def __init__(self, client_id, base_url=allocator_base,
address_type=None, start_timeout=None, api_key=None,
runtime_id=None, params=None, placement=None,
use_recorder_ports=False,
):
super(AllocatorManager, self).__init__()
self.label = 'AllocatorManager'
self.supports_reconnect = True
self.connect_vnc = True
self.connect_rewarder = True
if address_type is None: address_type = 'public'
if address_type not in ['public', 'pod', 'private']:
raise error.Error('Bad address type specified: {}. Must be public, pod, or private.'.format(address_type))
self.client_id = client_id
self.address_type = address_type
if start_timeout is None:
start_timeout = 20 * 60
self.start_timeout = start_timeout
self.params = params
self.placement = placement
self.use_recorder_ports = use_recorder_ports
# if base_url is None:
# base_url = scoreboard.api_base
# if base_url is None:
# base_url = gym_base_url
# if api_key is None:
# api_key = scoreboard.api_key
# if api_key is None:
# raise gym.error.AuthenticationError("""You must provide an OpenAI Gym API key.
# (HINT: Set your API key using "gym.scoreboard.api_key = .." or "export OPENAI_GYM_API_KEY=..."). You can find your API key in the OpenAI Gym web interface: https://gym.openai.com/settings/profile.""")
if api_key is None:
api_key = _api_key
self._requestor = AllocatorClient(self.label, api_key, base_url=base_url)
self.base_url = base_url
# These could be overridden on a per-allocation basis, if you
# want heterogeoneous envs. We don't support those currently
# in the higher layers, but this layer could support it
# easily.
self.runtime_id = runtime_id
self.pending = {}
self.error_buffer = utils.ErrorBuffer()
self.requests = queue.Queue()
self.ready = queue.Queue()
self._reconnect_history = {}
self._sleep = 1
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