class_docstr: A simple class for handling the ImageNet data set.
class_docstr_tok: ["A","simple","class","for","handling","the","ImageNet","data","set","."]
docstr: Returns a python list of all (sharded) data subset files.
  
  Returns:
    python list of all (sharded) data set files.
  
  Raises:
    ValueError: if there are not data_files matching the subset.
docstr_tok: ["Returns","a","python","list","of","all","(","sharded",")","data","subset","files",".","Returns",":","python","list","of","all","(","sharded",")","data","set","files",".","Raises",":","ValueError",":","if","there","are","not","data_files","matching","the","subset","."]
code: def data_files(self):
      """Returns a python list of all (sharded) data subset files.
  
      Returns:
        python list of all (sharded) data set files.
  
      Raises:
        ValueError: if there are not data_files matching the subset.
      """
      imagenet_data_dir = os.path.expanduser(FLAGS.imagenet_data_dir)
      if not tf.gfile.Exists(imagenet_data_dir):
          print("%s does not exist!" % (imagenet_data_dir))
          sys.exit(-1)
  
      tf_record_pattern = os.path.join(
          imagenet_data_dir, "%s-*" % self.subset
      )
      data_files = tf.gfile.Glob(tf_record_pattern)
      if not data_files:
          print(
              "No files found for dataset ImageNet/%s at %s"
              % (self.subset, imagenet_data_dir)
          )
  
          self.download_message()
          sys.exit(-1)
  
      return data_files
  
file_path: magenta/magenta/models/image_stylization/imagenet_data.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the ImagenetData obj's underlying member method code with example usage: obj.data_files() and returns: data_files