code: def batch_to_numpy(batch: Dict[str, tf.Tensor]) -> Dict[str, Array]:
      """Converts a batch with TF tensors to a batch of NumPy arrays."""
      # _numpy() reuses memory, does not make a copy.
      # pylint: disable=protected-access
      return jax.tree_util.tree_map(lambda x: x._numpy(), batch)
  
imports: from typing import Any, Callable, Dict, Iterable, Optional, Sequence, Tuple, Union
  from absl import logging
  from flax import struct
  from flax.metrics import tensorboard
  from flax.training import train_state
  import jax
  import jax.numpy
  import ml_collections
  import numpy
  import optax
  import tensorflow
  import input_pipeline
  import models
label_desc: Use image node_id 9 for calling a global function with example usage: batch_to_numpy(batch) and returns: jax