/// <summary>
/// Performs the remote initialization ot the SP on actor nodes.
/// </summary>
/// <param name="c"></param>
/// <param name="distMem"></param>
public override void InitMatrices(Connections c, DistributedMemory distMem)
{
IHtmDistCalculus remoteHtm = distMem?.ColumnDictionary as IHtmDistCalculus;
if (remoteHtm == null)
{
throw new ArgumentException("Must implement IHtmDistCalculus!");
}
this.distMemConfig = distMem;
SparseObjectMatrix <Column> mem = (SparseObjectMatrix <Column>)c.HtmConfig.Memory;
c.HtmConfig.Memory = mem == null ? mem = new SparseObjectMatrix <Column>(c.HtmConfig.ColumnDimensions, dict: distMem.ColumnDictionary) : mem;
c.HtmConfig.InputMatrix = new SparseBinaryMatrix(c.HtmConfig.InputDimensions);
// Initiate the topologies
c.HtmConfig.ColumnTopology = new Topology(c.HtmConfig.ColumnDimensions);
c.HtmConfig.InputTopology = new Topology(c.HtmConfig.InputDimensions);
//Calculate numInputs and numColumns
int numInputs = c.HtmConfig.InputMatrix.GetMaxIndex() + 1;
int numColumns = c.HtmConfig.Memory.GetMaxIndex() + 1;
if (numColumns <= 0)
{
throw new ArgumentException("Invalid number of columns: " + numColumns);
}
if (numInputs <= 0)
{
throw new ArgumentException("Invalid number of inputs: " + numInputs);
}
c.HtmConfig.NumInputs = numInputs;
c.HtmConfig.NumColumns = numColumns;
if (distMem != null)
{
//var distHtmCla = distMem.ColumnDictionary as HtmSparseIntDictionary<Column>;
var distHtmCla = distMem.ColumnDictionary;// as ActorSbDistributedDictionaryBase<Column>;
distHtmCla.HtmConfig = c.HtmConfig;
}
//
// Fill the sparse matrix with column objects
//var numCells = c.getCellsPerColumn();
// var partitions = mem.GetPartitions();
List <KeyPair> colList = new List <KeyPair>();
for (int i = 0; i < numColumns; i++)
{
//colList.Add(new KeyPair() { Key = i, Value = new Column(numCells, i, c.getSynPermConnected(), c.NumInputs) });
colList.Add(new KeyPair()
{
Key = i, Value = c.HtmConfig
});
}
Stopwatch sw = new Stopwatch();
sw.Start();
remoteHtm.InitializeColumnPartitionsDist(colList);
//mem.set(colList);
sw.Stop();
//c.setPotentialPools(new SparseObjectMatrix<Pool>(c.getMemory().getDimensions(), dict: distMem == null ? null : distMem.PoolDictionary));
Debug.WriteLine($" Upload time: {sw.ElapsedMilliseconds}");
// Already initialized by creating of columns.
//c.setConnectedMatrix(new SparseBinaryMatrix(new int[] { numColumns, numInputs }));
//Initialize state meta-management statistics
c.HtmConfig.OverlapDutyCycles = new double[numColumns];
c.HtmConfig.ActiveDutyCycles = new double[numColumns];
c.HtmConfig.MinOverlapDutyCycles = new double[numColumns];
c.HtmConfig.MinActiveDutyCycles = new double[numColumns];
c.BoostFactors = (new double[numColumns]);
ArrayUtils.FillArray(c.BoostFactors, 1);
}
/// <summary>
/// Uses the same implementation as Single-Threaded.
/// </summary>
/// <param name="c"></param>
/// <param name="distMem"></param>
public override void InitMatrices(Connections c, DistributedMemory distMem)
{
base.InitMatrices(c, distMem);
}