def __init__(
self,
model: ModelBase,
state_preprocessor: Preprocessor,
state_feature_config: rlt.ModelFeatureConfig,
):
super().__init__()
self.model = model
self.state_preprocessor = state_preprocessor
self.state_feature_config = state_feature_config
self.sparse_preprocessor = make_sparse_preprocessor(
self.state_feature_config, device=torch.device("cpu"))
def __init__(
self,
id_list_keys: List[str],
id_score_list_keys: List[str],
feature_config: rlt.ModelFeatureConfig,
device: torch.device,
):
self.id_list_keys = id_list_keys
self.id_score_list_keys = id_score_list_keys
assert set(id_list_keys).intersection(set(id_score_list_keys)) == set()
self.feature_config = feature_config
self.sparse_preprocessor = make_sparse_preprocessor(
feature_config=feature_config, device=device)
def __init__(
self,
model: ModelBase,
state_preprocessor: Preprocessor,
seq_len: int,
num_action: int,
state_feature_config: Optional[rlt.ModelFeatureConfig] = None,
):
super().__init__()
self.model = model
self.state_preprocessor = state_preprocessor
self.state_feature_config = state_feature_config or rlt.ModelFeatureConfig(
)
self.sparse_preprocessor = make_sparse_preprocessor(
self.state_feature_config, device=torch.device("cpu"))
self.seq_len = seq_len
self.num_action = num_action
def __init__(
self,
model: ModelBase,
state_preprocessor: Preprocessor,
state_feature_config: rlt.ModelFeatureConfig,
action_postprocessor: Optional[Postprocessor] = None,
serve_mean_policy: bool = False,
):
super().__init__()
self.model = model
self.state_preprocessor = state_preprocessor
self.state_feature_config = state_feature_config
self.sparse_preprocessor = make_sparse_preprocessor(
self.state_feature_config, device=torch.device("cpu")
)
self.action_postprocessor = action_postprocessor
self.serve_mean_policy = serve_mean_policy
