code: def extract_labels(filename, one_hot=False):
      """Extract the labels into a 1D uint8 numpy array [index]."""
      print("Extracting", filename)
      with gzip.open(filename) as bytestream:
          magic = _read32(bytestream)
          if magic != 2049:
              raise ValueError(
                  "Invalid magic number %d in MNIST label file: %s"
                  % (magic, filename)
              )
          num_items = _read32(bytestream)
          buf = bytestream.read(num_items)
          labels = numpy.frombuffer(buf, dtype=numpy.uint8)
          if one_hot:
              return dense_to_one_hot(labels)
          return labels
  
file_path: tflearn/tflearn/datasets/mnist.py
imports: from __future__ import print_function
  import gzip
  import os
  from six.moves import urllib
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: extract_labels(filename, one_hot) and returns: labels, dense_to_one_hot