@@ -70,10 +70,10 @@ def relabel_dataset_rtg(
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q_algo: Trained Q-learning algoirthm.
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k (int): Context length for DT.
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seed (int): The random seed.
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- num_action_samples (int, optional): The number of action samples for
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+ num_action_samples (int, optional): The number of action samples for
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V function estimation. Defaults to 10.
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gpu (int, optional): The GPU device ID. Defaults to None.
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- timestamp (str, optional): The timestamp for experiment name.
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+ timestamp (str, optional): The timestamp for experiment name.
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Defaults to None.
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"""
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# fix seed
@@ -130,7 +130,7 @@ def fit_cql(
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env (gym.Env): The environment instance.
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seed (int): The random seed.
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gpu (int, optional): The GPU device ID. Defaults to None.
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- timestamp (str, optional): The timestamp for experiment name.
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+ timestamp (str, optional): The timestamp for experiment name.
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Defaults to None.
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"""
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# fix seed
@@ -188,7 +188,7 @@ def fit_iql(
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env (gym.Env): The environment instance.
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seed (int): The random seed.
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gpu (int, optional): The GPU device ID. Defaults to None.
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- timestamp (str, optional): The timestamp for experiment name.
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+ timestamp (str, optional): The timestamp for experiment name.
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Defaults to None.
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"""
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# fix seed
@@ -258,7 +258,7 @@ def fit_dt(
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env (gym.Env): The environment instance.
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seed (int): The random seed.
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gpu (int, optional): The GPU device ID. Defaults to None.
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- timestamp (str, optional): The timestamp for experiment name.
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+ timestamp (str, optional): The timestamp for experiment name.
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Defaults to None.
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"""
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# fix seed
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