class_docstr: A `Dataset` comprising lines from one or more text files.
class_docstr_tok: ["A","`","Dataset","`","comprising","lines","from","one","or","more","text","files","."]
code: def __init__(
      self,
      filenames,
      compression_type=None,
      buffer_size=None,
      num_parallel_reads=None,
      name=None,
  ):
      wrapped = TextLineDatasetV2(
          filenames,
          compression_type,
          buffer_size,
          num_parallel_reads,
          name,
      )
      super(TextLineDatasetV1, self).__init__(wrapped)
  
imports: import os
  from tensorflow.python import tf2
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import from_tensor_slices_op
  from tensorflow.python.data.ops import structured_function
  from tensorflow.python.data.util import convert
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import type_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_dataset_ops
  from tensorflow.python.ops import gen_experimental_dataset_ops
  from tensorflow.python.types import data
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 to create a new TextLineDatasetV1 object from inherited base classes: dataset_ops with example: obj = TextLineDatasetV1(filenames, compression_type, buffer_size, num_parallel_reads, name)