37 lines
810 B
Python
37 lines
810 B
Python
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import matplotlib.pyplot as plt
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import tensorflow as tf
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import numpy as np
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import keras
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from data_load import data_format
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from attack_craft import craft_adv
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# 加载数据集
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X_train, X_test, Y_train, Y_test = data_format(
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'data/archive/PowerQualityDistributionDataset1.csv')
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# 设置随机种子以确保重现性
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np.random.seed(7)
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np.random.shuffle(X_test)
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np.random.seed(7)
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np.random.shuffle(Y_test)
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tf.random.set_seed(7)
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# 加载训练好的模型
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model = keras.models.load_model('model')
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model_adv = keras.models.load_model('model_adv')
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# 定义损失函数
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loss_fn = tf.keras.losses.MeanSquaredError()
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x_adv, loss = craft_adv(
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X_test, Y_test, 0.4, 0.5, model, loss_fn)
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loss_adv = model_adv.evaluate(x_adv, Y_test)
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print(f"原始模型：{loss},对抗训练后的模型：{loss_adv}")
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