78c3480e3b86b971cc834f1d3cec162408ba1ba0,torchaudio/functional/functional.py,,griffinlim,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,128

Before Change

        angles = 2 * math.pi * torch.rand(batch, freq, frames)
    else:
        angles = torch.zeros(batch, freq, frames)
    angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \
        .to(dtype=specgram.dtype, device=specgram.device)
    specgram = specgram.unsqueeze(-1).expand_as(angles)

    // And initialize the previous iterate to 0
    rebuilt = torch.tensor(0.)

After Change

            specgram.size(),
            dtype=_get_complex_dtype(specgram.dtype), device=specgram.device)
    else:
        angles = torch.full(
            specgram.size(), 1,
            dtype=_get_complex_dtype(specgram.dtype), device=specgram.device)

    // And initialize the previous iterate to 0
    tprev = torch.tensor(0., dtype=specgram.dtype, device=specgram.device)
    for _ in range(n_iter):

Instances