code: def replace_ImageToTensor(pipelines):
      """Replace the ImageToTensor transform in a data pipeline to
      DefaultFormatBundle, which is normally useful in batch inference.
  
      Args:
          pipelines (list[dict]): Data pipeline configs.
  
      Returns:
          list: The new pipeline list with all ImageToTensor replaced by
              DefaultFormatBundle.
  
      Examples:
          >>> pipelines = [
          ...    dict(type='LoadImageFromFile'),
          ...    dict(
          ...        type='MultiScaleFlipAug',
          ...        img_scale=(1333, 800),
          ...        flip=False,
          ...        transforms=[
          ...            dict(type='Resize', keep_ratio=True),
          ...            dict(type='RandomFlip'),
          ...            dict(type='Normalize', mean=[0, 0, 0], std=[1, 1, 1]),
          ...            dict(type='Pad', size_divisor=32),
          ...            dict(type='ImageToTensor', keys=['img']),
          ...            dict(type='Collect', keys=['img']),
          ...        ])
          ...    ]
          >>> expected_pipelines = [
          ...    dict(type='LoadImageFromFile'),
          ...    dict(
          ...        type='MultiScaleFlipAug',
          ...        img_scale=(1333, 800),
          ...        flip=False,
          ...        transforms=[
          ...            dict(type='Resize', keep_ratio=True),
          ...            dict(type='RandomFlip'),
          ...            dict(type='Normalize', mean=[0, 0, 0], std=[1, 1, 1]),
          ...            dict(type='Pad', size_divisor=32),
          ...            dict(type='DefaultFormatBundle'),
          ...            dict(type='Collect', keys=['img']),
          ...        ])
          ...    ]
          >>> assert expected_pipelines == replace_ImageToTensor(pipelines)
      """
      pipelines = copy.deepcopy(pipelines)
      for i, pipeline in enumerate(pipelines):
          if pipeline["type"] == "MultiScaleFlipAug":
              assert "transforms" in pipeline
              pipeline["transforms"] = replace_ImageToTensor(
                  pipeline["transforms"]
              )
          elif pipeline["type"] == "ImageToTensor":
              warnings.warn(
                  '"ImageToTensor" pipeline is replaced by '
                  '"DefaultFormatBundle" for batch inference. It is '
                  "recommended to manually replace it in the test "
                  "data pipeline in your config file.",
                  UserWarning,
              )
              pipelines[i] = {"type": "DefaultFormatBundle"}
      return pipelines
  
label_desc: Use image node_id 1 for calling a global function with example usage: replace_ImageToTensor(pipelines) and returns: pipelines