private NeuroWeight(NeuroWeight <T> other)
{
Weight = other.Weight.CloneMatrix();
Gradient = other.Gradient.CloneMatrix();
Cache1 = other.Cache1.CloneMatrix();
Cache2 = other.Cache2.CloneMatrix();
CacheM = other.CacheM.CloneMatrix();
Timestep = other.Timestep;
}
public static NeuroWeight <T> Load(Stream stream)
{
var result = new NeuroWeight <T>();
using (var reader = new BinaryReader(stream, Encoding.UTF8, true))
{
result.Weight = MatrixFactory.Load <T>(stream);
bool saveCache = reader.ReadBoolean();
bool saveGrad = reader.ReadBoolean();
if (saveCache)
{
result.Cache1 = MatrixFactory.Load <T>(stream);
result.Cache2 = MatrixFactory.Load <T>(stream);
result.CacheM = MatrixFactory.Load <T>(stream);
result.Timestep = reader.ReadInt32();
}
else
{
result.Cache1 = Matrix <T> .Build.Dense(result.Weight.RowCount, result.Weight.ColumnCount);
result.Cache2 = Matrix <T> .Build.Dense(result.Weight.RowCount, result.Weight.ColumnCount);
result.CacheM = Matrix <T> .Build.Dense(result.Weight.RowCount, result.Weight.ColumnCount);
}
if (saveGrad)
{
result.Gradient = MatrixFactory.Load <T>(stream);
}
else
{
result.Gradient = Matrix <T> .Build.Dense(result.Weight.RowCount, result.Weight.ColumnCount);
}
}
return(result);
}