public ACTIVATION GetACTIVATIONFromReader(IDataReader reader)
{
try
{
ACTIVATION aCTIVATION = new ACTIVATION
(
(int)reader["ACTIVATIONID"],
(int)reader["CUST_ID"],
reader["CARRIERTYPE"].ToString(),
reader["ACTIVATIONTYPE"].ToString(),
reader["ACCOUNTNO"].ToString(),
reader["ORDERNO"].ToString(),
reader["DEALERCODE"].ToString(),
(DateTime)reader["ACTIVATIONDATE"],
reader["MOBILENO"].ToString(),
reader["SIMM"].ToString(),
reader["IMEI"].ToString(),
reader["RATEPLAN"].ToString(),
(int)reader["COMMAMOUNT"],
(int)reader["SPIFF"],
(int)reader["REBATE"],
(char)reader["ISACTIVE"],
(int)reader["CREATEDBY"],
(DateTime)reader["CREATEDON"],
(int)reader["UPDATEDBY"],
(DateTime)reader["UPDATEDON"]
);
return(aCTIVATION);
}
catch (Exception ex)
{
return(null);
}
}
public NeuralGroup(string p_id, JSONObject p_data)
{
_id = p_id;
_dim = int.Parse(p_data["dim"].str);
_activationFunction = (ACTIVATION)Enum.Parse(typeof(ACTIVATION), p_data["actfn"].str);
_inConnections = new List <Connection>();
_outConnection = new List <Connection>();
_output = Vector.Zero(_dim);
_ap = Vector.Zero(_dim);
_bias = BasePool.Instance.Get(_dim);
byte[] buffer = Convert.FromBase64String(p_data["bias"].str);
MemoryStream stream = new MemoryStream(buffer);
BinaryReader reader = new BinaryReader(stream);
for (int i = 0; i < _dim; i++)
{
_bias[i] = reader.ReadSingle();
}
_derivs = null;
_valid = false;
}
public bool UpdateACTIVATION(ACTIVATION aCTIVATION)
{
using (SqlConnection connection = new SqlConnection(this.ConnectionString))
{
SqlCommand cmd = new SqlCommand("AbiMatuEnterprise_UpdateACTIVATION", connection);
cmd.CommandType = CommandType.StoredProcedure;
cmd.Parameters.Add("@ACTIVATIONID", SqlDbType.Int).Value = aCTIVATION.ACTIVATIONID;
cmd.Parameters.Add("@CUST_ID", SqlDbType.Int).Value = aCTIVATION.CUST_ID;
cmd.Parameters.Add("@CARRIERTYPE", SqlDbType.VarChar).Value = aCTIVATION.CARRIERTYPE;
cmd.Parameters.Add("@ACTIVATIONTYPE", SqlDbType.VarChar).Value = aCTIVATION.ACTIVATIONTYPE;
cmd.Parameters.Add("@ACCOUNTNO", SqlDbType.VarChar).Value = aCTIVATION.ACCOUNTNO;
cmd.Parameters.Add("@ORDERNO", SqlDbType.VarChar).Value = aCTIVATION.ORDERNO;
cmd.Parameters.Add("@DEALERCODE", SqlDbType.VarChar).Value = aCTIVATION.DEALERCODE;
cmd.Parameters.Add("@ACTIVATIONDATE", SqlDbType.DateTime).Value = aCTIVATION.ACTIVATIONDATE;
cmd.Parameters.Add("@MOBILENO", SqlDbType.VarChar).Value = aCTIVATION.MOBILENO;
cmd.Parameters.Add("@SIMM", SqlDbType.VarChar).Value = aCTIVATION.SIMM;
cmd.Parameters.Add("@IMEI", SqlDbType.VarChar).Value = aCTIVATION.IMEI;
cmd.Parameters.Add("@RATEPLAN", SqlDbType.VarChar).Value = aCTIVATION.RATEPLAN;
cmd.Parameters.Add("@COMMAMOUNT", SqlDbType.Int).Value = aCTIVATION.COMMAMOUNT;
cmd.Parameters.Add("@SPIFF", SqlDbType.Int).Value = aCTIVATION.SPIFF;
cmd.Parameters.Add("@REBATE", SqlDbType.Int).Value = aCTIVATION.REBATE;
cmd.Parameters.Add("@ISACTIVE", SqlDbType.Char).Value = aCTIVATION.ISACTIVE;
cmd.Parameters.Add("@CREATEDBY", SqlDbType.Int).Value = aCTIVATION.CREATEDBY;
cmd.Parameters.Add("@CREATEDON", SqlDbType.DateTime).Value = aCTIVATION.CREATEDON;
cmd.Parameters.Add("@UPDATEDBY", SqlDbType.Int).Value = aCTIVATION.UPDATEDBY;
cmd.Parameters.Add("@UPDATEDON", SqlDbType.DateTime).Value = aCTIVATION.UPDATEDON;
connection.Open();
int result = cmd.ExecuteNonQuery();
return(result == 1);
}
}
public static ACTIVATION GetACTIVATIONByID(int id)
{
ACTIVATION aCTIVATION = new ACTIVATION();
SqlACTIVATIONProvider sqlACTIVATIONProvider = new SqlACTIVATIONProvider();
aCTIVATION = sqlACTIVATIONProvider.GetACTIVATIONByID(id);
return(aCTIVATION);
}
public CoreLayer(int p_dim, ACTIVATION p_activationFunction, TYPE p_type) : base(p_type, CORE)
{
NeuralGroup core = new NeuralGroup("core", p_dim, p_activationFunction);
_groups.Add("core", core);
_inputGroup = _outputGroup = core;
}
public void Add(int size, ACTIVATION a, LOSS l, double bias)
{
activation = a;
loss = l;
for (int i = 0; i < size; i++)
{
Neuron n = new Neuron(this.Owner);
n.activation = activation;
n.loss = loss;
n.bias = bias;
n.father = this;
Neurons.Add(n);
}
}
public RecurrentLayer(int p_dim, ACTIVATION p_activationFunction, TYPE p_type) : base(p_type, RECURRENT)
{
NeuralGroup core = new NeuralGroup("core", p_dim, p_activationFunction);
NeuralGroup context = new NeuralGroup("context", p_dim, ACTIVATION.IDENTITY);
_groups.Add("core", core);
_groups.Add("context", context);
Connection c = Connect(context, core, true);
c.Init(Connection.INIT.LECUN_UNIFORM, 0.05f);
Connection r = Connect(core, context, false);
r.Weights = Matrix.Identity(p_dim, p_dim);
_inputGroup = _outputGroup = core;
}
public NeuralGroup(string p_id, int p_dim, ACTIVATION p_activationFunction)
{
_id = p_id;
_dim = p_dim;
_batch = 0;
_activationFunction = p_activationFunction;
_inConnections = new List <Connection>();
_outConnection = new List <Connection>();
_output = Vector.Zero(_dim);
_output_t = null;
_ap = Vector.Zero(_dim);
_ap_t = null;
_bias = Vector.Random(_dim);
_bias_t = null;
//_bias = Vector.Zero(_dim);
_derivs = null;
_derivs_t = null;
_valid = false;
}
public void LoadFromCode(List <string> code)
{
string s;
string s2;
string tag;
string[] ss;
string[] ss2;
Synapse _synapse;
Neuron _neuron;
Layer _layer;
Dictionary <int, NeuralObject> mapping = new Dictionary <int, NeuralObject>();
int _id = -1;
string _class = "";
ACTIVATION _activation = ACTIVATION.SOFTMAX;
LOSS _loss = LOSS.CROSS_ENTROPY;
int _father = -1;
double _bias = 0.00;
double _weight = 0.00;
double _learnfactor = 0.00;
int _previous = -1;
int _next = -1;
int maxID = -1;
for (int i = 0; i < code.Count; i++)
{
s = code[i].Trim();
ss = s.Split('|');
for (int j = 0; j < ss.Length; j++)
{
s = ss[j].Trim();
ss2 = s.Split(':');
s = ss2[0].Trim();
s2 = ss2[1].Trim();
switch (s)
{
default:
throw new System.Exception("unknow parameter");
case "ID":
if (!int.TryParse(s2, out _id))
{
throw new System.Exception("id not integer");
}
break;
case "Class":
_class = s2;
break;
case "Activation":
if (!Enum.TryParse <ACTIVATION>(s2, out _activation))
{
throw new System.Exception("invalid activation");
}
break;
case "Loss":
if (!Enum.TryParse <LOSS>(s2, out _loss))
{
throw new System.Exception("invalid loss");
}
break;
case "Bias":
if (!double.TryParse(s2, out _bias))
{
throw new System.Exception("bias is not double");
}
break;
case "Father":
if (!int.TryParse(s2, out _father))
{
throw new System.Exception("father not integer");
}
break;
case "Weight":
if (!double.TryParse(s2, out _weight))
{
throw new System.Exception("weight is not double");
}
break;
case "Learn Factor":
if (!double.TryParse(s2, out _learnfactor))
{
throw new System.Exception("learn factor is not double");
}
break;
case "Previous":
if (!int.TryParse(s2, out _previous))
{
throw new System.Exception("previous not integer");
}
break;
case "Next":
if (!int.TryParse(s2, out _next))
{
throw new System.Exception("next not integer");
}
break;
}
}
maxID = maxID < _id ? _id : maxID;
_lastid = _id;
switch (_class)
{
case "NeuralNetwork":
break;
case "Layer":
_layer = new Layer(this);
_layer.activation = _activation;
_layer.loss = _loss;
layers.Add(_layer);
mapping.Add(_id, _layer);
break;
case "Neuron":
_neuron = new Neuron(this);
_neuron.father = (Layer)mapping[_father];
_neuron.bias = _bias;
_neuron.activation = _activation;
_neuron.loss = _loss;
layers.Last().Neurons.Add(_neuron);
mapping.Add(_id, _neuron);
break;
case "Synapse":
_synapse = new Synapse(this);
_synapse.weight = _weight;
_synapse.learnFactor = _learnfactor;
_synapse.previous = (Neuron)mapping[_previous];
_synapse.next = (Neuron)mapping[_next];
layers.Last().Synapses.Add(_synapse);
mapping.Add(_id, _synapse);
break;
default:
break;
}
}
_lastid = maxID + 1;
}
public static bool UpdateACTIVATION(ACTIVATION aCTIVATION)
{
SqlACTIVATIONProvider sqlACTIVATIONProvider = new SqlACTIVATIONProvider();
return(sqlACTIVATIONProvider.UpdateACTIVATION(aCTIVATION));
}
public static int InsertACTIVATION(ACTIVATION aCTIVATION)
{
SqlACTIVATIONProvider sqlACTIVATIONProvider = new SqlACTIVATIONProvider();
return(sqlACTIVATIONProvider.InsertACTIVATION(aCTIVATION));
}
public Nodes(NODE mode, ACTIVATION act, int n)
{
init(mode, act, n);
}
public Nodes()
{
property = NODE.IN;
activation = ACTIVATION.SIN;
nb = 0;
}
public void init(NODE mode, ACTIVATION act, int n)
{
property = mode;
activation = act;
nb = n;
}
