code: def maximum_path_cython(value, mask):
      """Cython optimised version.
      value: [b, t_x, t_y]
      mask: [b, t_x, t_y]
      """
      value = value * mask
      device = value.device
      dtype = value.dtype
      value = value.data.cpu().numpy().astype(np.float32)
      path = np.zeros_like(value).astype(np.int32)
      mask = mask.data.cpu().numpy()
  
      t_x_max = mask.sum(1)[:, 0].astype(np.int32)
      t_y_max = mask.sum(2)[:, 0].astype(np.int32)
      maximum_path_c(path, value, t_x_max, t_y_max)
      return torch.from_numpy(path).to(device=device, dtype=dtype)
  
file_path: TTS/TTS/tts/layers/glow_tts/monotonic_align/__init__.py
imports: import numpy
  import torch
  from torch.nn import functional
  from TTS.tts.utils.generic_utils import sequence_mask
label_desc: Use image node_id 4 for calling a global function with example usage: maximum_path_cython(value, mask) and returns: torch