public NDArray Norm(NDArray result, NDArray src, int dimension, float value)
{
if (value == 0)
{
return(ReductionOp.Invoke(cudaReduceKernels, "e0_norm", 0.0f, ReduceInitType.GivenValue, result, src, dimension));
}
else if (value == 1)
{
return(ReductionOp.Invoke(cudaReduceKernels, "e1_norm", 0.0f, ReduceInitType.GivenValue, result, src, dimension));
}
else if (value == 2)
{
var writeTarget = ReductionOp.Invoke(cudaReduceKernels, "e2_norm", 0.0f, ReduceInitType.GivenValue, result, src, dimension);
Pow(writeTarget, writeTarget, 0.5f);
return(writeTarget);
}
else
{
var writeTarget = ReductionOp.Invoke(cudaReduceKernels, "en_norm", 0.0f, ReduceInitType.GivenValue, result, src, dimension, value);
Pow(writeTarget, writeTarget, 1.0f / value);
return(writeTarget);
}
}
public NDArray Max(NDArray result, NDArray src, int dimension)
{
return(ReductionOp.Invoke(cudaReduceKernels, "max", 0.0f, ReduceInitType.MinValue, result, src, dimension));
}
public NDArray Prod(NDArray result, NDArray src, int dimension)
{
return(ReductionOp.Invoke(cudaReduceKernels, "prod", 1.0f, ReduceInitType.GivenValue, result, src, dimension));
}
public Tensor Max(Tensor result, Tensor src, int dimension)
{
return(ReductionOp.Invoke(cudaReduceKernels, "max", 0.0f, ReduceInitType.MinValue, result, src, dimension));
}
public Tensor Prod(Tensor result, Tensor src, int dimension)
{
return(ReductionOp.Invoke(cudaReduceKernels, "prod", 1.0f, ReduceInitType.GivenValue, result, src, dimension));
}
