4431e04b482238eee5d581eb2c9ca6789ac0ff12,layers/attention.py,AttentionRNNCell,forward,#AttentionRNNCell#Any#Any#Any#Any#Any#Any#Any#,136

Before Change

        // Update the window
        self.win_idx = torch.argmax(alignment,1).long()[0].item()
        // Normalize context weight
        alignment = F.softmax(alignment, dim=-1)
        // alignment = 5 * alignment
        // alignment = torch.sigmoid(alignment) / torch.sigmoid(alignment).sum(dim=1).unsqueeze(1)
        // Attention context vector
        // (batch, 1, dim)

After Change

        // Normalize context weight
        // alignment = F.softmax(alignment, dim=-1)
        // alignment = 5 * alignment
        alignment = torch.sigmoid(alignment) / torch.sigmoid(alignment).sum(dim=1).unsqueeze(1)
        // Attention context vector
        // (batch, 1, dim)
        // c_i = \sum_{j=1}^{T_x} \alpha_{ij} h_j
        context = torch.bmm(alignment.unsqueeze(1), annots)

Instances