code: def levels_to_images(mlvl_tensor):
      batch_size = mlvl_tensor[0].shape[0]
      batch_list = [[] for _ in range(batch_size)]
      channels = mlvl_tensor[0].shape[1]
      for t in mlvl_tensor:
          t = t.transpose([0, 2, 3, 1])
          t = t.reshape([batch_size, -1, channels])
          for img in range(batch_size):
              batch_list[img].append(t[img])
      return [paddle.concat(item, axis=0) for item in batch_list]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ppdet.modeling import ops
  from functools import partial
label_desc: Use image node_id 2 for calling a global function with example usage: levels_to_images(mlvl_tensor) and returns: unknown