def __init__(
self,
env_class,
agent_class,
network_fn,
config,
scope,
init_hooks,
compress_episodes,
):
gin.parse_config(config, skip_unknown=True)
for hook in init_hooks:
hook()
import tensorflow as tf
tf.config.threading.set_inter_op_parallelism_threads(1)
tf.config.threading.set_intra_op_parallelism_threads(1)
with gin.config_scope(scope):
self.env = env_class()
self.agent = agent_class()
self._request_handler = core.RequestHandler(network_fn)
self._compress_episodes = compress_episodes
def __init__(
self,
env_class,
agent_class,
network_fn,
model_class,
model_network_fn,
config,
init_hooks,
):
# Limit number of threads used between independent tf.op-s to 1.
import tensorflow as tf # pylint: disable=import-outside-toplevel
tf.config.threading.set_inter_op_parallelism_threads(1)
tf.config.threading.set_intra_op_parallelism_threads(1)
gin.parse_config(config, skip_unknown=True)
for hook in init_hooks:
hook()
self.env = env_class()
self.agent = (agent_class() if model_class is None else
agent_class(model_class=model_class))
# Metrics cause some problems with Ray, so we switch them off,
# as we don't train any networks inside the worker.
if network_fn:
network_fn = functools.partial(network_fn, metrics=None)
if model_network_fn:
model_network_fn = functools.partial(model_network_fn,
metrics=None)
self._request_handler = core.RequestHandler(
network_fn, model_network_fn=model_network_fn)
def __init__(self, env_class, agent_class, network_fn, n_envs, output_dir):
super().__init__(env_class, agent_class, network_fn, n_envs, output_dir)
def make_env_and_agent():
env = env_class()
agent = agent_class()
return (env, agent)
self._envs_and_agents = [make_env_and_agent() for _ in range(n_envs)]
self._request_handler = core.RequestHandler(network_fn)
def __init__(self, env_class, agent_class, network_fn, config):
# Limit number of threads used between independent tf.op-s to 1.
import tensorflow as tf # pylint: disable=import-outside-toplevel
tf.config.threading.set_inter_op_parallelism_threads(1)
tf.config.threading.set_intra_op_parallelism_threads(1)
# TODO(pj): Test that skip_unknown is required!
gin.parse_config(config, skip_unknown=True)
self.env = env_class()
self.agent = agent_class()
self._request_handler = core.RequestHandler(network_fn)
def __init__(self,
env_class,
agent_class,
network_fn,
n_envs,
output_dir,
model_class=None,
model_network_fn=None):
super().__init__(env_class, agent_class, network_fn, n_envs,
output_dir, model_class, model_network_fn)
def make_env_and_agent():
env = env_class()
agent = (agent_class() if model_class is None else agent_class(
model_class=model_class))
return env, agent
self._envs_and_agents = [make_env_and_agent() for _ in range(n_envs)]
self._request_handler = core.RequestHandler(network_fn,
model_network_fn)