code: def _sliding_window(X, m):
      """Return the sliding windows for a time series and a window size.
  
      Parameters
      ----------
      X : array-like, shape = [n]
          A single univariate time series of length n
      m : int
          The window size to generate sliding windows
  
      Returns
      -------
      windows : array of shape [n-m+1, m]
          The sliding windows of length over the time series of length n
      """
      shape = X.shape[:-1] + (X.shape[-1] - m + 1, m)
      strides = X.strides + (X.strides[-1],)
      return np.lib.stride_tricks.as_strided(
          X, shape=shape, strides=strides
      )
  
file_path: sktime/sktime/transformations/series/_clasp_numba.py
imports: import numpy
  import pandas
  from sktime.transformations.panel.matrix_profile import _sliding_dot_products
  from sktime.utils.numba.njit import njit
label_desc: Use image node_id 1 for calling a global function with example usage: _sliding_window(X, m) and returns: np