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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 sample_prior(batch_size):
 cat, _ = get_distributions(DIST_PRIOR_PARAM[:NUM_CLASS], DIST_PRIOR_PARAM[NUM_CLASS:]) sample_cat = tf.one_hot(cat.sample(batch_size), NUM_CLASS) """ OpenAI official code actually models the "uniform" latent code as a Gaussian distribution, but obtain the samples from a uniform distribution. """

    sample_uni = tf.random_uniform([batch_size, NUM_UNIFORM], -1, 1)
    samples = tf.concat([sample_cat, sample_uni], axis=1)
    return samples