code: def _njit_soft_dtw_batch(D, R, gamma):
      """Compute soft dynamic time warping.
  
      Parameters
      ----------
      D : array-like, shape=(b, m, n), dtype=float64
      R : array-like, shape=(b, m+2, n+2), dtype=float64
      gamma : float64
          Regularization parameter.
      """
      for i_sample in prange(D.shape[0]):
          _njit_soft_dtw(D[i_sample, :, :], R[i_sample, :, :], gamma)
  
file_path: tslearn/tslearn/metrics/soft_dtw_fast.py
imports: import numpy
  from numba import njit, prange
  from tslearn.backend.backend import instantiate_backend
label_desc: Use image node_id 5 for calling a global function with example usage: _njit_soft_dtw_batch(D, R, gamma) without return types