, backend='gloo', local_rank=0, use_wholegraph=False)

Initialize distributed training and inference context.

# Standalone mode
import graphstorm as gs
gs.initialize()

# distributed mode
import graphstorm as gs
gs.initialize(ip_config="/tmp/ip_list.txt", backend="gloo")

Parameters

ip_config: str

File path of ip_config file, e.g., /tmp/ip_list.txt Default: None

backend: str

Torch distributed backend, e.g., gloo or nccl. Default: ‘gloo’

local_rank: int

The local rank of the current process. Default: 0

use_wholegraph: bool

Whether to use wholegraph for feature transfer. Default: False