code: def _tpu_multi_host_concat(v, strategy):
      """Correctly order TPU PerReplica objects."""
      replicas = strategy.experimental_local_results(v)
      # When distributed datasets are created from Tensors / NumPy,
      # TPUStrategy.experimental_distribute_dataset shards data in
      # (Replica, Host) order, and TPUStrategy.experimental_local_results returns
      # it in (Host, Replica) order.
      num_replicas_per_host = strategy.extended.num_replicas_per_host
      ordered_replicas = []
      for replica_id in range(num_replicas_per_host):
          ordered_replicas += replicas[
              replica_id::num_replicas_per_host
          ]
      return concat(ordered_replicas)
  
imports: import contextlib
  import warnings
  import numpy
  import tensorflow
  import tree
  from packaging.version import Version
  from tensorflow.python.eager import context
  from keras import callbacks
  from keras import metrics
  from keras import optimizers
  from keras.trainers import trainer
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.trainers.epoch_iterator import EpochIterator
  from keras.utils import traceback_utils
label_desc: Use image node_id 4 for calling a global function with example usage: _tpu_multi_host_concat(v, strategy) and returns: concat