code: def report_debug_images(logger, iteration=0):
      # type: (Logger, int) -> ()
      """
      reporting images to debug samples section
      :param logger: The task.logger to use for sending the plots
      :param iteration: The iteration number of the current reports
      """
  
      # report image as float image
      m = np.eye(256, 256, dtype=float)
      logger.report_image(
          "image", "image float", iteration=iteration, image=m
      )
  
      # report image as uint8
      m = np.eye(256, 256, dtype=np.uint8) * 255
      logger.report_image(
          "image", "image uint8", iteration=iteration, image=m
      )
  
      # report image as uint8 RGB
      m = np.concatenate(
          (np.atleast_3d(m), np.zeros((256, 256, 2), dtype=np.uint8)),
          axis=2,
      )
      logger.report_image(
          "image", "image color red", iteration=iteration, image=m
      )
  
      # report PIL Image object
      image_open = Image.open(
          os.path.join(
              os.path.dirname(os.path.abspath(__file__)),
              "data_samples",
              "picasso.jpg",
          )
      )
      logger.report_image(
          "image", "image PIL", iteration=iteration, image=image_open
      )
  
      # Image can be uploaded via 'report_media' too.
      logger.report_media(
          "image",
          "image with report media",
          iteration=iteration,
          local_path=os.path.join(
              os.path.dirname(os.path.abspath(__file__)),
              "data_samples",
              "picasso.jpg",
          ),
          file_extension="jpg",
      )
  
imports: import os
  import numpy
  from PIL import Image
  from clearml import Task, Logger
label_desc: Use image node_id 1 for calling a global function with example usage: report_debug_images(logger, iteration) without return types