classifier.py 文件源码

def evaluate(self, x_test, y_test, batch_size=256):
        """Evaluate classifier

        Args:
            x_test (np.array): 3D numpy array (n_samples, embedding_dim, tokenizer.max_sequence_length)
            y_test (np.array): 2D numpy array (n_samples, len(self.category_map))
            batch_size (int): Training batch size
        """
        print('Evaluating...')
        predictions_last_epoch = self.model.predict(x_test, batch_size=batch_size, verbose=1)
        predicted_classes = np.argmax(predictions_last_epoch, axis=1)
        target_names = ['']*len(self.category_map)
        for category in self.category_map:
            target_names[self.category_map[category]] = category
        y_val = np.argmax(y_test, axis=1)
        print(classification_report(y_val, predicted_classes, target_names=target_names, digits = 6))