code: def _njit_local_squared_dist(x, y):
      """Compute the squared distance between two vectors.
  
      Parameters
      ----------
      x : array-like, shape=(d,)
          A vector.
      y : array-like, shape=(d,)
          Another vector.
  
      Returns
      -------
      dist : float
          Squared distance between x and y.
      """
      dist = 0.0
      for di in range(x.shape[0]):
          diff = x[di] - y[di]
          dist += diff * diff
      return dist
  
imports: import warnings
  import numpy
  from numba import njit, prange
  from tslearn.backend import instantiate_backend
  from tslearn.utils import to_time_series
  from .utils import _cdist_generic
label_desc: Use image node_id 1 for calling a global function with example usage: _njit_local_squared_dist(x, y) and returns: dist