code: def _maybe_padding(x, seq_len, zeros=None):
      """padding 2d <time * feature> data with zeros
  
      Args:
          x (np.ndarray): 2d data with shape <time * feature>
          seq_len (int): target sequence length
          zeros (np.ndarray): zeros with shape <seq_len * feature>
      """
      assert seq_len > 0, "sequence length should be larger than 0"
      if zeros is None:
          zeros = np.zeros((seq_len, x.shape[1]), dtype=np.float32)
      else:
          assert (
              len(zeros) >= seq_len
          ), "zeros matrix is not large enough for padding"
      if len(x) != seq_len:  # padding zeros
          x = np.concatenate(
              [zeros[: seq_len - len(x), : x.shape[1]], x], axis=0
          )
      return x
  
imports: import copy
  import torch
  import warnings
  import numpy
  import pandas
  from qlib.data.dataset import DatasetH
label_desc: Use image node_id 4 for calling a global function with example usage: _maybe_padding(x, seq_len, zeros) and returns: x