java中的TensorFlow服务-在一个会话中运行多个预测

dependencies {
    implementation 'org.tensorflow:tensorflow:1.15.0'
}

import org.tensorflow.Session;
import org.tensorflow.Tensor;
import org.tensorflow.TensorFlow;

public class TensorFlowService {
    public static void main(String[] args) {
        try (Session session = new Session()) {
            // 在会话中运行预测操作
            // ...
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

import org.tensorflow.Graph;
import org.tensorflow.Session;
import org.tensorflow.Tensor;
import org.tensorflow.TensorFlow;

public class TensorFlowService {
    public static void main(String[] args) {
        try (Session session = new Session()) {
            // 加载预训练的模型
            byte[] modelBytes = // 从文件或其他来源加载模型字节码
            Graph graph = new Graph();
            graph.importGraphDef(modelBytes);

            session.importGraphDef(graph.toGraphDef());

            // 在会话中运行预测操作
            // ...
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

import org.tensorflow.Graph;
import org.tensorflow.Session;
import org.tensorflow.Tensor;
import org.tensorflow.TensorFlow;

public class TensorFlowService {
    public static void main(String[] args) {
        try (Session session = new Session()) {
            // 加载预训练的模型
            byte[] modelBytes = // 从文件或其他来源加载模型字节码
            Graph graph = new Graph();
            graph.importGraphDef(modelBytes);

            session.importGraphDef(graph.toGraphDef());

            // 创建输入Tensor
            Tensor inputTensor = // 构造输入Tensor

            // 运行预测操作
            Tensor outputTensor = session.runner()
                    .feed("input", inputTensor)
                    .fetch("output")
                    .run()
                    .get(0);

            // 处理输出Tensor
            // ...
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}