dialogue_personalization/model/common_layer.py [593:604]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
def sequence_mask(sequence_length, max_len=None):
    if max_len is None:
        max_len = sequence_length.data.max()
    batch_size = sequence_length.size(0)
    seq_range = torch.arange(0, max_len).long()
    seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len)
    seq_range_expand = seq_range_expand
    if sequence_length.is_cuda:
        seq_range_expand = seq_range_expand.cuda()
    seq_length_expand = (sequence_length.unsqueeze(1)
                        .expand_as(seq_range_expand))
    return seq_range_expand < seq_length_expand
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



dialogue_personalization/utils/beam_ptr.py [192:203]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
def sequence_mask(sequence_length, max_len=None):
    if max_len is None:
        max_len = sequence_length.data.max()
    batch_size = sequence_length.size(0)
    seq_range = torch.arange(0, max_len).long()
    seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len)
    seq_range_expand = seq_range_expand
    if sequence_length.is_cuda:
        seq_range_expand = seq_range_expand.cuda()
    seq_length_expand = (sequence_length.unsqueeze(1)
                        .expand_as(seq_range_expand))
    return seq_range_expand < seq_length_expand
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -