simple fix
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@ -240,7 +240,7 @@ class sample_data_manager(object):
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# so far filtering for the latest emoji. TODO: maybe there are also better approaches
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labels_i = emoji2sent([latest(e) for e in emojis_i], only_emoticons=only_emoticons )
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else:
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labels_i = np.array([np.mean(emoji2sent(e, only_emoticons=only_emoticons), axis=0) for e in emojis_i])
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labels_i = np.array([np.mean(emoji2sent(e, only_emoticons=only_emoticons), axis=0).tolist() for e in emojis_i])
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# and filter out all samples we have no label for:
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wrong_labels = np.isnan(np.linalg.norm(labels_i, axis=1))
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