code: def __stack(history, data, n_steps, delay):
      """Memory-stacking helper function.
  
      Parameters
      ----------
      history : output array (2-dimensional)
      data : pre-padded input array (2-dimensional)
      n_steps : int > 0, the number of steps to stack
      delay : int != 0, the amount of delay between steps
  
      Returns
      -------
      None
          Output is stored directly in the history array
      """
      # Dimension of each copy of the data
      d = data.shape[-2]
  
      # Total number of time-steps to output
      t = history.shape[-1]
  
      if delay > 0:
          for step in range(n_steps):
              q = n_steps - 1 - step
              # nth block is original shifted left by n*delay steps
              history[..., step * d : (step + 1) * d, :] = data[
                  ..., q * delay : q * delay + t
              ]
      else:
          # Handle the last block separately to avoid -t:0 empty slices
          history[..., -d:, :] = data[..., -t:]
  
          for step in range(n_steps - 1):
              # nth block is original shifted right by n*delay steps
              q = n_steps - 1 - step
              history[..., step * d : (step + 1) * d, :] = data[
                  ..., -t + q * delay : q * delay
              ]
  
file_path: librosa/librosa/feature/utils.py
imports: import numpy
  import scipy.signal
  from numba import jit
  from .._cache import cache
  from ..util.exceptions import ParameterError
  from typing import Any
label_desc: Use image node_id 3 for calling a global function with example usage: __stack(history, data, n_steps, delay) without return types