17    lemmatizer = WordNetLemmatizer()
18    return [lemmatizer.lemmatize(token) for token in tokens]
19
20if __name__ == "__main__":21    pass

26        text_embedding = model.encode_text(self.get_text())
27        return torch.cat((image_embedding, text_embedding), dim=1)
28
29if __name__ == "__main__":30    pass

13def apply_blur(image):
14    return cv2.GaussianBlur(image, (5, 5), 0)
15
16if __name__ == "__main__":17    pass

20                elif isinstance(layer, tf.keras.layers.Conv2D):
21                    self.model.add(tf.keras.layers.Conv2D(layer.filters, layer.kernel_size, input_shape=(layer.input_shape[-3], layer.input_shape[-2], layer.input_shape[-1])))
22
23if __name__ == "__main__":24    pass

46            self.model.n_classes_ = self.model.layers[-1].units
47            self.model.fit(self.model.predict(tf.random.normal((100, self.model.n_features_))), tf.random.uniform((100,), maxval=self.model.n_classes_, dtype=tf.int32))
48
49if __name__ == "__main__":50    pass