"""Computes the inception score of the generated images imgs Quantile = np.searchsorted(quantiles, kl_div) / len(quantiles)Ġ View Complete Implementation : inception_score.py, under MIT License, by akanazawa def inception_score(imgs, device=None, batch_size=32, resize=False, splits=1): Quantiles = (kl_div_dist, prob=np.linspace(0, 1, 500, endpoint=False))įor p, q in zip(doc_topic_test_true, doc_topic_test): Kl_div_dist = (doc_topic_test_true,ĭoc_topic) # (p, q) calculates Kullback-Leibler divergence Picking at random from a fitted model and calculating the KL divergence.ĭoc_topic_test = ansform(dtm_test) In this case, our null hypothesis is that we are doing no better than """Evaluate transform by checking predicted doc_topic distribution 2 View Complete Implementation : test_lda_transform.py, under Mozilla Public License 2.0, by vi3k6i5 def test_lda_transform_null(self):
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