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