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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def restore_from_checkpoint(self, checkpoint_path):
 """To restore inception model variables from the checkpoint file. Some variables might be missing in the checkpoint file, so it only loads the ones that are avialable, assuming the rest would be initialized later. Args: checkpoint_path: Path to the checkpoint file for the Inception graph. """

    import tensorflow as tf
    # Get all variables to restore. Exclude Logits and AuxLogits because they
    # depend on the input data and we do not need to intialize them from
    # checkpoint.
    all_vars = tf.contrib.slim.get_variables_to_restore(
        exclude=['InceptionV3/AuxLogits', 'InceptionV3/Logits', 'global_step'])

    saver = tf.train.Saver(all_vars)
    saver.restore(self.tf_session, checkpoint_path)