Hey looks like you were able to create a new topic here, makes sense as this is more of a Core issue.
Depending on the nature of the problem, you may be able to simplify the repro even further. In the example below, we force f
to be executed on a worker node, and try to access the results (from object store) on the head node.
import ray
import numpy as np
@ray.remote
def f():
return np.arange(100_000)
ip_resource = "node:<WORKER_NODE_IP>"
result = ray.get(f.options(resources={ip_resource: 0.01}).remote())