Ejemplo n.º 1
0
            public void QuadraticTest()
            {
                var actual   = new Matrix(4, 1);
                var expected = new Matrix(4, 1);

                actual.InRandomize();
                expected.InRandomize();

                var autoErr = new QuadraticCost().Evaluate(actual, expected);
                var error   = 0.0;

                for (var i = 0; i < actual.Rows; i++)
                {
                    for (var j = 0; j < actual.Columns; j++)
                    {
                        error += Math.Pow(actual[i, j] - expected[i, j], 2);
                    }
                }
                error /= 2;
                error /= actual.Rows * actual.Columns;
                Assert.IsTrue(Math.Abs(error - autoErr) < 0.01, new QuadraticCost().Type().ToString() + " Forward!");

                var autoDErr = new QuadraticCost().Backward(actual, expected);
                var dErr     = new Matrix(actual.Rows, actual.Columns);

                for (var i = 0; i < actual.Rows; i++)
                {
                    for (var j = 0; j < actual.Columns; j++)
                    {
                        dErr[i, j] = Math.Pow(expected[i, j] - actual[i, j], 2);
                    }
                }
                dErr *= 1.0 / actual.Rows * actual.Columns;
                Assert.IsTrue(Math.Abs(dErr.FrobeniusNorm() - autoDErr.FrobeniusNorm()) < 0.01, new QuadraticCost().Type().ToString() + " Backward!");
            }
Ejemplo n.º 2
0
 public void SetUp()
 {
     _sut = new QuadraticCost();
 }
Ejemplo n.º 3
0
        public void InitNetwork(ECostType costType, CostSettings costSettings, EOptimizerType optimizerType, OptimizerSettings optimizerSettings)
        {
            Utility.Dims InShape;
            Utility.Dims OutShape;
            Utility.Dims WShape;

            for (int i = 1; i < Layers.Count; i++)
            {
                Data.Data["a" + i.ToString()] = new Matrix(Layers[i].NCount, 1);
                InShape = new Utility.Dims(Layers[i].NCount, 1);

                Data.Data["b" + i.ToString()] = Matrix.RandomMatrix(Layers[i].NCount, 1, 1, EDistrubution.Gaussian);

                OutShape = new Utility.Dims(Layers[i].NCount, 1);

                Data.Data["W" + i.ToString()] = Matrix.RandomMatrix(Layers[i - 1].NCount, Layers[i].NCount, 1, EDistrubution.Gaussian);
                WShape = new Utility.Dims(Layers[i - 1].NCount, Layers[i].NCount);

                Layers[i].SetSettings(new LayerSettings(InShape, OutShape, WShape));
            }

            Data.Data["a0"] = new Matrix(Layers[0].NCount, 1);
            InShape         = new Utility.Dims(Layers[0].NCount, 1);

            Data.Data["b0"] = new Matrix(Layers[0].NCount, 1);
            OutShape        = new Utility.Dims(Layers[0].NCount, 1);

            Data.Data["W0"] = new Matrix(Layers[0].NCount * Layers[1].NCount, Layers[1].NCount);
            WShape          = new Utility.Dims(Layers[0].NCount * Layers[1].NCount, Layers[1].NCount);

            Layers[0].SetSettings(new LayerSettings(InShape, OutShape, WShape));

            switch (costType)
            {
            case ECostType.Invalid:
                throw new ArgumentException("Invalid Cost Function Selected!");

            case ECostType.CrossEntropyCost:
                CostFunction = new CrossEntropyCost((CrossEntropyCostSettings)costSettings);
                break;

            case ECostType.ExponentionalCost:
                CostFunction = new ExponentionalCost((ExponentionalCostSettings)costSettings);
                break;

            case ECostType.GeneralizedKullbackLeiblerDivergence:
                CostFunction = new GeneralizedKullbackLeiblerDivergence((GeneralizedKullbackLeiblerDivergenceSettings)costSettings);
                break;

            case ECostType.HellingerDistance:
                CostFunction = new HellingerDistance((HellingerDistanceSettings)costSettings);
                break;

            case ECostType.ItakuraSaitoDistance:
                CostFunction = new ItakuraSaitoDistance((ItakuraSaitoDistanceSettings)costSettings);
                break;

            case ECostType.KullbackLeiblerDivergence:
                CostFunction = new KullbackLeiblerDivergence((KullbackLeiblerDivergenceSettings)costSettings);
                break;

            case ECostType.QuadraticCost:
                CostFunction = new QuadraticCost((QuadraticCostSettings)costSettings);
                break;

            default:
                throw new ArgumentException("Invalid Cost Function Selected!");
            }

            switch (optimizerType)
            {
            case EOptimizerType.Invalid:
                throw new ArgumentException("Invalid Optimizer Function Selected!");

            case EOptimizerType.AdaDelta:
                OptimizerFunction = new AdaDelta((AdaDeltaSettings)optimizerSettings);
                break;

            case EOptimizerType.AdaGrad:
                OptimizerFunction = new AdaGrad((AdaGradSettings)optimizerSettings);
                break;

            case EOptimizerType.Adam:
                OptimizerFunction = new Adam((AdamSettings)optimizerSettings);
                break;

            case EOptimizerType.Adamax:
                OptimizerFunction = new Adamax((AdamaxSettings)optimizerSettings);
                break;

            case EOptimizerType.GradientDescent:
                OptimizerFunction = new GradientDescent((GradientDescentSettings)optimizerSettings);
                break;

            case EOptimizerType.Momentum:
                OptimizerFunction = new Momentum((MomentumSettings)optimizerSettings);
                break;

            case EOptimizerType.Nadam:
                OptimizerFunction = new Nadam((NadamSettings)optimizerSettings);
                break;

            case EOptimizerType.NesterovMomentum:
                OptimizerFunction = new NesterovMomentum((NesterovMomentumSettings)optimizerSettings);
                break;

            case EOptimizerType.RMSProp:
                OptimizerFunction = new RMSProp((RMSPropSettings)optimizerSettings);
                break;

            default:
                throw new ArgumentException("Invalid Optimizer Function Selected!");
            }
        }