9381164a1f996f4a5533f4834db8dd708a84c6f8,rnns/benchmarks/lstm_variants/lstm.py,LSTM,__init__,#LSTM#Any#Any#Any#Any#Any#,113

Before Change

        self.bias = bias
        self.dropout = dropout
        self.i2h = nn.Linear(input_size, 4 * hidden_size, bias=bias)
        self.h2h = nn.Linear(hidden_size, 4 * hidden_size, bias=bias)
        self.reset_parameters()
        assert(dropout_method.lower() in ["pytorch", "gal", "moon", "semeniuta"])
        self.dropout_method = dropout_method

After Change

        keep = 1.0 - self.dropout
        self.mask = V(th.bernoulli(T(1, self.hidden_size).fill_(keep)))

    def reset_parameters(self):
        std = 1.0 / math.sqrt(self.hidden_size)
        for w in self.parameters():
            w.data.uniform_(-std, std)

    def forward(self, x, hidden):
        do_dropout = self.training and self.dropout > 0.0
        h, c = hidden
        h = h.view(h.size(1), -1)

Instances