class_docstr: Base class for different Reader types, that produce a record every step.
  
  Conceptually, Readers convert string 'work units' into records (key,
  value pairs).  Typically the 'work units' are filenames and the
  records are extracted from the contents of those files.  We want a
  single record produced per step, but a work unit can correspond to
  many records.
  
  Therefore we introduce some decoupling using a queue.  The queue
  contains the work units and the Reader dequeues from the queue when
  it is asked to produce a record (via Read()) but it has finished the
  last work unit.
  
  @compatibility(eager)
  Readers are not compatible with eager execution. Instead, please
  use `tf.data` to get data into your model.
  @end_compatibility
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docstr: Produce a string tensor that encodes the state of a reader.
  
  Not all Readers support being serialized, so this can produce an
  Unimplemented error.
  
  Args:
    name: A name for the operation (optional).
  
  Returns:
    A string Tensor.
code: def serialize_state(self, name=None):
      """Produce a string tensor that encodes the state of a reader.
  
      Not all Readers support being serialized, so this can produce an
      Unimplemented error.
  
      Args:
        name: A name for the operation (optional).
  
      Returns:
        A string Tensor.
      """
      if self._reader_ref.dtype == dtypes.resource:
          return gen_io_ops.reader_serialize_state_v2(
              self._reader_ref, name=name
          )
      else:
          return gen_io_ops.reader_serialize_state(
              self._reader_ref, name=name
          )
  
imports: from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.lib.io import python_io
  from tensorflow.python.ops import gen_data_flow_ops
  from tensorflow.python.ops import gen_io_ops
  from tensorflow.python.ops import gen_parsing_ops
  from tensorflow.python.ops.gen_io_ops import *
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 7 for calling the ReaderBase obj's underlying member method code with example usage: obj.serialize_state(name) and returns: gen_io_ops, gen_io_ops