def ray_start_cluster():
node_args = {
"num_cpus": 8,
"_internal_config": json.dumps({
"initial_reconstruction_timeout_milliseconds": 1000,
"num_heartbeats_timeout": 10
})
}
# Start with 4 worker nodes and 8 cores each.
cluster = Cluster(
initialize_head=True, connect=True, head_node_args=node_args)
workers = []
for _ in range(4):
workers.append(cluster.add_node(**node_args))
cluster.wait_for_nodes()
yield cluster
ray.shutdown()
cluster.shutdown()
def ray_start_cluster():
node_args = {
"resources":
dict(CPU=8),
"_internal_config":
json.dumps({
"initial_reconstruction_timeout_milliseconds": 1000,
"num_heartbeats_timeout": 10
})
}
# Start with 4 worker nodes and 8 cores each.
g = Cluster(initialize_head=True, connect=True, head_node_args=node_args)
workers = []
for _ in range(4):
workers.append(g.add_node(**node_args))
g.wait_for_nodes()
yield g
ray.shutdown()
g.shutdown()
def ray_start_cluster():
node_args = {
"num_cpus":
4,
"_internal_config":
json.dumps({
"initial_reconstruction_timeout_milliseconds": 1000,
"num_heartbeats_timeout": 10
})
}
# Start with 3 worker nodes and 4 cores each.
cluster = Cluster(initialize_head=True,
connect=True,
head_node_args=node_args)
workers = []
for _ in range(3):
workers.append(cluster.add_node(**node_args))
cluster.wait_for_nodes()
yield cluster
ray.shutdown()
cluster.shutdown()
