code: def infeed_dequeue_tuple(dtypes, shapes, name=None):
      """A placeholder op for values fed into the TPU simultaneously as a tuple.
  
      Args:
        dtypes: A list of `tf.DType`s that has length `>= 1`. The element types of
          each element in `outputs`.
        shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`). The
          shapes of each tensor in `outputs`.
        name: A name for the operation (optional).
  
      Returns:
        A list of `Tensor` objects of type `dtypes`.
        A list of tensors that will be provided using the infeed mechanism.
  
      Raises:
        TypeError: If a type in 'dtypes` is not a supported infeed type.
      """
      for dtype in dtypes:
          if dtype not in _SUPPORTED_INFEED_DTYPES:
              raise TypeError(
                  "{} is not a supported TPU infeed type. Supported types are: "
                  "{}".format(dtype, list(_SUPPORTED_INFEED_DTYPES))
              )
      return gen_tpu_ops.infeed_dequeue_tuple(dtypes, shapes, 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 10 for calling a global function with example usage: infeed_dequeue_tuple(dtypes, shapes, name) and returns: gen_tpu_ops