public WeightMatrix Dropout(WeightMatrix V, bool[] droppedMask)
{
var res = new WeightMatrix(V.Rows, V.Columns, 0);
var N = V.Weight.Length;
var V2 = V.Clone();
for (var i = 0; i < N; i++)
{
if (droppedMask[i])
{
V2.Weight[i] = 0;
} // drop!
}
res = V2;
if (this.needs_backprop)
{
Action backward = () =>
{
var chain_grad = res;
V.Gradient = new double[N]; // zero out gradient wrt data
for (var i = 0; i < N; i++)
{
if (!(droppedMask[i]))
{
V.Gradient[i] += chain_grad.Gradient[i]; // copy over the gradient
}
}
};
this.backprop.Add(backward);
}
return(res);
}
public WeightMatrix Dropout(WeightMatrix V, double drop_prob)
{
var res = new WeightMatrix(V.Rows, V.Columns, 0);
var N = V.Weight.Length;
bool[] dropped = new bool[V.Rows * V.Columns];
var V2 = V.Clone();
for (var i = 0; i < N; i++)
{
if (ra.NextDouble() < drop_prob)
{
V2.Weight[i] = 0; dropped[i] = true;
} // drop!
else
{
dropped[i] = false;
}
}
res = V2;
if (this.needs_backprop)
{
Action backward = () =>
{
var chain_grad = res;
V.Gradient = new double[N]; // zero out gradient wrt data
for (var i = 0; i < N; i++)
{
if (!(dropped[i]))
{
V.Gradient[i] += chain_grad.Gradient[i]; // copy over the gradient
}
}
};
this.backprop.Add(backward);
}
return(res);
}