code: def tohost(x):
      """Collect batches from all devices to host and flatten batch dimensions."""
      n_device, n_batch, *remaining_dims = x.shape
      return np.array(x).reshape(
          (n_device * n_batch,) + tuple(remaining_dims)
      )
  
imports: import collections
  import dataclasses
  import os
  import input_pipeline
  import jax
  import jax.numpy
  import models
  import numpy
  import optax
  import temperature_sampler
  import tensorflow
  import utils
  from absl import logging
  from clu import metric_writers, periodic_actions
  from configs import default
  from jax import random
  from jax.sharding import Mesh, NamedSharding
  from jax.sharding import PartitionSpec
  from utils import HasCache, TrainState
  from flax import linen
  from flax.experimental import nnx
  from flax.training import checkpoints, common_utils
label_desc: Use image node_id 11 for calling a global function with example usage: tohost(x) and returns: np