model_GRU.py 文件源码

def __init__(self, args):
        super(GRU, self).__init__()
        self.args = args
        # print(args)

        self.hidden_dim = args.lstm_hidden_dim
        self.num_layers = args.lstm_num_layers
        V = args.embed_num
        D = args.embed_dim
        C = args.class_num
        # self.embed = nn.Embedding(V, D, max_norm=args.max_norm)
        self.embed = nn.Embedding(V, D)
        # word embedding
        if args.word_Embedding:
            pretrained_weight = np.array(args.pretrained_weight)
            self.embed.weight.data.copy_(torch.from_numpy(pretrained_weight))
        # gru
        self.gru = nn.GRU(D, self.hidden_dim, dropout=args.dropout, num_layers=self.num_layers)
        # linear
        self.hidden2label = nn.Linear(self.hidden_dim, C)
        # hidden
        self.hidden = self.init_hidden(self.num_layers, args.batch_size)
        # dropout
        self.dropout = nn.Dropout(args.dropout)