def create_remote_workers(self, cls, num_actors, agent_config, worker_spec,
*args):
"""
Creates Ray actors for remote execution.
Args:
cls (Union[RayValueWorker, RayPolicyWorker]): RayActor class.
num_actors (int): Num RayActor to create.
agent_config (dict): Agent config.
worker_spec (dict): Worker spec.
*args (any): Arguments for RayActor class.
Returns:
list: Remote Ray actors.
"""
workers = []
cls_as_remote = cls.as_remote(num_cpus=self.num_cpus_per_worker,
num_gpus=self.num_gpus_per_worker).remote
# Create remote objects and schedule init tasks.
ray_constant_exploration = worker_spec.get("ray_constant_exploration",
False)
for i in range_(num_actors):
if ray_constant_exploration is True:
exploration_val = worker_exploration(i, num_actors)
worker_spec["ray_exploration"] = exploration_val
worker = cls_as_remote(deepcopy(agent_config), worker_spec, *args)
self.worker_ids[worker] = "worker_{}".format(i)
workers.append(worker)
self.logger.info("Successfully built agent num {}.".format(i))
return workers
def create_remote_workers(self, cls, num_actors, agent_config, worker_spec,
*args):
"""
Creates Ray actors for remote execution.
Args:
cls (RayWorker): Actor class, must be an instance of RayWorker.
num_actors (int): Num
agent_config (dict): Agent config.
worker_spec (dict): Worker spec.
*args (any): Arguments for RayWorker class.
Returns:
list: Remote Ray actors.
"""
workers = []
init_tasks = []
cls_as_remote = cls.as_remote(num_cpus=self.num_cpus_per_worker,
num_gpus=self.num_gpus_per_worker).remote
# Create remote objects and schedule init tasks.
ray_constant_exploration = worker_spec.get("ray_constant_exploration",
False)
for i in range_(num_actors):
if ray_constant_exploration is True:
exploration_val = worker_exploration(i, num_actors)
worker_spec["ray_exploration"] = exploration_val
worker = cls_as_remote(deepcopy(agent_config), worker_spec, *args)
self.worker_ids[worker] = "worker_{}".format(i)
workers.append(worker)
build_result = worker.init_agent.remote()
init_tasks.append(build_result)
ready, not_ready = ray.wait(init_tasks, num_returns=len(init_tasks))
for i, res in enumerate(ready):
result = ray.get(res)
if result:
self.logger.info("Successfully built agent num {}.".format(i))
return workers