mirror of https://github.com/hpcaitech/ColossalAI
312 lines
9.9 KiB
Python
312 lines
9.9 KiB
Python
import os
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import sys
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from typing import List
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import click
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import torch
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from packaging import version
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from colossalai.context import Config
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from .hostinfo import HostInfo, HostInfoList
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from .multinode_runner import MultiNodeRunner
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# Constants that define our syntax
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NODE_SEP = ','
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def fetch_hostfile(hostfile_path: str, ssh_port: int) -> HostInfoList:
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"""
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Parse the hostfile to obtain a list of hosts.
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A hostfile should look like:
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worker-0
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worker-1
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worker-2
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...
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Args:
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hostfile_path (str): the path to the hostfile
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ssh_port (int): the port to connect to the host
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"""
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if not os.path.isfile(hostfile_path):
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click.echo(f"Error: Unable to find the hostfile, no such file: {hostfile_path}")
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exit()
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with open(hostfile_path, 'r') as fd:
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device_pool = HostInfoList()
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for line in fd.readlines():
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line = line.strip()
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if line == '':
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# skip empty lines
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continue
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# build the HostInfo object
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hostname = line.strip()
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hostinfo = HostInfo(hostname=hostname, port=ssh_port)
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if device_pool.has(hostname):
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click.echo(f"Error: found duplicate host {hostname} in the hostfile")
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exit()
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device_pool.append(hostinfo)
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return device_pool
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def parse_device_filter(device_pool: HostInfoList, include_str=None, exclude_str=None) -> HostInfoList:
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'''Parse an inclusion or exclusion string and filter a hostfile dictionary.
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Examples:
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include_str="worker-0,worker-1" will execute jobs only on worker-0 and worker-1.
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exclude_str="worker-1" will use all available devices except worker-1.
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Args:
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device_pool (HostInfoList): a list of HostInfo objects
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include_str (str): --include option passed by user, default None
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exclude_str (str): --exclude option passed by user, default None
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Returns:
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filtered_hosts (HostInfoList): filtered hosts after inclusion/exclusion
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'''
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# Ensure include/exclude are mutually exclusive
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if include_str and exclude_str:
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click.echo("--include and --exclude are mutually exclusive, only one can be used")
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exit()
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# no-op
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if include_str is None and exclude_str is None:
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return device_pool
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# Either build from scratch or remove items
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if include_str:
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parse_str = include_str
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filtered_hosts = HostInfoList()
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elif exclude_str:
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parse_str = exclude_str
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filtered_hosts = device_pool
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# foreach node in the list
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for node_config in parse_str.split(NODE_SEP):
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hostname = node_config
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hostinfo = device_pool.get_hostinfo(hostname)
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# sanity check hostname
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if not device_pool.has(hostname):
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click.echo(f"Error: Hostname '{hostname}' not found in hostfile")
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exit()
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if include_str:
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filtered_hosts.append(hostinfo)
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elif exclude_str:
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filtered_hosts.remove(hostname)
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return filtered_hosts
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def get_launch_command(
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master_addr: str,
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master_port: int,
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nproc_per_node: int,
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user_script: str,
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user_args: List[str],
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node_rank: int,
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num_nodes: int,
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extra_launch_args: str = None,
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) -> str:
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"""
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Generate a command for distributed training.
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Args:
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master_addr (str): the host of the master node
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master_port (str): the port of the master node
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nproc_per_node (str): the number of processes to launch on each node
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user_script (str): the user Python file
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user_args (str): the arguments for the user script
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node_rank (int): the unique ID for the node
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num_nodes (int): the number of nodes to execute jobs
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Returns:
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cmd (str): the command the start distributed training
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"""
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def _arg_dict_to_list(arg_dict):
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ret = []
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for k, v in arg_dict.items():
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if v:
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ret.append(f'--{k}={v}')
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else:
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ret.append(f'--{k}')
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return ret
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if extra_launch_args:
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extra_launch_args_dict = dict()
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for arg in extra_launch_args.split(','):
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if '=' in arg:
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k, v = arg.split('=')
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extra_launch_args_dict[k] = v
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else:
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extra_launch_args_dict[arg] = None
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extra_launch_args = extra_launch_args_dict
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else:
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extra_launch_args = dict()
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torch_version = version.parse(torch.__version__)
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assert torch_version.major >= 1
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if torch_version.minor < 9:
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cmd = [
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sys.executable, "-m", "torch.distributed.launch", f"--nproc_per_node={nproc_per_node}",
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f"--master_addr={master_addr}", f"--master_port={master_port}", f"--nnodes={num_nodes}",
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f"--node_rank={node_rank}"
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]
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else:
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# extra launch args for torch distributed launcher with torch >= 1.9
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default_torchrun_rdzv_args = dict(rdzv_backend="c10d",
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rdzv_endpoint=f"{master_addr}:{master_port}",
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rdzv_id="colossalai-default-job")
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# update rdzv arguments
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for key in default_torchrun_rdzv_args.keys():
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if key in extra_launch_args:
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value = extra_launch_args.pop(key)
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default_torchrun_rdzv_args[key] = value
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if torch_version.minor < 10:
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cmd = [
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sys.executable, "-m", "torch.distributed.run", f"--nproc_per_node={nproc_per_node}",
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f"--nnodes={num_nodes}", f"--node_rank={node_rank}"
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]
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else:
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cmd = [
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"torchrun", f"--nproc_per_node={nproc_per_node}", f"--nnodes={num_nodes}", f"--node_rank={node_rank}"
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]
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cmd += _arg_dict_to_list(default_torchrun_rdzv_args)
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cmd += _arg_dict_to_list(extra_launch_args) + [user_script] + user_args
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cmd = ' '.join(cmd)
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return cmd
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def launch_multi_processes(args: Config) -> None:
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"""
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Launch multiple processes on a single node or multiple nodes.
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The overall logic can be summarized as the pseudo code below:
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if hostfile given:
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hostinfo = parse_hostfile(hostfile)
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hostinfo = include_or_exclude_hosts(hostinfo)
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launch_on_multi_nodes(hostinfo)
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elif hosts given:
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hostinfo = parse_hosts(hosts)
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launch_on_multi_nodes(hostinfo)
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else:
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launch_on_current_node()
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Args:
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args (Config): the arguments taken from command line
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"""
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assert isinstance(args, Config)
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if args.nproc_per_node is None:
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click.echo("--nproc_per_node did not receive any value")
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exit()
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# cannot accept hosts and hostfile at the same time
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if args.host and args.hostfile:
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click.echo("Error: hostfile and hosts are mutually exclusive, only one is required")
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# check if hostfile is given
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if args.hostfile:
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device_pool = fetch_hostfile(args.hostfile, ssh_port=args.ssh_port)
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active_device_pool = parse_device_filter(device_pool, args.include, args.exclude)
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if args.num_nodes > 0:
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# only keep the first num_nodes to execute jobs
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updated_active_device_pool = HostInfoList()
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for count, hostinfo in enumerate(active_device_pool):
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if args.num_nodes == count:
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break
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updated_active_device_pool.append(hostinfo)
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active_device_pool = updated_active_device_pool
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else:
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active_device_pool = None
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env = os.environ.copy()
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# use hosts if hostfile is not given
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if args.host and active_device_pool is None:
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active_device_pool = HostInfoList()
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host_list = args.host.strip().split(NODE_SEP)
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for hostname in host_list:
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hostinfo = HostInfo(hostname=hostname, port=args.ssh_port)
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active_device_pool.append(hostinfo)
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if not active_device_pool:
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# run on local node if not hosts or hostfile is given
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# add local node to host info list
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active_device_pool = HostInfoList()
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localhost_info = HostInfo(hostname='127.0.0.1', port=args.ssh_port)
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active_device_pool.append(localhost_info)
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# launch distributed processes
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runner = MultiNodeRunner()
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curr_path = os.path.abspath('.')
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# collect current path env
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env = dict()
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for k, v in os.environ.items():
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# do not support multi-line env var
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if v and '\n' not in v:
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env[k] = v
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# establish remote connection
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runner.connect(host_info_list=active_device_pool, workdir=curr_path, env=env)
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# execute distributed launching command
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for node_id, hostinfo in enumerate(active_device_pool):
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cmd = get_launch_command(master_addr=args.master_addr,
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master_port=args.master_port,
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nproc_per_node=args.nproc_per_node,
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user_script=args.user_script,
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user_args=args.user_args,
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node_rank=node_id,
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num_nodes=len(active_device_pool),
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extra_launch_args=args.extra_launch_args)
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runner.send(hostinfo=hostinfo, cmd=cmd)
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# start training
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msg_from_node = runner.recv_from_all()
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has_error = False
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# print node status
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click.echo("\n====== Training on All Nodes =====")
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for hostname, msg in msg_from_node.items():
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click.echo(f"{hostname}: {msg}")
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# check if a process failed
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if msg == "failure":
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has_error = True
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# stop all nodes
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runner.stop_all()
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# receive the stop status
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msg_from_node = runner.recv_from_all()
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# print node status
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click.echo("\n====== Stopping All Nodes =====")
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for hostname, msg in msg_from_node.items():
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click.echo(f"{hostname}: {msg}")
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# give the process an exit code
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# so that it behaves like a normal process
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if has_error:
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sys.exit(1)
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else:
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sys.exit(0)
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