nnet/monotonic_align/__init__.py

# import numpy as np
# import torch
# from .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)