class_docstr: A Dataset comprising lines from one or more CSV files.
  
  The `tf.data.experimental.CsvDataset` class provides a minimal CSV Dataset
  interface. There is also a richer `tf.data.experimental.make_csv_dataset`
  function which provides additional convenience features such as column header
  parsing, column type-inference, automatic shuffling, and file interleaving.
  
  The elements of this dataset correspond to records from the file(s).
  RFC 4180 format is expected for CSV files
  (https://tools.ietf.org/html/rfc4180)
  Note that we allow leading and trailing spaces for int or float fields.
  
  For example, suppose we have a file 'my_file0.csv' with four CSV columns of
  different data types:
  
  >>> with open('/tmp/my_file0.csv', 'w') as f:
  ...   f.write('abcdefg,4.28E10,5.55E6,12\n')
  ...   f.write('hijklmn,-5.3E14,,2\n')
  
  We can construct a CsvDataset from it as follows:
  
  >>> dataset = tf.data.experimental.CsvDataset(
  ...   "/tmp/my_file0.csv",
  ...   [tf.float32,  # Required field, use dtype or empty tensor
  ...    tf.constant([0.0], dtype=tf.float32),  # Optional field, default to 0.0
  ...    tf.int32,  # Required field, use dtype or empty tensor
  ...   ],
  ...   select_cols=[1,2,3]  # Only parse last three columns
  ... )
  
  The expected output of its iterations is:
  
  >>> for element in dataset.as_numpy_iterator():
  ...   print(element)
  (4.28e10, 5.55e6, 12)
  (-5.3e14, 0.0, 2)
  
  See
  https://www.tensorflow.org/tutorials/load_data/csv#tfdataexperimentalcsvdataset
  for more in-depth example usage.
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code: def element_spec(self):
      return self._element_spec
  
imports: import collections
  import csv
  import functools
  import gzip
  import numpy
  from tensorflow.python import tf2
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.data.experimental.ops import error_ops
  from tensorflow.python.data.experimental.ops import parsing_ops
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import map_op
  from tensorflow.python.data.ops import options
  from tensorflow.python.data.ops import readers
  from tensorflow.python.data.util import convert
  from tensorflow.python.data.util import nest
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.ops import io_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the CsvDatasetV2 obj's underlying member method code with example usage: obj.element_spec() and returns: self