def default_resource_request(cls, config):
cf = dict(cls._default_config, **config)
Agent._validate_config(cf)
return Resources(
cpu=cf["num_cpus_for_driver"],
gpu=cf["num_gpus"],
extra_cpu=cf["num_cpus_per_worker"] * cf["num_workers"] +
cf["num_aggregation_workers"],
extra_gpu=cf["num_gpus_per_worker"] * cf["num_workers"])
def default_resource_request(cls, config):
cf = dict(cls._default_config, **config)
Agent._validate_config(cf)
if cf["optimizer_class"] == "AsyncReplayOptimizer":
extra = cf["optimizer"]["num_replay_buffer_shards"]
else:
extra = 0
return Resources(
cpu=cf["num_cpus_for_driver"],
gpu=cf["num_gpus"],
extra_cpu=cf["num_cpus_per_worker"] * cf["num_workers"] + extra,
extra_gpu=cf["num_gpus_per_worker"] * cf["num_workers"])
def default_resource_request(cls, config):
cf = dict(cls._default_config, **config)
Agent._validate_config(cf)
if cf["optimizer_class"] == "AsyncReplayOptimizer":
extra = cf["optimizer"]["num_replay_buffer_shards"]
else:
extra = 0
return Resources(
cpu=cf["num_cpus_for_driver"],
gpu=cf["num_gpus"],
extra_cpu=cf["num_cpus_per_worker"] * cf["num_workers"] + extra,
extra_gpu=cf["num_gpus_per_worker"] * cf["num_workers"])
def __getstate__(self):
state = Agent.__getstate__(self)
state.update({
"num_target_updates": self.num_target_updates,
"last_target_update_ts": self.last_target_update_ts,
})
return state
def __getstate__(self):
state = Agent.__getstate__(self)
state.update({
"num_target_updates": self.num_target_updates,
"last_target_update_ts": self.last_target_update_ts,
})
return state
def __setstate__(self, state):
Agent.__setstate__(self, state)
self.num_target_updates = state["num_target_updates"]
self.last_target_update_ts = state["last_target_update_ts"]
def __setstate__(self, state):
Agent.__setstate__(self, state)
self.num_target_updates = state["num_target_updates"]
self.last_target_update_ts = state["last_target_update_ts"]
