TensorflowBasicOperationServlet.java

import org.apache.felix.scr.annotations.sling.SlingServlet;
import org.apache.sling.api.SlingHttpServletRequest;
import org.apache.sling.api.SlingHttpServletResponse;
import org.apache.sling.api.servlets.SlingSafeMethodsServlet;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.tensorflow.*;

import java.io.IOException;
import java.util.Arrays;

/**
 * Created by alse on 12/17/17.
 */

@SlingServlet(paths={"/services/tftest"})
public class TensorflowBasicOperationServlet extends SlingSafeMethodsServlet {
    static private final Logger logger = LoggerFactory.getLogger(TensorflowBasicOperationServlet.class);

    @Override
    protected void doGet(SlingHttpServletRequest request, SlingHttpServletResponse response) throws IOException {
        response.setContentType("text/html");
        response.setCharacterEncoding("utf-8");

        // Create a new graph
        GraphBuilder g = new GraphBuilder(new Graph());

        // Basic constant operations
        Output a = g.constant("a", 1);
        Output b = g.constant("b", 3);

        // add sub mul and div operations
        Output c = g.add(a, b);
        Output d = g.sub(a, b);
        Output e = g.mul(a, b);
        Output f = g.div(a, b);

        // create a new session and run the operations
        Session s =  new Session(g.graph);
        response.getWriter().println(s.runner().fetch(c.op().name()).run().get(0).intValue());
        response.getWriter().println(s.runner().fetch(d.op().name()).run().get(0).intValue());
        response.getWriter().println(s.runner().fetch(e.op().name()).run().get(0).intValue());
        response.getWriter().println(s.runner().fetch(f.op().name()).run().get(0).intValue());

        // matrix multiplication
        float[][] X = new float[][]{new float[]{1,2,3}};
        float[][] Y = new float[][]{new float[]{4}, new float[]{5}, new float[]{6}};

        Output h = g.constant("h", X);
        Output i = g.constant("i", Y);

        Output j = g.matmul(i, h);
        response.getWriter().println(s.runner().fetch(j.op().name()).run().get(0).toString());


        // using placeholder
        Output k = g.placeholder("k", DataType.INT32);
        Output l = g.add(c, k);

        // create a tensor to store the value for k
        Tensor k_value = Tensor.create(10);

        // now feed the value for the placeholder and compute l
        response.getWriter().println(s.runner().feed("k", k_value).fetch(l.op().name()).run().get(0).intValue());
        response.getWriter().println("Testing done!");

        s.close();
    }

}