3dcb5c77165c1a0c33a35a7831182f1aa2e8ad73,fairseq/models/model_utils.py,,fill_tensors,#Any#Any#Any#Any#,34

Before Change

        return y

    if x.size(1) < y.size(1):
        dims = [x.size(0), y.size(1) - x.size(1)]
        if x.dim() == 3:
            dims.append(x.size(2))
        x = torch.cat([x, x.new_zeros(*dims).fill_(padding_idx)], 1)
        x[mask] = y
    elif x.size(1) > y.size(1):
        x[mask] = padding_idx
        if x.dim() == 2:

After Change

    n_selected = mask.sum()
    if n_selected == 0:
        return x
    assert n_selected == y.size(0)
    if n_selected == x.size(0):
        return y

Instances