code: def infeed_dequeue(dtype, shape, name=None):
      """A placeholder op for a value that will be fed into the computation.
  
      Args:
        dtype: A `tf.DType`. The type of elements in the tensor.
        shape: A `tf.TensorShape` or list of `ints`. The shape of the tensor.
        name: A name for the operation (optional).
  
      Returns:
        A `Tensor` of type `dtype`.
        A tensor that will be provided using the infeed mechanism.
  
      Raises:
        TypeError: If 'dtype` is not a supported infeed type.
      """
      if dtype not in _SUPPORTED_INFEED_DTYPES:
          raise TypeError(
              "Operation '{}' has type {} which is not a supported TPU infeed type. "
              "Supported types are: {}".format(
                  name, dtype, list(_SUPPORTED_INFEED_DTYPES)
              )
          )
  
      return gen_tpu_ops.infeed_dequeue(dtype, shape, 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 9 for calling a global function with example usage: infeed_dequeue(dtype, shape, name) and returns: gen_tpu_ops