class_docstr: A Reader that outputs the queued work as both the key and value.
  
  To use, enqueue strings in a Queue.  Read will take the front
  work string and output (work, work).
  
  See ReaderBase for supported methods.
  
  @compatibility(eager)
  Readers are not compatible with eager execution. Instead, please
  use `tf.data` to get data into your model.
  @end_compatibility
class_docstr_tok: ["A","Reader","that","outputs","the","queued","work","as","both","the","key","and","value",".","To","use",",","enqueue","strings","in","a","Queue",".","Read","will","take","the","front","work","string","and","output","(","work",",","work",")",".","See","ReaderBase","for","supported","methods",".","@","compatibility","(","eager",")","Readers","are","not","compatible","with","eager","execution",".","Instead",",","please","use","`","tf.data","`","to","get","data","into","your","model",".","@","end_compatibility"]
docstr: Create a IdentityReader.
  
  Args:
    name: A name for the operation (optional).
code: def __init__(self, name=None):
      """Create a IdentityReader.
  
      Args:
        name: A name for the operation (optional).
      """
      rr = gen_io_ops.identity_reader_v2(name=name)
      super(IdentityReader, self).__init__(rr, supports_serialize=True)
  
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 1 to create a new IdentityReader object from inherited base classes: ReaderBase with example: obj = IdentityReader(name)