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@@ -26,12 +26,10 @@ def save_wmark_signatures(model):
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np.save(fname_b, wmark_regularizer.get_signature())
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-# 从文件中获取
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-def get_layer_weights_and_predicted(model, checkpoint_save_path, target_blk_id):
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+# 获取指定层权重和密钥预测值
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+def get_layer_weights_and_predicted(target_layer):
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x = np.load(fname_x)
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- model.load_weights(checkpoint_save_path)
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- # get signature from model weight and matrix
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- target_layer = model.get_layer(index=target_blk_id)
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+ # get signature from model layer and matrix
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layer_weights = target_layer.get_weights()
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weight = (np.array(layer_weights[0])).mean(axis=3)
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pred_bparam = np.dot(weight.reshape(1, weight.size), x) # dot product
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