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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)
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