code: def enqueue_tpu_embedding_integer_batch(
      batch, device_ordinal, mode_override=None, name=None
  ):
      """A placeholder op for enqueueing embedding IDs to the TPU.
  
      Args:
        batch: A list of 1D tensors, one for each embedding table, containing the
          indices into the tables.
        device_ordinal: The TPU device to use. Should be >= 0 and less than the
          number of TPU cores in the task on which the node is placed.
        mode_override: A string input that overrides the mode specified in the
          TPUEmbeddingConfiguration. Supported values are {'unspecified',
          'inference', 'train', 'backward_pass_only'}. When set to 'unspecified',
          the mode set in TPUEmbeddingConfiguration is used, otherwise mode_override
          is used (optional).
        name: A name for the operation (optional).
  
      Returns:
        An EnqueueTPUEmbeddingIntegerBatch operation.
      """
      if mode_override is None:
          mode_override = "unspecified"
      return gen_tpu_ops.enqueue_tpu_embedding_integer_batch(
          batch=batch,
          device_ordinal=device_ordinal,
          mode_override=mode_override,
          name=name,
      )
  
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_tpu_ops
  from tensorflow.python.ops.gen_tpu_ops import *
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.tpu import tpu_function
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 12 for calling a global function with example usage: enqueue_tpu_embedding_integer_batch(batch, device_ordinal, mode_override, name) and returns: gen_tpu_ops