mirror of
https://github.com/vale981/ray
synced 2025-03-10 13:26:39 -04:00
30 lines
593 B
Python
30 lines
593 B
Python
|
# trainer.py
|
||
|
|
from collections import Counter
|
||
|
|
import os
|
||
|
|
import sys
|
||
|
|
import time
|
||
|
|
import ray
|
||
|
|
|
||
|
|
num_cpus = int(sys.argv[1])
|
||
|
|
|
||
|
|
ray.init(address=os.environ["ip_head"])
|
||
|
|
|
||
|
|
print("Nodes in the Ray cluster:")
|
||
|
|
print(ray.nodes())
|
||
|
|
|
||
|
|
|
||
|
|
@ray.remote
|
||
|
|
def f():
|
||
|
|
time.sleep(1)
|
||
|
|
return ray.services.get_node_ip_address()
|
||
|
|
|
||
|
|
|
||
|
|
# The following takes one second (assuming that
|
||
|
|
# ray was able to access all of the allocated nodes).
|
||
|
|
for i in range(60):
|
||
|
|
start = time.time()
|
||
|
|
ip_addresses = ray.get([f.remote() for _ in range(num_cpus)])
|
||
|
|
print(Counter(ip_addresses))
|
||
|
|
end = time.time()
|
||
|
|
print(end - start)
|