code: def create_feeds(image_shape):
      """
      Create feeds mapping for the inputs of Pragrm execution.
  
      Args:
          image_shape(list[int]): Model input shape, such as [4, 224, 224].
      Returns:
          feeds(dict): A dict to map variables'name to their values.
                       key (string): Name of variable to feed.
                       Value (tuple): paddle.static.data.
      """
      feeds = dict()
      feeds["data"] = paddle.static.data(
          name="data", shape=[None] + image_shape, dtype="float32"
      )
      feeds["label"] = paddle.static.data(
          name="label", shape=[None, 1], dtype="int64"
      )
  
      return feeds
  
imports: import time
  import logging
  from profile import Profiler
  import numpy
  from optimizer import build_optimizer
  from lr_scheduler import build_lr_scheduler
  from utils.misc import AverageMeter
  from utils.mode import Mode, RunScope
  from utils.utility import get_num_trainers
  import models
  import dllogger
  import paddle
  import paddle.nn.functional
  from paddle.distributed import fleet
  from paddle.distributed.fleet import DistributedStrategy
  from paddle.incubate import asp
  from paddle.distributed.fleet.meta_optimizers.common import CollectiveHelper
label_desc: Use image node_id 1 for calling a global function with example usage: create_feeds(image_shape) and returns: feeds