MeanErrorLossParameter.cs

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.ComponentModel;
using MyCaffe.basecode;
using MyCaffe.common;
 
namespace MyCaffe.param
{
    [Serializable]
    [TypeConverter(typeof(ExpandableObjectConverter))]
    public class MeanErrorLossParameter : LayerParameterBase
    {
        int m_nAxis = 1; // Axis used to calculate the loss normalization.
        MEAN_ERROR m_meanErrorType = MEAN_ERROR.MAE; // default to the Mean Absolute Error.
 
 
        public MeanErrorLossParameter()
        {
        }
 
        [Description("Specifies the axis of the probability, default = 1")]
        public int axis
        {
            get { return m_nAxis; }
            set { m_nAxis = value; }
        }
 
        public MEAN_ERROR mean_error_type
        {
            get { return m_meanErrorType; }
            set { m_meanErrorType = value; }
        }
 
        public override object Load(System.IO.BinaryReader br, bool bNewInstance = true)
        {
            RawProto proto = RawProto.Parse(br.ReadString());
            MeanErrorLossParameter p = FromProto(proto);
 
            if (!bNewInstance)
                Copy(p);
 
            return p;
        }
 
        public override void Copy(LayerParameterBase src)
        {
            MeanErrorLossParameter p = (MeanErrorLossParameter)src;
            m_nAxis = p.m_nAxis;
            m_meanErrorType = p.m_meanErrorType;
        }
 
        public override LayerParameterBase Clone()
        {
            MeanErrorLossParameter p = new MeanErrorLossParameter();
            p.Copy(this);
            return p;
        }
 
        public override RawProto ToProto(string strName)
        {
            RawProtoCollection rgChildren = new RawProtoCollection();
 
            rgChildren.Add("axis", axis.ToString());
            rgChildren.Add("mean_error_type", mean_error_type.ToString());
 
            return new RawProto(strName, "", rgChildren);
        }
 
        public static MeanErrorLossParameter FromProto(RawProto rp)
        {
            string strVal;
            MeanErrorLossParameter p = new MeanErrorLossParameter();
 
            if ((strVal = rp.FindValue("axis")) != null)
                p.axis = int.Parse(strVal);
 
            if ((strVal = rp.FindValue("mean_error_type")) != null)
            {
                switch (strVal)
                {
                    case "MSE":
                        p.mean_error_type = MEAN_ERROR.MSE;
                        break;
                    case "MAE":
                        p.mean_error_type = MEAN_ERROR.MAE;
                        break;
                    default:
                        throw new Exception("The mean _error_type parameter must be one of the following: MSE, MAE");
                }
            }
 
            return p;
        }
    }
}