(
        self, input_size: int, hidden_size: int, using_sequence: bool = True
    )
Instantiating LSTMEncoder 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 LSTMEncoder 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 LSTMEncoder 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
def __init__(
        self, input_size: int, hidden_size: int, using_sequence: bool = True
    ) -> None:
        """Instantiating LSTMEncoder 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(LSTMEncoder, self).__init__()
        self._using_sequence = using_sequence
        self._ops = nn.LSTM(input_size, hidden_size, batch_first=True)
def __init__ ( self , input_size : int , hidden_size : int , using_sequence : bool = True ) -> None : super ( LSTMEncoder , self ) . __init__ ( ) self . _using_sequence = using_sequence self . _ops = nn . LSTM ( input_size , hidden_size , batch_first = True )