monotonic_align/__init__.py

import numpy as np
import torch
from .monotonic_align.core import maximum_path_c


def maximum_path(neg_cent, mask):
  """ Cython optimized version.
  neg_cent: [b, t_t, t_s]
  mask: [b, t_t, t_s]
  """
  device = neg_cent.device
  dtype = neg_cent.dtype
  neg_cent = neg_cent.data.cpu().numpy().astype(np.float32)
  path = np.zeros(neg_cent.shape, dtype=np.int32)

  t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(np.int32)
  t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(np.int32)
  maximum_path_c(path, neg_cent, t_t_max, t_s_max)
  return torch.from_numpy(path).to(device=device, dtype=dtype)