def init(self, cluster="", job_name="", task_index=0, **kwargs):
""" Initialize the graph with creating graph server instance with
given cluster env info.
Args:
cluster (dict | josn str): Empty dict or string when Graph runs with
local mode. Otherwise, cluster includes server_count, client_count
and traker.
server_count (int): count of servers.
client_count (int): count of clients.
traker (str): traker path.
job_name (str): `client` or `server`, default empty means Graph runs
with local mode.
task_index (int): index of current server of client.
"""
tracker = ""
if not cluster:
self._deploy_mode = 0
pywrap.set_deploy_mode(self._deploy_mode)
self._client = pywrap.in_memory_client()
task_index = 0
server_count = 1
else:
self._deploy_mode = 1
pywrap.set_deploy_mode(self._deploy_mode)
if isinstance(cluster, dict):
cluster_spec = cluster
elif isinstance(cluster, str):
cluster_spec = json.loads(cluster)
server_count = cluster_spec.get("server_count")
client_count = cluster_spec.get("client_count")
if not server_count or not client_count:
raise ValueError("cluster is composed of server_count,"
"worker_count and tracker")
tracker = cluster_spec.get("tracker")
pywrap.set_server_count(server_count)
pywrap.set_client_count(client_count)
if tracker:
pywrap.set_tracker(tracker)
if job_name == "client":
pywrap.set_client_id(task_index)
self._client = pywrap.rpc_client()
self._server = None
else:
if job_name == "server":
self._client = None
if not tracker and kwargs.get("tracker"):
tracker = kwargs["tracker"]
if tracker:
self._server = Server(task_index, server_count, tracker)
else:
self._server = Server(task_index, server_count)
self._server.start()
self._server.init(self._edge_sources, self._node_sources)
return self
def deploy_in_worker_mode(self, tracker, hosts, task_index, task_count):
if hosts:
pywrap.set_server_hosts(hosts)
hosts = hosts.split(',')
host = hosts[task_index]
task_count = len(hosts)
else:
host = "0.0.0.0:0"
assert task_index < task_count
pywrap.set_client_id(task_index)
pywrap.set_client_count(task_count)
pywrap.set_server_count(task_count)
pywrap.set_tracker(tracker)
self._client = pywrap.in_memory_client()
self._server = Server(task_index, task_count, host, tracker)
self._server.start()
self._server.init(self._edge_sources, self._node_sources)
def deploy_in_local_mode(self):
self._client = pywrap.in_memory_client()
self._server = Server(0, 1, "", "")
self._server.start()
self._server.init(self._edge_sources, self._node_sources)
def init(self,
task_index=0,
task_count=1,
cluster="",
job_name="",
**kwargs):
""" Initialize the graph with creating graph server instance with
given cluster env info.
Args:
task_index (int): Current task index in in_memory mode or current
server or client index in independent mode.
task_count (int): Total task count in in_memory mode.
cluster (dict | josn str): Empty dict or string when Graph runs with
local mode. Otherwise, cluster includes server_count, client_count
and tracker.
server_count (int): count of servers.
client_count (int): count of clients.
tracker (str): tracker path.
job_name (str): `client` or `server`, default empty means Graph runs
with local mode.
"""
# In memory mode, local or distribute.
if not cluster:
assert job_name == "", "Initialize local server with empty `cluster`."
server_count = task_count
tracker = kwargs.get("tracker", 'root://graphlearn')
if server_count == 1:
assert task_index == 0, "Local mode, task_index=0, task_count=1"
self._deploy_mode = 0 # Local in_memory mode.
else:
assert isinstance(server_count, int)
assert isinstance(task_index, int)
assert server_count > task_index
self._deploy_mode = 2 # Distribute in_memory mode.
pywrap.set_server_count(server_count)
pywrap.set_client_count(server_count)
pywrap.set_tracker(tracker)
pywrap.set_client_id(task_index)
pywrap.set_deploy_mode(self._deploy_mode)
self._client = pywrap.in_memory_client()
else: # Distribute independent mode.
assert job_name in ("client", "server")
if isinstance(cluster, dict):
cluster_spec = cluster
elif isinstance(cluster, str):
cluster_spec = json.loads(cluster)
else:
raise ValueError("cluster must be dict or json string.")
server_count = cluster_spec.get("server_count")
client_count = cluster_spec.get("client_count")
tracker = cluster_spec.get("tracker", 'root://graphlearn')
if not server_count or not client_count:
raise ValueError("cluster is composed of server_count,"
"worker_count and tracker")
self._deploy_mode = 1
pywrap.set_deploy_mode(self._deploy_mode)
pywrap.set_server_count(server_count)
pywrap.set_client_count(client_count)
os.system('mkdir -p {}'.format(tracker))
if job_name == "client":
pywrap.set_tracker(tracker)
pywrap.set_client_id(task_index)
self._client = pywrap.rpc_client()
self._server = None
else:
if job_name == "server":
self._client = None
self._server = Server(task_index, server_count, tracker)
self._server.start()
self._server.init(self._edge_sources, self._node_sources)
return self
def init(self,
task_index=0,
task_count=1,
cluster="",
job_name="",
**kwargs):
""" Initialize the graph with creating graph server instance with
given cluster env info.
Args:
task_index (int): Current task index in in_memory mode or current
server or client index in independent mode.
task_count (int): Total task count in in_memory mode.
cluster (dict | josn str): Empty dict or string when Graph runs with
local mode. Otherwise, cluster includes (server_count, client_count,
tracker) or (server, client) or (server, client_count)
server_count (int): count of servers.
client_count (int): count of clients.
tracker (str): tracker path.
server (string): hosts of servers, split by ','.
job_name (str): `client` or `server`, default empty means Graph runs
with local mode.
kwargs:
tracker (string): tracker path for in-memory mode.
hosts (string): hosts of servers for in-memory mode.
"""
# In memory mode, local or distribute.
if not job_name:
assert cluster == ""
tracker = kwargs.get("tracker", 'root://graphlearn')
hosts = kwargs.get("hosts")
host = "0.0.0.0:0"
if hosts:
pywrap.set_server_hosts(hosts)
hosts = hosts.split(',')
host = hosts[task_index]
task_count = len(hosts)
assert task_index < task_count
# Local in-memory mode.
if task_count == 1:
pywrap.set_deploy_mode(0)
# Distribute in-memory mode.
else:
pywrap.set_deploy_mode(2)
pywrap.set_server_count(task_count)
pywrap.set_client_count(task_count)
pywrap.set_tracker(tracker)
pywrap.set_client_id(task_index)
self._client = pywrap.in_memory_client()
self._server = Server(task_index, task_count, host, tracker)
self._server.start()
self._server.init(self._edge_sources, self._node_sources)
# Distribute service mode.
else:
if isinstance(cluster, dict):
cluster_spec = cluster
elif isinstance(cluster, str):
cluster_spec = json.loads(cluster)
else:
raise ValueError("cluster must be dict or json string.")
tracker = cluster_spec.get("tracker", 'root://graphlearn')
server_count = cluster_spec.get("server_count")
servers = cluster_spec.get("server")
if servers:
pywrap.set_server_hosts(servers)
servers = servers.split(',')
server_count = len(servers)
client_count = cluster_spec.get("client_count")
clients = cluster_spec.get("client")
if clients:
client_count = len(clients.split(','))
if not server_count or not client_count:
raise ValueError(
"cluster is composed of"
" (server_count, client_count, tracker)"
" or (server, client) or (server, client_count)}")
pywrap.set_server_count(server_count)
pywrap.set_client_count(client_count)
pywrap.set_deploy_mode(1)
if job_name == "client":
pywrap.set_tracker(tracker)
pywrap.set_client_id(task_index)
self._client = pywrap.rpc_client()
self._server = None
elif job_name == "server":
self._client = None
server_host = "0.0.0.0:0" if not servers else servers[
task_index]
self._server = Server(task_index, server_count, server_host,
tracker)
self._server.start()
self._server.init(self._edge_sources, self._node_sources)
else:
raise ValueError("Only support client and server for GL.")
return self