(self, sess, vocab, batch_size, seq_len, cell_size, num_layers, test=False)
Initializes an LSTM Model.

        @param sess: The TensorFlow Session.
        @param vocab: A list of all the words on which the model will be trained.
        @param batch_size: The batch size for training.
        @param seq_len: The sequence length. (The number of words in each element of the batch.)
        @param cell_size: The size of the hidden layers in the LSTM cells.
                          (also the size of the word embeddings.)
        @param num_layers: The number of LSTM layers in the network.
        @param test: Whether to test or train the model. Default = False.
Initializes an LSTM Model.
Initializes an LSTM Model .
def __init__(self, sess, vocab, batch_size, seq_len, cell_size, num_layers, test=False):
        """
        Initializes an LSTM Model.

        @param sess: The TensorFlow Session.
        @param vocab: A list of all the words on which the model will be trained.
        @param batch_size: The batch size for training.
        @param seq_len: The sequence length. (The number of words in each element of the batch.)
        @param cell_size: The size of the hidden layers in the LSTM cells.
                          (also the size of the word embeddings.)
        @param num_layers: The number of LSTM layers in the network.
        @param test: Whether to test or train the model. Default = False.
        """
        self.sess = sess

        self.vocab = vocab
        self.vocab_size = len(self.vocab)
        self.batch_size = batch_size
        self.seq_len = seq_len
        self.cell_size = cell_size
        self.num_layers = num_layers

        self.build_graph(test)
def __init__ ( self , sess , vocab , batch_size , seq_len , cell_size , num_layers , test = False ) : self . sess = sess self . vocab = vocab self . vocab_size = len ( self . vocab ) self . batch_size = batch_size self . seq_len = seq_len self . cell_size = cell_size self . num_layers = num_layers self . build_graph ( test )