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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 scheduled_sample_prob(ground_truth_x, generated_x, batch_size, scheduled_sample_var):
 """Probability based scheduled sampling. Args: ground_truth_x: tensor of ground-truth data points. generated_x: tensor of generated data points. batch_size: batch size scheduled_sample_var: probability of choosing from ground_truth. Returns: New batch with randomly selected data points. """

  probability_threshold = scheduled_sample_var
  probability_of_generated = tf.random_uniform([batch_size])
  return tf.where(probability_of_generated > probability_threshold,
                  generated_x, ground_truth_x)