code: def sum_pixel_values(batch: BatchWrapper) -> np.array:
      """Sum the values of all the pixels in the batch, returning a numpy array with an entry per channel."""
      images = batch.original_images
      return sum(image.sum(axis=(0, 1)) for image in images)
  
imports: import typing
  import numpy
  from deepchecks.core.check_result import CheckResult
  from deepchecks.core.checks import DatasetKind
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.vision.base_checks import TrainTestCheck
  from deepchecks.vision.context import Context
  from deepchecks.vision.vision_data.batch_wrapper import BatchWrapper
  from deepchecks.vision.datasets.detection.coco_torch import load_dataset
  import pandas
  import plotly.express
  from deepchecks.core import ConditionResult
label_desc: Use image node_id 3 for calling a global function with example usage: sum_pixel_values(batch) and returns: sum