def __init__(self, encoder_major=None, encoder_minor=None, hparams=None):
EncoderBase.__init__(self, hparams)
encoder_major_hparams = utils.get_instance_kwargs(
None, self._hparams.encoder_major_hparams)
encoder_minor_hparams = utils.get_instance_kwargs(
None, self._hparams.encoder_minor_hparams)
if encoder_major is not None:
self._encoder_major = encoder_major
else:
with tf.variable_scope(self.variable_scope.name):
with tf.variable_scope('encoder_major'):
self._encoder_major = utils.check_or_get_instance(
self._hparams.encoder_major_type,
encoder_major_hparams,
['texar.modules.encoders', 'texar.custom'])
if encoder_minor is not None:
self._encoder_minor = encoder_minor
elif self._hparams.config_share:
with tf.variable_scope(self.variable_scope.name):
with tf.variable_scope('encoder_minor'):
self._encoder_minor = utils.check_or_get_instance(
self._hparams.encoder_major_type,
encoder_major_hparams,
['texar.modules.encoders', 'texar.custom'])
else:
with tf.variable_scope(self.variable_scope.name):
with tf.variable_scope('encoder_minor'):
self._encoder_minor = utils.check_or_get_instance(
self._hparams.encoder_minor_type,
encoder_minor_hparams,
['texar.modules.encoders', 'texar.custom'])
def __init__(self,
env_config,
sess=None,
policy=None,
policy_kwargs=None,
policy_caller_kwargs=None,
learning_rate=None,
hparams=None):
EpisodicAgentBase.__init__(self, env_config, hparams)
self._sess = sess
self._lr = learning_rate
self._discount_factor = self._hparams.discount_factor
with tf.variable_scope(self.variable_scope):
if policy is None:
kwargs = utils.get_instance_kwargs(
policy_kwargs, self._hparams.policy_hparams)
policy = utils.check_or_get_instance(
self._hparams.policy_type,
kwargs,
module_paths=['texar.modules', 'texar.custom'])
self._policy = policy
self._policy_caller_kwargs = policy_caller_kwargs or {}
self._observs = []
self._actions = []
self._rewards = []
self._train_outputs = None
self._build_graph()
def _build_network(self, network, kwargs):
if network is not None:
self._network = network
else:
kwargs = utils.get_instance_kwargs(kwargs,
self._hparams.network_hparams)
self._network = utils.check_or_get_instance(
self._hparams.network_type,
kwargs,
module_paths=['texar.modules', 'texar.custom'])
def __init__(self,
env_config,
sess=None,
actor=None,
actor_kwargs=None,
critic=None,
critic_kwargs=None,
hparams=None):
EpisodicAgentBase.__init__(self, env_config=env_config, hparams=hparams)
self._sess = sess
self._num_actions = self._env_config.action_space.high - \
self._env_config.action_space.low
with tf.variable_scope(self.variable_scope):
if actor is None:
kwargs = utils.get_instance_kwargs(
actor_kwargs, self._hparams.actor_hparams)
kwargs.update(dict(env_config=env_config, sess=sess))
actor = utils.get_instance(
class_or_name=self._hparams.actor_type,
kwargs=kwargs,
module_paths=['texar.agents', 'texar.custom'])
self._actor = actor
if critic is None:
kwargs = utils.get_instance_kwargs(
critic_kwargs, self._hparams.critic_hparams)
kwargs.update(dict(env_config=env_config, sess=sess))
critic = utils.get_instance(
class_or_name=self._hparams.critic_type,
kwargs=kwargs,
module_paths=['texar.agents', 'texar.custom'])
self._critic = critic
if self._actor._discount_factor != self._critic._discount_factor:
raise ValueError('discount_factor of the actor and the critic '
'must be the same.')
self._discount_factor = self._actor._discount_factor
self._observs = []
self._actions = []
self._rewards = []
def __init__(self,
env_config,
sess=None,
actor=None,
actor_kwargs=None,
critic=None,
critic_kwargs=None,
hparams=None):
EpisodicAgentBase.__init__(self,
env_config=env_config,
hparams=hparams)
self._sess = sess
self._num_actions = self._env_config.action_space.high - \
self._env_config.action_space.low
with tf.variable_scope(self.variable_scope):
if actor is None:
kwargs = utils.get_instance_kwargs(actor_kwargs,
self._hparams.actor_kwargs)
kwargs.update(dict(env_config=env_config, sess=sess))
actor = utils.get_instance(
class_or_name=self._hparams.actor_type,
kwargs=kwargs,
module_paths=['texar.agents', 'texar.custom'])
self.actor = actor
if critic is None:
kwargs = utils.get_instance_kwargs(critic_kwargs,
self._hparams.critic_kwargs)
kwargs.update(dict(env_config=env_config, sess=sess))
critic = utils.get_instance(
class_or_name=self._hparams.critic_type,
kwargs=kwargs,
module_paths=['texar.agents', 'texar.custom'])
self.critic = critic
assert self.actor._discount_factor == self.critic._discount_factor
self._discount_factor = self.actor._discount_factor
def __init__(self,
env_config,
sess=None,
qnet=None,
target=None,
qnet_kwargs=None,
qnet_caller_kwargs=None,
replay_memory=None,
replay_memory_kwargs=None,
exploration=None,
exploration_kwargs=None,
hparams=None):
EpisodicAgentBase.__init__(self, env_config, hparams)
self._sess = sess
self._cold_start_steps = self._hparams.cold_start_steps
self._sample_batch_size = self._hparams.sample_batch_size
self._update_period = self._hparams.update_period
self._discount_factor = self._hparams.discount_factor
self._target_update_strategy = self._hparams.target_update_strategy
self._num_actions = self._env_config.action_space.high - \
self._env_config.action_space.low
with tf.variable_scope(self.variable_scope):
if qnet is None:
kwargs = utils.get_instance_kwargs(qnet_kwargs,
self._hparams.qnet_hparams)
qnet = utils.check_or_get_instance(
ins_or_class_or_name=self._hparams.qnet_type,
kwargs=kwargs,
module_paths=['texar.modules', 'texar.custom'])
target = utils.check_or_get_instance(
ins_or_class_or_name=self._hparams.qnet_type,
kwargs=kwargs,
module_paths=['texar.modules', 'texar.custom'])
self._qnet = qnet
self._target = target
self._qnet_caller_kwargs = qnet_caller_kwargs or {}
if replay_memory is None:
kwargs = utils.get_instance_kwargs(
replay_memory_kwargs, self._hparams.replay_memory_hparams)
replay_memory = utils.check_or_get_instance(
ins_or_class_or_name=self._hparams.replay_memory_type,
kwargs=kwargs,
module_paths=['texar.core', 'texar.custom'])
self._replay_memory = replay_memory
if exploration is None:
kwargs = utils.get_instance_kwargs(
exploration_kwargs, self._hparams.exploration_hparams)
exploration = utils.check_or_get_instance(
ins_or_class_or_name=self._hparams.exploration_type,
kwargs=kwargs,
module_paths=['texar.core', 'texar.custom'])
self._exploration = exploration
self._build_graph()
self._observ = None
self._action = None
self._timestep = 0