Function cut_n_stack

utils.py:175–188

(seq, snip_length, cut_dim=0, cutting_stride=None, pad_samples=0)

def cut_n_stack(seq, snip_length, cut_dim=0, cutting_stride=None, pad_samples=0):
    if cutting_stride is None:
        cutting_stride = snip_length

    pad_left = pad_samples // 2
    pad_right = pad_samples - pad_samples // 2

    seq = pad_both_ends(seq, pad_left, pad_right, dim=cut_dim)

    stacked = seq.narrow(cut_dim, 0, snip_length).unsqueeze(0)
    iterations = (seq.size()[cut_dim] - snip_length) // cutting_stride + 1
    for i in range(1, iterations):
        stacked = torch.cat((stacked, seq.narrow(cut_dim, i * cutting_stride, snip_length).unsqueeze(0)))
    return stacked


def create_windowed_sequence(seqs, snip_length, cut_dim=0, cutting_stride=None, pad_samples=0):