public override IVolume Forward(IVolume input, bool isTraining = false)
{
this.InputActivation = input;
var output = input.Clone();
var length = input.Length;
if (isTraining)
{
// do dropout
for (var i = 0; i < length; i++)
{
if (Random.NextDouble() < this.DropProb)
{
output.Set(i, 0);
this.dropped[i] = true;
} // drop!
else
{
this.dropped[i] = false;
}
}
}
else
{
// scale the activations during prediction
for (var i = 0; i < length; i++)
{
output.Set(i, output.Get(i) * (1 - this.DropProb));
}
}
this.OutputActivation = output;
return(this.OutputActivation); // dummy identity function for now
}
public override IVolume Forward(IVolume input, bool isTraining = false)
{
this.InputActivation = input;
var output = input.Clone();
Parallel.For(0, input.Length, i =>
{
if (output.GetWeight(i) < 0)
{
output.SetWeight(i, 0); // threshold at 0
}
});
this.OutputActivation = output;
return(this.OutputActivation);
}
public override IVolume Forward(IVolume input, bool isTraining = false)
{
this.InputActivation = input;
var output = input.Clone();
#if PARALLEL
Parallel.For(0, input.Length, i =>
#else
for (var i = 0; i < length; i++)
#endif
{
if (output.Get(i) < 0)
{
output.Set(i, 0); // threshold at 0
}
}
public IVolume ClonePlan(IVolume original)
{
return(AddPlan(original.Clone(), original));
}