Making large AI models cheaper, faster and more accessible
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import click
from colossalai.context import Config
from .run import launch_multi_processes
@click.command(
help="Launch distributed training on a single node or multiple nodes",
context_settings=dict(ignore_unknown_options=True),
)
@click.option(
"-H",
"-host",
"--host",
type=str,
default=None,
help="the list of hostnames to launch in the format <host1>,<host2>",
)
@click.option(
"--hostfile",
type=str,
default=None,
help="Hostfile path that defines the device pool available to the job, each line in the file is a hostname",
)
@click.option(
"--include",
type=str,
default=None,
help="Specify computing devices to use during execution. String format is <host1>,<host2>,"
" only effective when used with --hostfile.",
)
@click.option(
"--exclude",
type=str,
default=None,
help="Specify computing devices to NOT use during execution. Mutually exclusive with --include. Formatting is the same as --include,"
" only effective when used with --hostfile.",
)
@click.option(
"--num_nodes",
type=int,
default=-1,
help="Total number of worker nodes to use, only effective when used with --hostfile.",
)
@click.option("--nproc_per_node", type=int, default=None, help="Number of GPUs to use on each node.")
@click.option(
"--master_port",
type=int,
default=29500,
help="(optional) Port used by PyTorch distributed for communication during distributed training.",
)
@click.option(
"--master_addr",
type=str,
default="127.0.0.1",
help="(optional) IP address of node 0, will be inferred via 'hostname -I' if not specified.",
)
@click.option(
"--extra_launch_args",
type=str,
default=None,
help="Set additional torch distributed launcher arguments such as --standalone. The format is --extra_launch_args arg1=1,arg2=2. "
"This will be converted to --arg1=1 --arg2=2 during execution",
)
@click.option("--ssh-port", type=int, default=None, help="(optional) the port used for ssh connection")
@click.argument("user_script", type=str)
@click.argument("user_args", nargs=-1)
def run(
host: str,
hostfile: str,
num_nodes: int,
nproc_per_node: int,
include: str,
exclude: str,
master_addr: str,
master_port: int,
extra_launch_args: str,
ssh_port: int,
user_script: str,
user_args: str,
) -> None:
"""
To launch multiple processes on a single node or multiple nodes via command line.
Usage::
# run with 4 GPUs on the current node use default port 29500
colossalai run --nprocs_per_node 4 train.py
# run with 2 GPUs on the current node at port 29550
colossalai run --nprocs_per_node 4 --master_port 29550 train.py
# run on two nodes
colossalai run --host <host1>,<host2> --master_addr host1 --nprocs_per_node 4 train.py
# run with hostfile
colossalai run --hostfile <file_path> --master_addr <host> --nprocs_per_node 4 train.py
# run with hostfile with only included hosts
colossalai run --hostfile <file_path> --master_addr host1 --include host1,host2 --nprocs_per_node 4 train.py
# run with hostfile excluding the hosts selected
colossalai run --hostfile <file_path> --master_addr host1 --exclude host2 --nprocs_per_node 4 train.py
"""
if not user_script.endswith(".py"):
click.echo(f"Error: invalid Python file {user_script}. Did you use a wrong option? Try colossalai run --help")
exit()
args_dict = locals()
args = Config(args_dict)
args.user_args = list(args.user_args)
launch_multi_processes(args)