def _download_dataset(dataset_dir):
 for filename in [_TRAIN_DATA_FILENAME, _TRAIN_LABELS_FILENAME, _TEST_DATA_FILENAME, _TEST_LABELS_FILENAME]:
  filepath = os.path.join(dataset_dir, filename)
  if (not os.path.exists(filepath)):
   print(('Downloading file %s...' % filename))
   def _progress(count, block_size, total_size):
    sys.stdout.write(('\r>> Downloading %.1f%%' % ((float((count * block_size)) / float(total_size)) * 100.0)))
    sys.stdout.flush()
   (filepath, _) = urllib.request.urlretrieve((_DATA_URL + filename), filepath, _progress)
   print()
   with tf.gfile.GFile(filepath) as f:
    size = f.Size()
   print('Successfully downloaded', filename, size, 'bytes.')

def _download_dataset ( dataset_dir ) : for filename in [ _TRAIN_DATA_FILENAME , _TRAIN_LABELS_FILENAME , _TEST_DATA_FILENAME , _TEST_LABELS_FILENAME ] : filepath = os . path . join ( dataset_dir , filename ) if ( not os . path . exists ( filepath ) ) : print ( ( 'Downloading file %s...' % filename ) ) def _progress ( count , block_size , total_size ) : sys . stdout . write ( ( '\r>> Downloading %.1f%%' % ( ( float ( ( count * block_size ) ) / float ( total_size ) ) * 100.0 ) ) ) sys . stdout . flush ( ) ( filepath , _ ) = urllib . request . urlretrieve ( ( _DATA_URL + filename ) , filepath , _progress ) print ( ) with tf . gfile . GFile ( filepath ) as f : size = f . Size ( ) print ( 'Successfully downloaded' , filename , size , 'bytes.' )
downloads mnist locally .