コード例 #1
0
ファイル: Program.cs プロジェクト: webmaster1983/ConvNetSharp
        public static Set[] CreateSampleSets(
            TestNet consumer,
            int batchSize,
            int totalSets)
        {
            var sets = new List <Set>();

            var builder = BuilderInstance <double> .Volume;

            for (var s = 0; s < totalSets; s += batchSize)
            {
                var batchInputs = consumer
                                  .InputShape
                                  .Select(inputShape =>
                {
                    var inputBatch = Shape.From(inputShape.Dimensions[0], inputShape.Dimensions[1], inputShape.Dimensions[2], batchSize);
                    return(builder.Random(inputBatch));
                }).ToArray();

                var outputShape      = Shape.From(consumer.OutputShape.Dimensions[0], consumer.OutputShape.Dimensions[1], consumer.OutputShape.Dimensions[2], batchSize);
                var tempBatchOutputs = builder.Random(outputShape);
                var batchOutputs     = builder.SameAs(outputShape);
                tempBatchOutputs.Softmax(batchOutputs);

                sets.Add(new Set
                {
                    Inputs  = batchInputs,
                    Outputs = batchOutputs
                });
            }

            return(sets.ToArray());
        }
コード例 #2
0
ファイル: Program.cs プロジェクト: zaharPonimash/ConvNetSharp
        private static void ExecuteNeuralNet(
            string name,
            TestNet net,
            int batchSize,
            int totalSets,
            int iterations)
        {
            var inputs = CreateSampleSets(net, batchSize, totalSets);

            var stopWatch = new Stopwatch();

            Console.WriteLine($"- {name} ------");
            stopWatch.Restart();

            var trainer = new SgdTrainer(net);

            trainer.LearningRate = 0.01;
            trainer.Momentum     = 0.5;
            trainer.BatchSize    = batchSize;

            for (var i = 0; i < iterations; i++)
            {
                foreach (var set in inputs)
                {
                    trainer.Train(set.Inputs[0], set.Outputs);
                }
            }

            stopWatch.Stop();

            Console.WriteLine("    total: {0:0.000}ms", stopWatch.ElapsedMilliseconds);
            Console.WriteLine("  forward: {0:0.000}ms", trainer.ForwardTimeMs);
            Console.WriteLine(" backward: {0:0.000}ms", trainer.BackwardTimeMs);
            Console.WriteLine("   update: {0:0.000}ms", trainer.UpdateWeightsTimeMs);
        }
コード例 #3
0
ファイル: Program.cs プロジェクト: webmaster1983/ConvNetSharp
        private static TestNet Create(int layerSize, int nmLayers, Shape input, int output)
        {
            var net = new TestNet();

            net.InputShape  = new[] { Shape.From(input) };
            net.OutputShape = Shape.From(1, 1, output);
            net.AddLayer(new InputLayer(input.Dimensions[0], input.Dimensions[1], input.Dimensions[2]));
            for (var i = 0; i < nmLayers; i++)
            {
                net.AddLayer(new FullyConnLayer(layerSize));
                net.AddLayer(new ReluLayer());
            }
            net.AddLayer(new FullyConnLayer(output));
            net.AddLayer(new SoftmaxLayer(output));
            return(net);
        }