docstr: Evaluate the model on test dataset.
  
  The evaluate method will evaluate the model on a test
  dataset.
  
  Parameters
  ----------
  x_test : ndarray
      the x_test is the test dataset
  y_test : ndarray shape=(BatchSize,)
      the y_test is the labels of the test dataset
  verbose : int (Default = 2)
      By setting verbose 0, 1 or 2 you just say how do you want to
      'see' the training progress for each epoch.
  
  Returns
  -------
  evaluate : List
      return list of loss value and accuracy value on test dataset
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code: def evaluate(self, x_test, y_test, verbose=2):
      """Evaluate the model on test dataset.
  
      The evaluate method will evaluate the model on a test
      dataset.
  
      Parameters
      ----------
      x_test : ndarray
          the x_test is the test dataset
      y_test : ndarray shape=(BatchSize,)
          the y_test is the labels of the test dataset
      verbose : int (Default = 2)
          By setting verbose 0, 1 or 2 you just say how do you want to
          'see' the training progress for each epoch.
  
      Returns
      -------
      evaluate : List
          return list of loss value and accuracy value on test dataset
  
      """
      return self.model.evaluate(x_test, y_test, verbose=verbose)
  
file_path: dipy/dipy/nn/model.py
imports: from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 4 for calling the SingleLayerPerceptron obj's underlying member method code with example usage: obj.evaluate(x_test, y_test, verbose) and returns: self