code: def repeat(
      n: int,
      body: Callable[
          ..., Union[core_types.TensorLike, Iterable]
      ],  # pylint:disable=g-bare-generic
      inputs: Optional[List[core_types.TensorLike]] = None,
      infeed_queue: Optional[tpu_feed.InfeedQueue] = None,
      name: Any = None,
  ) -> List[core_types.TensorLike]:
      """Builds a training loop that executes a fixed number of iterations.
  
      The set of loop-carried tensors correspond to `inputs`.
      `body` must be a function that takes and returns the values of the
      loop-carried tensors.
  
      Args:
        n: the number of loop iterations
        body: a Python function that builds the loop body.
        inputs: a list of initial values passed into the training loop or None
          (equivalent to an empty list).
        infeed_queue: if not None, the infeed queue from which to append a tuple of
          arguments as inputs to condition.
        name: (Deprecated) Does nothing.
  
      Returns:
        The final values of the loop-carried tensors.
      Raises:
        ValueError: if there is a type error.
      """
  
      def _convert_to_list(xs):
          if not isinstance(xs, (list, tuple)):
              return [xs]
          else:
              return list(xs)
  
      def cond(i, *args):
          del args
          return i < n
  
      def body_wrapper(i, *args):
          return [i + 1] + _convert_to_list(body(*args))
  
      inputs = [0] if inputs is None else [0] + _convert_to_list(inputs)
      outputs = while_loop(
          cond,
          body_wrapper,
          inputs=inputs,
          infeed_queue=infeed_queue,
          name=name,
      )
      outputs = _convert_to_list(outputs)
      if len(outputs) == 1:
          # Returns the Op rather than an empty list.
          return outputs[0].op
      else:
          return outputs[1:]
  
file_path: tensorflow-upstream/tensorflow/python/tpu/training_loop.py
imports: from typing import Any, Callable, Iterable, List, Optional, Union
  from tensorflow.python.compiler.xla import xla
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.tpu import tensor_tracer
  from tensorflow.python.tpu import tpu_feed
  from tensorflow.python.tpu import tpu_function
  from tensorflow.python.types import core
label_desc: Use image node_id 2 for calling a global function with example usage: repeat(n, body, inputs, infeed_queue, name) and returns: unknown, unknown, outputs, outputs, list, list