(self, input_size: int, hidden_size: int, using_sequence: bool = True)
Instantiating BiLSTM class""

        Args:
            input_size (int): the number of expected features in the input x
            hidden_size (int): the number of features in the hidden state h
            using_sequence (bool): using all hidden states of sequence. Default: True
Instantiating BiLSTM class""
Instantiating BiLSTM class
def __init__(self, input_size: int, hidden_size: int, using_sequence: bool = True) -> None:
        """Instantiating BiLSTM class""

        Args:
            input_size (int): the number of expected features in the input x
            hidden_size (int): the number of features in the hidden state h
            using_sequence (bool): using all hidden states of sequence. Default: True
        """
        super(BiLSTM, self).__init__()
        self._using_sequence = using_sequence
        self._ops = nn.LSTM(input_size, hidden_size, batch_first=True, bidirectional=True)
def __init__ ( self , input_size : int , hidden_size : int , using_sequence : bool = True ) -> None : super ( BiLSTM , self ) . __init__ ( ) self . _using_sequence = using_sequence self . _ops = nn . LSTM ( input_size , hidden_size , batch_first = True , bidirectional = True )