class_docstr: A simple class for handling the ImageNet data set.
class_docstr_tok: ["A","simple","class","for","handling","the","ImageNet","data","set","."]
docstr: Instruction to download and extract the tarball from Flowers website.
docstr_tok: ["Instruction","to","download","and","extract","the","tarball","from","Flowers","website","."]
code: def download_message(self):
      """Instruction to download and extract the tarball from Flowers website."""
  
      print("Failed to find any ImageNet %s files" % self.subset)
      print("")
      print(
          "If you have already downloaded and processed the data, then make "
          "sure to set --imagenet_data_dir to point to the directory "
          "containing the location of the sharded TFRecords.\n"
      )
      print(
          "If you have not downloaded and prepared the ImageNet data in the "
          "TFRecord format, you will need to do this at least once. This "
          "process could take several hours depending on the speed of your "
          "computer and network connection\n"
      )
      print(
          "Please see "
          "https://github.com/tensorflow/models/blob/master/research/slim/"
          "datasets/download_and_convert_imagenet.sh "
          "for a tool to build the ImageNet dataset.\n"
      )
      print(
          "Note that the raw data size is 300 GB and the processed data size "
          "is 150 GB. Please ensure you have at least 500GB disk space."
      )
  
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 4 for calling the ImagenetData obj's underlying member method code with example usage: obj.download_message() without return types