Ejemplo n.º 1
0
        static void Main(string[] args)
        {
            NumericsTest test = new NumericsTest();

            test.Test();

            var log4_net_config = Path.Combine(Path.GetDirectoryName(typeof(Program).Assembly.Location), "log4net.config");

            XmlConfigurator.Configure(new FileInfo(log4_net_config));


            int   batch_size    = 32;
            uint  w             = 60;
            uint  h             = 20;
            float learning_rate = 1e-4f;
            float weight_decay  = 1e-4f;

            ReadData rdtrain = new ReadData("data\\train\\", batch_size);
            ReadData rdval   = new ReadData("data\\val\\", batch_size);


            //var first = rdtrain.First();
            Context ctx = new Context(DeviceType.KGpu, 0);

            //NDArray dataArray = new NDArray(new Shape((uint)batchSize, 3, W, H), ctx, false);
            //NDArray labelArray = new NDArray(new Shape((uint)batchSize,4), ctx, false);


            //Symbol data1 = Symbol.Variable("data1");
            //Symbol data2 = Symbol.Variable("data2");
            var         pnet  = get_ocrnet(batch_size);
            Speedometer speed = new Speedometer(batch_size, 50);

            CustomMetric custom_metric = new CustomMetric((l, p) => Accuracy(l, p, batch_size));

            Optimizer optimizer = new CcSgd(momentum: 0.9f, learning_rate: 0.001f, wd: 0.00001f, rescale_grad: 1.0f / batch_size);


            FeedForward model = new FeedForward(pnet, new List <Context> {
                ctx
            },
                                                num_epoch: 10,
                                                optimizer: optimizer,
                                                initializer: new Xavier(factor_type: FactorType.In, magnitude: 2.34f)

                                                );


            model.Fit(rdtrain, rdval,
                      custom_metric,
                      batch_end_callback: new List <Action <mxnet.csharp.util.BatchEndParam> > {
                speed.Call
            });
            Console.WriteLine("");
        }
Ejemplo n.º 2
0
        static void Main(string[] args)
        {
            NumericsTest test = new NumericsTest();

            test.Test();

            var log4_net_config = Path.Combine(Path.GetDirectoryName(typeof(Program).Assembly.Location), "log4net.config");

            XmlConfigurator.Configure(new FileInfo(log4_net_config));


            var model = FeedForward.Load("checkpoint\\cnn");

            ReadData rdpredict = new ReadData("data\\train\\", 32, true);
            var      testOut   = model.Predict(rdpredict, 1);


            TrainTest();
        }