title: Get order of class labels for Keras predict function
body: <p>I have the same question as <a href="https://stackoverflow.com/questions/38971293/get-class-labels-from-keras-functional-model">this question</a> here in SO. However, when I tried using the <strong>probas_to_classes()</strong> utility function, **it is already missing in the current code:</p>
  
  <pre><code>"""Numpy-related utilities."""
  from __future__ import absolute_import
  
  import numpy as np
  
  
  def to_categorical(y, num_classes=None):
      """Converts a class vector (integers) to binary class matrix.
  
      E.g. for use with categorical_crossentropy.
  
      # Arguments
          y: class vector to be converted into a matrix
              (integers from 0 to num_classes).
          num_classes: total number of classes.
  
      # Returns
          A binary matrix representation of the input.
      """
      y = np.array(y, dtype='int').ravel()
      if not num_classes:
          num_classes = np.max(y) + 1
      n = y.shape[0]
      categorical = np.zeros((n, num_classes))
      categorical[np.arange(n), y] = 1
      return categorical
  
  
  def normalize(x, axis=-1, order=2):
      """Normalizes a Numpy array.
  
      # Arguments
          x: Numpy array to normalize.
          axis: axis along which to normalize.
          order: Normalization order (e.g. 2 for L2 norm).
  
      # Returns
          A normalized copy of the array.
      """
      l2 = np.atleast_1d(np.linalg.norm(x, order, axis))
      l2[l2 == 0] = 1
      return x / np.expand_dims(l2, axis)
  </code></pre>
  
  <p>Do you have any other alternatives in order to get the classes associated with the output of the model?</p>