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https://github.com/open-mmlab/Amphion
09 September 2024, 06:46:44 UTC
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  • Branches (2)
  • Releases (3)
  • Visits
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    • HEAD
    • refs/heads/main
    • refs/heads/revert-154-FACodec-readme
    • v0.1.1-alpha
    • v0.1.0-alpha
    • v0.1.0
  • 320c54d
  • /
  • modules
  • /
  • monotonic_align
  • /
  • __init__.py
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Tip revision: a4c23e2e1f15e4be0b0c7194e6b69a82a4bb4a07 authored by Xueyao Zhang on 18 December 2023, 14:14:33 UTC
Amphion v0.1 Release (#39)
Tip revision: a4c23e2
__init__.py
# This code from https://github.com/jaywalnut310/vits/

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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