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paddlepaddle--paddle/python/paddle/distributed/fleet/base/role_maker.py
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wehub-resource-sync e25996e7db chore: import upstream snapshot with attribution
2026-07-13 12:40:42 +08:00

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# Copyright (c) 2020 PaddlePaddle Authors. 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.
"""Definition of Role Makers."""
from __future__ import annotations
import os
import re
import time
import warnings
from multiprocessing import Manager, Process
from typing import TYPE_CHECKING, Any, ClassVar, Literal
import numpy as np
import paddle
from paddle.base import core
from paddle.distributed.fleet.base.private_helper_function import (
wait_server_ready,
)
from ...backup_env import getenv_or_backup
if TYPE_CHECKING:
import numpy.typing as npt
__all__ = []
class Role:
WORKER: ClassVar[Literal[1]] = 1
SERVER: ClassVar[Literal[2]] = 2
HETER_WORKER: ClassVar[Literal[3]] = 3
ALL: ClassVar[Literal[4]] = 4
COORDINATOR: ClassVar[Literal[5]] = 5
class Gloo:
"""
Gloo is a universal class for barrier and collective communication
"""
class RENDEZVOUS:
HDFS = 1
FILE = 2
HTTP = 3
def __init__(self):
self._worker_comm = None
self._server_comm = None
self._nodes_comm = None
self._comm_world = ["worker", "server", "all"]
self._err_init = (
"gloo is not initialized, will not communicator with other nodes"
)
self._err_type = "gloo initialized error, please check arguments"
self._err_world = (
f"argument error, comm_world must in {self._comm_world}"
)
self._is_initialized = False
self._init_timeout_seconds = 3600
self._run_timeout_seconds = 9999999
self._rendezvous = None
self._role = None
self._iface = None
self._role_id = -1
self._worker_num = -1
self._server_num = -1
self._need_init_all = False
def init(
self,
rendezvous,
role,
role_id,
worker_num,
server_num,
need_init_all=False,
kwargs=None,
):
self._rendezvous = rendezvous
self._role = role
self._role_id = role_id
self._worker_num = worker_num
self._server_num = server_num
self._need_init_all = need_init_all
self._iface = ""
self._prefix = kwargs.get("store.prefix", "")
http_server = None
if self._rendezvous == Gloo.RENDEZVOUS.HDFS:
dfs_name = kwargs.get("dfs.name", "")
dfs_ugi = kwargs.get("dfs.ugi", "")
dfs_path = kwargs.get("dfs.path", "")
if not dfs_name or not dfs_ugi or not dfs_path:
raise ValueError(self._err_type)
self._init_dfs(dfs_name, dfs_ugi, dfs_path, self._prefix)
elif self._rendezvous == Gloo.RENDEZVOUS.FILE:
fs_path = kwargs.get("dfs.path", "")
if not fs_path:
raise ValueError(self._err_type)
self._init_fs(fs_path, self._prefix)
elif self._rendezvous == Gloo.RENDEZVOUS.HTTP:
ip = kwargs.get("http.host", "")
port = kwargs.get("http.port", "")
start_http_server = kwargs.get("start_http_server", False)
http_server_d = kwargs.get("http_server_d")
if not ip or not port:
raise ValueError(self._err_type)
http_server = self._init_http(
ip, port, self._prefix, start_http_server, http_server_d
)
else:
raise ValueError(self._err_type)
self._is_initialized = True
self._http_server = http_server
def _init_fs(self, fs_path, prefix):
def init(rank, nodes, role):
gloo = core.Gloo()
gloo.set_rank(rank)
gloo.set_size(nodes)
gloo.set_prefix(prefix)
gloo.set_iface(self._iface)
gloo.set_timeout_seconds(
self._init_timeout_seconds, self._run_timeout_seconds
)
gloo.set_hdfs_store(os.path.join(fs_path, role), "", "")
gloo.init()
return gloo
if self._role == Role.WORKER:
rank, nodes = self._get_rank_nodes(Role.WORKER)
gloo = init(rank, nodes, "WORKER")
self._worker_comm = gloo
else:
rank, nodes = self._get_rank_nodes(Role.SERVER)
gloo = init(rank, nodes, "SERVER")
self._server_comm = gloo
if self._need_init_all:
rank, nodes = self._get_rank_nodes(Role.ALL)
gloo = init(rank, nodes, "ALL")
self._nodes_comm = gloo
def _init_dfs(self, dfs_name, dfs_ugi, dfs_path, prefix):
def init(rank, nodes, role):
gloo = core.Gloo()
gloo.set_rank(rank)
gloo.set_size(nodes)
gloo.set_prefix(prefix)
gloo.set_iface(self._iface)
gloo.set_timeout_seconds(
self._init_timeout_seconds, self._run_timeout_seconds
)
gloo.set_hdfs_store(os.path.join(dfs_path, role), dfs_name, dfs_ugi)
gloo.init()
return gloo
if self._role == Role.WORKER:
rank, nodes = self._get_rank_nodes(Role.WORKER)
gloo = init(rank, nodes, "WORKER")
self._worker_comm = gloo
else:
rank, nodes = self._get_rank_nodes(Role.SERVER)
gloo = init(rank, nodes, "SERVER")
self._server_comm = gloo
if self._need_init_all:
rank, nodes = self._get_rank_nodes(Role.ALL)
gloo = init(rank, nodes, "ALL")
self._nodes_comm = gloo
def _init_http(self, ip, port, prefix, start_http_server, http_server_d):
def __start_kv_server(http_server_d, size_d):
print(f"start http_server: {port}, {size_d}")
from paddle.distributed.fleet.utils.http_server import KVServer
http_server = KVServer(port, size_d)
http_server.start()
wait_seconds = 5
while (
http_server_d.get("running", False)
or not http_server.should_stop()
):
time.sleep(wait_seconds)
http_server.stop()
def init_kv_server(http_server_d):
worker_key = prefix + '_' + 'worker'
size_d = {
worker_key: self._worker_num,
}
print(f"worker_key:{worker_key}, size: {size_d}")
http_server_d["running"] = True
# child process for http server
_http_server = Process(
target=__start_kv_server, args=(http_server_d, size_d)
)
_http_server.daemon = True
# set running status to True
# start child process
_http_server.start()
return _http_server
def init(rank, nodes, role):
gloo = core.Gloo()
gloo.set_rank(rank)
gloo.set_size(nodes)
gloo.set_prefix(prefix)
gloo.set_iface(self._iface)
gloo.set_timeout_seconds(
self._init_timeout_seconds, self._run_timeout_seconds
)
gloo.set_http_store(ip, port, 'worker')
ep = ":".join([ip, str(port)])
wait_server_ready([ep])
gloo.init()
return gloo
port = int(port)
if start_http_server:
print("to start http_server")
http_server = init_kv_server(http_server_d)
if self._role == Role.WORKER:
rank, nodes = self._get_rank_nodes(Role.WORKER)
gloo = init(rank, nodes, "WORKER")
self._worker_comm = gloo
# TODO (sandyhouse): initialize gloo for server and all
# the closing of kv server may cause gloo init failure
# since it depend on the full mesh connection
# e.g. 0 connected with 1,2,3 while 2-3 not connected yet
# TODO(kuizhiqing)
if start_http_server:
http_server_d["running"] = False
http_server.join()
def _get_rank_nodes(self, role):
nodes = 0
rank = -1
if role == Role.WORKER:
nodes = self._worker_num
rank = self._role_id
elif role == Role.SERVER:
nodes = self._server_num
rank = self._role_id
elif role == Role.ALL:
nodes = self._worker_num + self._server_num
if self._role == Role.WORKER:
rank = self._role_id
else:
rank = self._worker_num + self._role_id
else:
ValueError(self._err_type)
return rank, nodes
def __get_default_iface(self):
"""
get default physical interface
"""
default1 = self.__get_default_iface_from_gateway()
default2 = self.__get_default_iface_from_interfaces()
return default2 if default1 == "lo" else default1
def __get_default_iface_from_gateway(self):
"""
get default physical interface
"""
res = os.popen("route -A inet").read().strip().split("\n")
gateway_idx = None
iface_idx = None
for item in res:
item = item.split()
if "Gateway" in item and "Iface" in item:
gateway_idx = item.index("Gateway")
iface_idx = item.index("Iface")
elif gateway_idx is not None and iface_idx is not None:
gateway = None
if len(item) > gateway_idx:
gateway = item[gateway_idx]
if (
gateway
and gateway != '*'
and gateway != "0.0.0.0"
and len(item) > iface_idx
):
return item[iface_idx]
return "lo"
def __get_default_iface_from_interfaces(self):
"""
get default physical interface
"""
res = (
os.popen("ip -f inet addr | awk NR%3==1").read().strip().split("\n")
)
for item in res:
if "BROADCAST" in item:
return item.split(":")[1].strip()
return "lo"
def barrier(self, comm_world):
"""
dummy barrier, do nothing
"""
if not self._is_initialized:
warnings.warn(self._err_init)
return
if comm_world not in self._comm_world:
raise ValueError(self._err_world)
if comm_world == "worker":
self._worker_comm.barrier()
elif comm_world == "server":
self._server_comm.barrier()
else:
self._nodes_comm.barrier()
def all_reduce(self, input, mode="sum", comm_world="worker"):
if not self._is_initialized:
warnings.warn(self._err_init)
return input
if comm_world not in self._comm_world:
raise ValueError(self._err_world)
input = np.array(input)
input_shape = input.shape
input_list = input.reshape(-1).tolist()
self.barrier(comm_world)
if comm_world == "worker":
ans = self._worker_comm.all_reduce(input_list, mode)
elif comm_world == "server":
ans = self._server_comm.all_reduce(input_list, mode)
else:
ans = self._nodes_comm.all_reduce(input_list, mode)
output = np.array(ans).reshape(input_shape)
return output
def all_gather(self, input, comm_world="worker"):
"""
dummy all gather, do nothing
Args:
obj(any): obj to do all gather
"""
if not self._is_initialized:
warnings.warn(self._err_init)
return input
if comm_world not in self._comm_world:
raise ValueError(self._err_world)
if comm_world == "worker":
output = self._worker_comm.all_gather(input)
elif comm_world == "server":
output = self._server_comm.all_gather(input)
else:
output = self._nodes_comm.all_gather(input)
return output
class RoleMakerBase:
"""
RoleMakerBase is a base class for assigning a role to current process
in distributed training.
A paddle developer can implement RoleMakerBase to design a role maker
for worker or pserver assignment.
"""
def __init__(self):
self._worker_endpoints = []
self._server_endpoints = []
self._cur_endpoint = ""
self._role_is_generated = False
self._role = None
self._current_id = -1
def _is_worker(self):
"""
return is_worker() of current process
"""
raise NotImplementedError("Please implement this method in child class")
def _is_server(self):
"""
return is_server() of current process
"""
raise NotImplementedError("Please implement this method in child class")
def _is_first_worker(self):
"""
Check whether the node is the first instance of worker.
Returns:
bool: True if this is the first node of worker,
False if not.
"""
raise NotImplementedError("Please implement this method in child class")
def _worker_num(self):
"""
Get current total worker number.
Returns:
int: worker number
"""
raise NotImplementedError("Please implement this method in child class")
def _server_num(self):
"""
Get current total server number.
Returns:
int: server number
"""
raise NotImplementedError("Please implement this method in child class")
def _worker_index(self):
"""
Get current worker id.
Returns:
int: node id
"""
raise NotImplementedError("Please implement this method in child class")
def _server_index(self):
"""
Get current server id.
Returns:
int: node id
"""
raise NotImplementedError("Please implement this method in child class")
def _role_id(self):
"""
Get current id.
Returns:
int: node id
"""
raise NotImplementedError("Please implement this method in child class")
def _node_num(self):
"""
Get the training node number
Returns:
int: node num
"""
raise NotImplementedError("Please implement this method in child class")
def _get_trainer_endpoints(self):
"""
return trainer endpoints
"""
return self._worker_endpoints
def _get_pserver_endpoints(self):
"""
return pserver endpoints
"""
return self._server_endpoints
def to_string(self):
return f"role: {self._role}, current_id: {self._current_id}, worker_endpoints: {self._worker_endpoints}, server_endpoints: {self._server_endpoints}"
def _all_gather(self, input, comm_world="worker"):
print("warning: RoleMakerBase does not have all gather worker.")
def _all_reduce(self, input, mode="sum", comm_world="worker"):
"""
Args:
input(list/numpy.array): array of one dim
output(list/numpy.array): array of one dim
mode(str): "sum" or "min" or "max"
"""
print("warning: RoleMakerBase does not have all reduce worker.")
def _barrier(self, comm_world):
"""
barrier between trainers if current role is TRAINER
"""
print("warning: RoleMakerBase does not have barrier worker.")
# def _is_heter_worker(self):
# """
# Return is_heter_worker() of current process
# """
# raise NotImplementedError("Please implement this method in child class")
# def _heter_worker_num(self):
# """
# Get current total heter-worker number.
#
# Returns:
# int: heter_worker number
# """
# raise NotImplementedError("Please implement this method in child class")
# def _get_heter_worker_endpoints(self):
# """
# Returns:
# string: all heter_trainers'endpoints
# """
# raise NotImplementedError("Please implement this method in child class")
# def _get_heter_worker_endpoint(self):
# """
# Returns:
# int: corresponding heter_trainer's endpoint
# """
# raise NotImplementedError("Please implement this method in child class")
class PaddleCloudRoleMaker(RoleMakerBase):
"""
PaddleCloudRoleMaker is an interface for distributed configuration initialization based on obtaining distributed related information from environment variables.
Examples:
.. code-block:: pycon
>>> import os
>>> import paddle.distributed.fleet as fleet
>>> os.environ["PADDLE_PSERVER_NUMS"] = "2"
>>> os.environ["PADDLE_TRAINERS_NUM"] = "2"
>>> os.environ["POD_IP"] = "127.0.0.1"
>>> os.environ["PADDLE_PORT"] = "36001"
>>> os.environ["TRAINING_ROLE"] = "PSERVER"
>>> os.environ["PADDLE_PSERVERS_IP_PORT_LIST"] = "127.0.0.1:36001,127.0.0.2:36001"
>>> os.environ["PADDLE_TRAINER_ID"] = "0"
>>> fleet.PaddleCloudRoleMaker(is_collective=False)
"""
def __init__(self, is_collective: bool = False, **kwargs: Any) -> None:
super().__init__()
self._is_collective = is_collective
self._non_distributed = False
self._kwargs = kwargs
self._role_is_generated = False
# for heterps
self._stage_id = 1
self._stage_num = 1
self._next_heter_trainer_endpoints = []
self._previous_heter_trainer_endpoints = []
self._heter_trainer_endpoints = []
self._heter_trainer_device = "cpu"
self._heter_trainer_device_type = "cpu"
self._is_heter_parameter_server_mode = False
self._stage_trainers = []
self._server_endpoints = []
self._worker_endpoints = []
self._coordinator_endpoints = None
self._with_coordinator = False
self._gloo = Gloo() # gloo instance
def _barrier(self, comm_world: str) -> None:
self._gloo.barrier(comm_world)
def _all_gather(
self, input: Any, comm_world: str = "worker"
) -> list[float]:
return self._gloo.all_gather(input, comm_world)
def _all_reduce(
self, input: Any, mode: str = "sum", comm_world: str = "worker"
) -> npt.NDArray[Any]:
return self._gloo.all_reduce(input, mode, comm_world)
def _heter_device(self) -> str:
"""
return the heter device that current heter worker is using
"""
if not self._role_is_generated:
self._generate_role()
return self._heter_trainer_device
def _heter_device_type(self) -> str:
"""
return the heter device type that current heter worker is using
"""
if not self._role_is_generated:
self._generate_role()
return self._heter_trainer_device_type
def _get_stage_id(self) -> int:
"""
return stage id of current heter worker
"""
if not self._role_is_generated:
self._generate_role()
return self._stage_id
def _get_stage_trainers(self) -> list[int]:
"""
return trainer num of all stages
"""
if not self._role_is_generated:
self._generate_role()
return self._stage_trainers
def _get_num_stage(self) -> int:
"""
return stage num
"""
if not self._role_is_generated:
self._generate_role()
return self._stage_num
def _is_worker(self) -> bool:
"""
whether current process is worker
"""
if not self._role_is_generated:
self._generate_role()
return self._role == Role.WORKER
def _is_server(self) -> bool:
"""
whether current process is server
"""
if not self._role_is_generated:
self._generate_role()
return self._role == Role.SERVER
def _is_coordinator(self) -> bool:
if not self._role_is_generated:
self._generate_role()
return self._role == Role.COORDINATOR
def _is_first_worker(self) -> bool:
"""
whether current process is worker of rank 0
"""
if not self._role_is_generated:
self._generate_role()
return self._role == Role.WORKER and self._current_id == 0
def _worker_index(self) -> int:
"""
get index of current worker
"""
if not self._role_is_generated:
self._generate_role()
return self._current_id
def _server_index(self) -> int:
"""
get index of current server
"""
if not self._role_is_generated:
self._generate_role()
return self._current_id
def _role_id(self) -> int:
"""
get index of current node
"""
if not self._role_is_generated:
self._generate_role()
return self._current_id
def _worker_num(self) -> int:
"""
return the current number of worker
"""
if not self._role_is_generated:
self._generate_role()
return self._trainers_num
def _server_num(self) -> int:
"""
return the current number of server
"""
if not self._role_is_generated:
self._generate_role()
return (
len(self._get_pserver_endpoints())
if self._get_pserver_endpoints() is not None
else 0
)
def _node_num(self) -> int:
"""
return the training node number
"""
if not self._role_is_generated:
self._generate_role()
return self._nodes_num
def _get_node_num(self) -> int:
"""
return the training node number
"""
if not self._role_is_generated:
self._generate_role()
return self._nodes_num
def _get_local_rank(self) -> str | None:
if not self._role_is_generated:
self._generate_role()
return self._local_rank
def _get_local_device_ids(self) -> str | None:
if not self._role_is_generated:
self._generate_role()
return self._local_device_ids
def _get_world_device_ids(self) -> str | None:
if not self._role_is_generated:
self._generate_role()
return self._world_device_ids
def _get_trainer_endpoints(self) -> list[str]:
"""
get endpoint of all trainers
"""
if not self._role_is_generated:
self._generate_role()
return self._worker_endpoints
def _get_trainer_endpoint(self) -> str:
if not self._role_is_generated:
self._generate_role()
assert self._role == Role.WORKER, (
"get_trainer_endpoint should be called by trainer"
)
return self._cur_endpoint
def _get_heter_worker_endpoints(self) -> list[str]:
"""
Returns:
string: all heter_trainers'endpoints
"""
if not self._role_is_generated:
self._generate_role()
assert self._heter_trainer_endpoints != [], (
"Heter Worker Endpoints Not initialized"
)
return self._heter_trainer_endpoints
def _get_heter_worker_endpoint(self) -> str:
"""
Returns:
str: corresponding heter_trainer's endpoint
"""
if not self._role_is_generated:
self._generate_role()
assert self._role == Role.HETER_WORKER, (
"_get_heter_worker_endpoint should be invoked by heter worker"
)
return self._cur_endpoint
def _get_pserver_endpoints(self) -> list[str]:
"""
get endpoint of all pservers
"""
if not self._role_is_generated:
self._generate_role()
return self._server_endpoints
def _get_coordinator_endpoints(self) -> list[str]:
if not self._role_is_generated:
self._generate_role()
return self._coordinator_endpoints
def _get_previous_trainers(self):
"""
invoked by heter worker
"""
if not self._role_is_generated:
self._generate_role()
assert self._role in (
Role.WORKER,
Role.HETER_WORKER,
), "_get_previous_trainers should be invoked by trainer or heter worker"
return self._previous_heter_trainer_endpoints
def _get_next_trainers(self) -> list[str]:
"""
invoked by heter worker
"""
if not self._role_is_generated:
self._generate_role()
assert self._role in (
Role.WORKER,
Role.HETER_WORKER,
), "_get_next_trainers should be invoked by trainer or heter worker"
return self._next_heter_trainer_endpoints
def _is_non_distributed(self) -> bool:
"""
Return True if indispensable environment for fleetrun is not found
(use python-run to launch fleet-code directly)
"""
if not self._role_is_generated:
self._generate_role()
return self._non_distributed
def _heter_worker_num(self) -> int:
"""
get heter worker nums
"""
if not self._role_is_generated:
self._generate_role()
return self._heter_trainers_num
def _is_heter_worker(self) -> bool:
"""
whether current process is heter worker
"""
if not self._role_is_generated:
self._generate_role()
return self._role == Role.HETER_WORKER
def _ps_env(self) -> None: # each role will execute it
# Environment variable PADDLE_PSERVERS_IP_PORT_LIST must be set
# format: string(ip:port,ip:port), eg. 127.0.0.1:6001,127.0.0.1:6002
self._server_endpoints = os.getenv("PADDLE_PSERVERS_IP_PORT_LIST", None)
if self._server_endpoints is None:
# back to non_distributed execution.
self._server_endpoints = ""
self._trainers_num = 1
self._role = Role.WORKER
self._current_id = 0
self._nodes_num = 1
self._heter_trainers_num = 0
self._heter_trainer_endpoints = None
self._non_distributed = True
return
self._server_endpoints = self._server_endpoints.split(",")
self._worker_endpoints = getenv_or_backup(
"PADDLE_TRAINER_ENDPOINTS", None
)
if self._worker_endpoints is not None:
self._worker_endpoints = self._worker_endpoints.split(",")
else:
self._worker_endpoints = []
self._coordinator_endpoints = os.getenv(
"PADDLE_COORDINATOR_ENDPOINTS", ""
)
if self._coordinator_endpoints == "":
print("fl-ps > coordinator address is null!")
else:
self._with_coordinator = True
self._coordinator_endpoints = self._coordinator_endpoints.split(",")
trainers_num = os.getenv("PADDLE_TRAINERS_NUM", None)
if trainers_num is None:
raise ValueError(
"Can not find PADDLE_TRAINERS_NUM, please check your environment."
)
trainers_num = int(trainers_num)
training_role = os.getenv("TRAINING_ROLE", None)
if training_role is None:
raise ValueError(
"Can not find TRAINING_ROLE, please check your environment."
)
if training_role not in [
"TRAINER",
"PSERVER",
"HETER_TRAINER",
"COORDINATOR",
]:
raise ValueError(
f"TRAINING_ROLE must be PSERVER or TRAINER or HETER_TRAINER or COORDINATOR, but get {training_role}, please check your environment."
)
# For Heter Parameter Server env setting
next_heter_trainer_eplist = os.getenv(
"PADDLE_NEXT_HETER_TRAINER_IP_PORT_LIST", ""
)
previous_heter_trainer_eplist = os.getenv(
"PADDLE_PREVIOUS_HETER_TRAINER_IP_PORT_LIST", ""
)
all_heter_trainer_eplist = os.getenv(
"PADDLE_ALL_HETER_TRAINER_IP_PORT_LIST", ""
)
if all_heter_trainer_eplist != "":
self._heter_trainer_endpoints = all_heter_trainer_eplist.split(",")
self._is_heter_parameter_server_mode = True
self._heter_trainers_num = len(self._heter_trainer_endpoints)
if previous_heter_trainer_eplist == "":
assert training_role in (
"TRAINER",
"PSERVER",
), "training_role should be trainer or pserver"
else:
try:
self._previous_heter_trainer_endpoints = (
previous_heter_trainer_eplist.split(",")
)
except:
raise ValueError(
"Can not Find PADDLE_PREVIOUS_HETER_TRAINER_IP_PORT_LIST in env or its format doesn't match the requirement: 'IP:PORT,IP:PORT' ."
)
if next_heter_trainer_eplist == "":
assert training_role in (
"HETER_TRAINER",
"PSERVER",
), "training_role should be heter trainer or pserver"
else:
try:
self._next_heter_trainer_endpoints = (
next_heter_trainer_eplist.split(",")
)
except:
raise ValueError(
"Can not Find PADDLE_NEXT_HETER_TRAINER_IP_PORT_LIST in env or its format doesn't match the requirement: 'IP:PORT,IP:PORT' ."
)
else:
self._is_heter_parameter_server_mode = False
self._heter_trainers_num = 0
if training_role == "TRAINER":
role = Role.WORKER
current_id = os.getenv("PADDLE_TRAINER_ID", None)
if current_id is None:
raise ValueError(
"Can not find PADDLE_TRAINER_ID, please check your environment."
)
current_id = int(current_id)
if self._is_heter_parameter_server_mode:
self._stage_id = os.getenv("STAGE_ID", None)
if self._stage_id is None:
raise ValueError(
"Can not find STAGE_ID, please check your environment."
)
self._stage_id = int(self._stage_id)
self._stage_num = os.getenv("STAGE_NUM", None)
if self._stage_num is None:
raise ValueError(
"Can not find STAGE_NUM, please check your environment."
)
self._stage_num = int(self._stage_num)
self._stage_trainers = os.getenv(
"PADDLE_STAGE_TRAINERS_NUM", None
)
if self._stage_trainers is None:
raise ValueError(
"Can not find PADDLE_STAGE_TRAINERS_NUM, please check your environment."
)
self._stage_trainers = tuple(
[int(x) for x in re.findall(r'\d+', self._stage_trainers)]
)
cur_port = os.getenv("PADDLE_PORT", None)
if cur_port is None:
raise ValueError(
"Can not find PADDLE_PORT, please check your environment."
)
cur_ip = os.getenv("POD_IP", None)
if cur_ip is None:
raise ValueError(
"Can not find POD_IP, please check your environment."
)
curr_endpoint = ":".join([cur_ip, cur_port])
self._cur_endpoint = curr_endpoint
elif training_role == "COORDINATOR":
print(">>> curr node is coordinator!")
role = Role.COORDINATOR
current_id = int(os.getenv("PADDLE_TRAINER_ID", "0"))
elif training_role == "PSERVER":
role = Role.SERVER
cur_port = os.getenv("PADDLE_PORT", None)
if cur_port is None:
raise ValueError(
"Can not find PADDLE_PORT, please check your environment."
)
cur_ip = os.getenv("POD_IP", None)
if cur_ip is None:
raise ValueError(
"Can not find POD_IP, please check your environment."
)
curr_endpoint = ":".join([cur_ip, cur_port])
self._cur_endpoint = curr_endpoint
current_id = self._server_endpoints.index(self._cur_endpoint)
elif training_role == "HETER_TRAINER":
role = Role.HETER_WORKER
self._stage_id = os.getenv("STAGE_ID", None)
if self._stage_id is None:
raise ValueError(
"Can not find STAGE_ID, please check your environment."
)
self._stage_id = int(self._stage_id)
self._stage_num = os.getenv("STAGE_NUM", None)
if self._stage_num is None:
raise ValueError(
"Can not find STAGE_NUM, please check your environment."
)
self._stage_num = int(self._stage_num)
self._stage_trainers = os.getenv("PADDLE_STAGE_TRAINERS_NUM", None)
if self._stage_trainers is None:
raise ValueError(
"Can not find PADDLE_STAGE_TRAINERS_NUM, please check your environment."
)
self._stage_trainers = tuple(
[int(x) for x in re.findall(r'\d+', self._stage_trainers)]
)
self._heter_trainer_device_type = os.getenv(
"HETER_DEVICE_TYPE", None
)
if self._heter_trainer_device_type is None:
raise ValueError(
"Can not find HETER_DEVICE_TYPE, please check your environment."
)
assert self._heter_trainer_device_type in (
"cpu",
"gpu",
"xpu",
), "HETER_DEVICE_TYPE should be cpu,gpu or xpu"
if self._heter_trainer_device_type == "gpu":
heter_device_id = os.getenv("FLAGS_selected_gpus", "0")
self._heter_trainer_device = ":".join(
(self._heter_trainer_device_type, heter_device_id)
)
if self._heter_trainer_device == "xpu":
heter_device_id = os.getenv("FLAGS_selected_xpus", "0")
self._heter_trainer_device = ":".join(
(self._heter_trainer_device_type, heter_device_id)
)
cur_port = os.getenv("PADDLE_PORT", None)
if cur_port is None:
raise ValueError(
"Can not find PADDLE_PORT, please check your environment."
)
cur_ip = os.getenv("POD_IP", None)
if cur_ip is None:
raise ValueError(
"Can not find POD_IP, please check your environment."
)
curr_endpoint = ":".join([cur_ip, cur_port])
self._cur_endpoint = curr_endpoint
current_id = (
all_heter_trainer_eplist.split(",").index(curr_endpoint)
+ trainers_num
)
self._trainers_num = trainers_num
self._role = role
self._current_id = current_id
self._nodes_num = len({x.split(':')[0] for x in self._worker_endpoints})
def _collective_env(self) -> None:
self._current_id = int(os.getenv("PADDLE_TRAINER_ID", "0"))
self._training_role = os.getenv("PADDLE_TRAINING_ROLE", "TRAINER")
assert self._training_role == "TRAINER"
self._role = Role.WORKER
self._worker_endpoints = getenv_or_backup("PADDLE_TRAINER_ENDPOINTS")
self._cur_endpoint = os.getenv("PADDLE_CURRENT_ENDPOINT")
if self._worker_endpoints is None:
# back to non_distributed execution.
self._worker_endpoints = "127.0.0.1:6170"
self._cur_endpoint = self._worker_endpoints
self._non_distributed = True
self._worker_endpoints = self._worker_endpoints.split(",")
self._trainers_num = len(self._worker_endpoints)
auto_tuner = os.getenv("PADDLE_AUTO_PARALLEL_CONFIG", None)
if auto_tuner is not None:
trainers_num = os.getenv("PADDLE_TRAINERS_NUM", None)
self._trainers_num = int(trainers_num)
self._nodes_num = len({x.split(':')[0] for x in self._worker_endpoints})
self._local_rank = os.getenv("PADDLE_RANK_IN_NODE")
self._local_device_ids = os.getenv("PADDLE_LOCAL_DEVICE_IDS")
self._world_device_ids = os.getenv("PADDLE_WORLD_DEVICE_IDS")
def _gloo_init(self) -> None:
# PADDLE_WITH_GLOO 1: trainer barrier, 2: all barrier
use_gloo = int(os.getenv("PADDLE_WITH_GLOO", "0"))
if use_gloo not in [1, 2]:
return
# PADDLE_GLOO_RENDEZVOUS 1: HDFS 2: FILE 3: HTTP
rendezvous_type = int(os.getenv("PADDLE_GLOO_RENDEZVOUS", "0"))
prefix = os.getenv("SYS_JOB_ID", "")
if rendezvous_type not in [
Gloo.RENDEZVOUS.HDFS,
Gloo.RENDEZVOUS.HTTP,
Gloo.RENDEZVOUS.FILE,
]:
raise ValueError(self._gloo._err_type)
need_init_all = True if use_gloo == 2 else False
if rendezvous_type == Gloo.RENDEZVOUS.HDFS:
dfs_name = os.getenv("PADDLE_GLOO_FS_NAME", "")
dfs_ugi = os.getenv("PADDLE_GLOO_FS_UGI", "")
dfs_path = os.getenv("PADDLE_GLOO_FS_PATH", "")
kwargs = {
"dfs.name": dfs_name,
"dfs.ugi": dfs_ugi,
"dfs.path": dfs_path,
"store.prefix": prefix,
}
elif rendezvous_type == Gloo.RENDEZVOUS.HTTP:
start_http_server = False
manager = Manager()
http_server_d = manager.dict()
http_server_d["running"] = False
if self._is_collective:
ep_rank_0 = self._worker_endpoints[0]
if self._is_first_worker():
start_http_server = True
else:
ep_rank_0 = os.getenv("PADDLE_GLOO_HTTP_ENDPOINT", "")
if self._is_server() and self._server_index() == 0:
start_http_server = True
ip, port = ep_rank_0.split(':')
kwargs = {
"http.host": ip,
"http.port": port,
"store.prefix": prefix,
'start_http_server': start_http_server,
'http_server_d': http_server_d,
}
else:
dfs_path = os.getenv("PADDLE_GLOO_FS_PATH", "")
kwargs = {
"dfs.path": dfs_path,
"store.prefix": prefix,
}
if rendezvous_type == Gloo.RENDEZVOUS.HDFS:
type = "HDFS"
elif rendezvous_type == Gloo.RENDEZVOUS.HTTP:
type = "HTTP"
else:
type = "FILE"
print(
f"Gloo init with {type}: need_init_all: {need_init_all}, args: {kwargs}"
)
self._gloo.init(
rendezvous=rendezvous_type,
role=self._role,
role_id=self._role_id(),
worker_num=self._worker_num(),
server_num=self._server_num(),
need_init_all=need_init_all,
kwargs=kwargs,
)
if rendezvous_type == Gloo.RENDEZVOUS.HTTP:
http_server_d['running'] = False
def _generate_role(self) -> None:
"""
generate role for role maker
"""
if not self._role_is_generated:
if not self._is_collective:
self._ps_env()
else:
self._collective_env()
self._role_is_generated = True
if not paddle.in_dynamic_mode():
self._gloo_init()
class UserDefinedRoleMaker(PaddleCloudRoleMaker):
"""
UserDefinedRoleMaker is an interface for distributed configuration initialization based on obtaining distributed related information from user-defined parameters.
Examples:
.. code-block:: pycon
>>> import paddle.distributed.fleet as fleet
>>> from paddle.distributed.fleet.base.role_maker import Role
>>> fleet.UserDefinedRoleMaker(
... current_id=0,
... role=Role.SERVER,
... worker_num=2,
... server_endpoints=["127.0.0.1:36011", "127.0.0.1:36012"],
... )
"""
def __init__(
self,
is_collective: bool = False,
init_gloo: bool = False,
**kwargs: Any,
) -> None:
super().__init__(
is_collective=is_collective, init_gloo=init_gloo, **kwargs
)
self._init_gloo = init_gloo
def _user_defined_ps_env(self) -> None:
self._server_endpoints = self._kwargs.get("server_endpoints")
self._worker_endpoints = self._kwargs.get("worker_endpoints", [])
self._trainers_num = self._kwargs.get("worker_num", 0)
if self._trainers_num == 0:
assert len(self._worker_endpoints) > 0
self._trainers_num = len(self._worker_endpoints)
self._role = self._kwargs.get("role")
self._current_id = self._kwargs.get("current_id")
if (
self._role == Role.WORKER
and len(self._worker_endpoints) > self._current_id
):
self._cur_endpoint = self._worker_endpoints[self._current_id]
elif self._role == Role.SERVER:
self._cur_endpoint = self._server_endpoints[self._current_id]
self._nodes_num = len({x.split(':')[0] for x in self._worker_endpoints})
def _user_defined_collective_env(self) -> None:
self._worker_endpoints = self._kwargs.get("worker_endpoints")
self._current_id = self._kwargs.get("current_id")
self._trainers_num = len(self._worker_endpoints)
self._training_role = Role.WORKER
self._nodes_num = len({x.split(':')[0] for x in self._worker_endpoints})
def _generate_role(self) -> None:
"""
generate role for role maker
"""
if not self._role_is_generated:
if not self._is_collective:
self._user_defined_ps_env()
else:
self._user_defined_collective_env()
self._role_is_generated = True
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