mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
29 lines
1 KiB
Python
29 lines
1 KiB
Python
|
from ray.rllib.policy.policy import PolicySpec
|
||
|
|
from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID
|
||
|
|
from ray.rllib.utils.typing import PartialTrainerConfigDict
|
||
|
|
|
||
|
|
|
||
|
|
def check_multi_agent(config: PartialTrainerConfigDict):
|
||
|
|
"""Checks, whether a (partial) config defines a multi-agent setup.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
config (PartialTrainerConfigDict): The user/Trainer/Policy config
|
||
|
|
to check for multi-agent.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
Tuple[MultiAgentPolicyConfigDict, bool]: The resulting (all
|
||
|
|
fixed) multi-agent policy dict and whether we have a
|
||
|
|
multi-agent setup or not.
|
||
|
|
"""
|
||
|
|
multiagent_config = config["multiagent"]
|
||
|
|
policies = multiagent_config.get("policies")
|
||
|
|
if not policies:
|
||
|
|
policies = {DEFAULT_POLICY_ID}
|
||
|
|
if isinstance(policies, set):
|
||
|
|
policies = multiagent_config["policies"] = {
|
||
|
|
pid: PolicySpec()
|
||
|
|
for pid in policies
|
||
|
|
}
|
||
|
|
is_multiagent = len(policies) > 1 or DEFAULT_POLICY_ID not in policies
|
||
|
|
return policies, is_multiagent
|