seq2seq_models.py 文件源码

def __init__(self, output_dim, hidden_dim, output_length, depth=1, dropout=0.25, **kwargs):
        super(SimpleSeq2seq, self).__init__()
        if type(depth) not in [list, tuple]:
            depth = (depth, depth)
        self.encoder = LSTM(hidden_dim, **kwargs)
        self.decoder = LSTM(hidden_dim, return_sequences=True, **kwargs)
        for i in range(1, depth[0]):
            self.add(LSTM(hidden_dim, return_sequences=True, **kwargs))
            self.add(Dropout(dropout))
        self.add(self.encoder)
        self.add(Dropout(dropout))
        self.add(RepeatVector(output_length))
        self.add(self.decoder)
        for i in range(1, depth[1]):
            self.add(LSTM(hidden_dim, return_sequences=True, **kwargs))
            self.add(Dropout(dropout))
        #if depth[1] > 1:
        self.add(TimeDistributedDense(output_dim, activation='softmax'))