rnn.py 文件源码

def __init__(self, mode, input_size, hidden_size, num_layers=1, batch_first=False, dropout=0, train=True, bidirectional=False):
        super(CudnnRNN, self).__init__()
        self.mode = cudnn.rnn.get_cudnn_mode(mode)
        self.input_mode = cudnn.CUDNN_LINEAR_INPUT
        self.input_size = input_size
        self.hidden_size = hidden_size
        self.num_layers = num_layers
        self.batch_first = batch_first
        self.dropout = dropout
        self.train = train
        self.bidirectional = 1 if bidirectional else 0
        self.num_directions = 2 if bidirectional else 1
        self.seed = torch.IntTensor(1).random_()[0]