class_docstr: A `Dataset` of fixed-length records from one or more binary files.
class_docstr_tok: ["A","`","Dataset","`","of","fixed-length","records","from","one","or","more","binary","files","."]
code: def __init__(
      self,
      filenames,
      record_bytes,
      header_bytes=None,
      footer_bytes=None,
      buffer_size=None,
      compression_type=None,
      num_parallel_reads=None,
      name=None,
  ):
      wrapped = FixedLengthRecordDatasetV2(
          filenames,
          record_bytes,
          header_bytes,
          footer_bytes,
          buffer_size,
          compression_type,
          num_parallel_reads,
          name=name,
      )
      super(FixedLengthRecordDatasetV1, 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 FixedLengthRecordDatasetV1 object from inherited base classes: dataset_ops with example: obj = FixedLengthRecordDatasetV1(filenames, record_bytes, header_bytes, footer_bytes, buffer_size, compression_type, num_parallel_reads, name)