def setup_mixins(policy, obs_space, action_space, config):
# copied from PPO
KLCoeffMixin.__init__(policy, config)
EntropyCoeffSchedule.__init__(policy, config["entropy_coeff"],
config["entropy_coeff_schedule"])
LearningRateSchedule.__init__(policy, config["lr"], config["lr_schedule"])
# hack: put in a noop VF so some of the inherited PPO code runs
policy.value_function = tf.zeros(
tf.shape(policy.get_placeholder(SampleBatch.CUR_OBS))[0])
def setup_mixins(policy, obs_space, action_space, config):
ValueNetworkMixin.__init__(policy, obs_space, action_space, config)
KLCoeffMixin.__init__(policy, config)
EntropyCoeffSchedule.__init__(policy, config["entropy_coeff"],
config["entropy_coeff_schedule"])
LearningRateSchedule.__init__(policy, config["lr"], config["lr_schedule"])
ImitationLearningRateSchedule.__init__(
policy, config["model"]["custom_options"]["num_imitation_iters"],
config["model"]["custom_options"]["imitation_weight"], config)
def setup_mixins(policy, obs_space, action_space, config):
KLCoeffMixin.__init__(policy, config)
EntropyCoeffSchedule.__init__(policy, config["entropy_coeff"],
config["entropy_coeff_schedule"])
LearningRateSchedule.__init__(policy, config["lr"], config["lr_schedule"])
ImitationLearningRateSchedule.__init__(policy, config["model"]["custom_options"]["num_imitation_iters"],
config["model"]["custom_options"]["imitation_weight"], config)
# hack: put in a noop VF so some of the inherited PPO code runs
policy.value_function = tf.zeros(
tf.shape(policy.get_placeholder(SampleBatch.CUR_OBS))[0])
def setup_mixins(policy, obs_space, action_space, config):
"""Copied from PPO"""
KLCoeffMixin.__init__(policy, config)
EntropyCoeffSchedule.__init__(policy, config["entropy_coeff"],
config["entropy_coeff_schedule"])
LearningRateSchedule.__init__(policy, config["lr"], config["lr_schedule"])
def setup_mixins(policy, obs_space, action_space, config):
LearningRateSchedule.__init__(policy, config["lr"], config["lr_schedule"])
KLCoeffMixin.__init__(policy, config)
ValueNetworkMixin.__init__(policy)
