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hub / github.com/alibaba/graph-learn / init

Method init

graphlearn/python/graph.py:375–430  ·  view source on GitHub ↗

Initialize the graph object in local mode or distributed mode. If deployed in local mode, just call `g.init()` without any parameters. If in distributed, you should care about WORKER mode and SERVER mode. Args: task_index (int): Current task index. If in WORKER mode, it

(self, task_index=0, task_count=1,
           cluster="", job_name="", **kwargs)

Source from the content-addressed store, hash-verified

373 self._edge_sources.append(edge_source_reverse)
374
375 def init(self, task_index=0, task_count=1,
376 cluster="", job_name="", **kwargs):
377 """ Initialize the graph object in local mode or distributed mode.
378
379 If deployed in local mode, just call `g.init()` without any parameters.
380 If in distributed, you should care about WORKER mode and SERVER mode.
381
382 Args:
383 task_index (int): Current task index.
384 If in WORKER mode, it means the current worker index.
385 If in SERVER mode, it means the current server index.
386 task_count (int): Total task count. Only needed in WORKER mode.
387 It means in the total worker count.
388 cluster (dict | json string): Only needed in SERVER mode.
389 3 kinds of schemas are supported:
390 cluster = {
391 "server_count": 2,
392 "client_count": 4,
393 "tracker": "root://graphlearn"
394 }
395 cluster = {
396 "server": "127.0.0.2:6666,127.0.0.3:7777",
397 "client": "127.0.0.4:8888,127.0.0.5:9999"
398 }
399 cluster = {
400 "server": "127.0.0.2:6666,127.0.0.3:7777",
401 "client_count", 2
402 }
403 server_count (int): count of servers.
404 client_count (int): count of clients.
405 server (string): hosts of servers, split by ','.
406 job_name (str): `client` or `server`. Only needed in SERVER mode.
407 kwargs:
408 tracker (string): Optional tracker path for WORKER mode.
409 hosts (string): Optional worker hosts for WORKER mode.
410 """
411 if self._with_vineyard:
412 pywrap.set_storage_mode(8)
413 pywrap.set_tracker_mode(0)
414
415 if not cluster and task_count == 1:
416 # Local mode
417 pywrap.set_deploy_mode(pywrap.DeployMode.LOCAL)
418 self.deploy_in_local_mode(task_index)
419 elif not cluster:
420 if task_count > 1 or kwargs.get("hosts") is not None:
421 # WORKER mode
422 pywrap.set_deploy_mode(pywrap.DeployMode.WORKER)
423 tracker = kwargs.get("tracker", "root://graphlearn")
424 hosts = kwargs.get("hosts")
425 self.deploy_in_worker_mode(tracker, hosts, task_index, task_count)
426 else:
427 # SERVER mode
428 pywrap.set_deploy_mode(pywrap.DeployMode.SERVER)
429 self.deploy_in_server_mode(task_index, cluster, job_name)
430 return self
431
432 def deploy_in_local_mode(self, task_index):

Callers 15

init_vineyardMethod · 0.95
mainFunction · 0.95
mainFunction · 0.95
mainFunction · 0.95
mainFunction · 0.95
mainFunction · 0.95
mainFunction · 0.95
mainFunction · 0.95
deploy_in_local_modeMethod · 0.45
deploy_in_worker_modeMethod · 0.45
deploy_in_server_modeMethod · 0.45
_server_managerFunction · 0.45

Calls 4

deploy_in_local_modeMethod · 0.95
deploy_in_worker_modeMethod · 0.95
deploy_in_server_modeMethod · 0.95
getMethod · 0.45

Tested by 15

mainFunction · 0.76
mainFunction · 0.76
mainFunction · 0.76
mainFunction · 0.76
mainFunction · 0.76
mainFunction · 0.76
mainFunction · 0.76
init_graphMethod · 0.36
test_weighted_labeledMethod · 0.36
test_labeledMethod · 0.36