51 references to ExpOperator_Single
System.Numerics.Tensors (51)
System\Numerics\Tensors\netcore\TensorPrimitives.Cbrt.cs (6)
37return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector128.Create(3f)).As<float, T>(); 42return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector128.Create(3d)).As<double, T>(); 50return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector256.Create(3f)).As<float, T>(); 55return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector256.Create(3d)).As<double, T>(); 63return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector512.Create(3f)).As<float, T>(); 68return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector512.Create(3d)).As<double, T>();
System\Numerics\Tensors\netcore\TensorPrimitives.Cosh.cs (6)
80Vector128<float> z = ExpOperator<float>.Invoke(y - Vector128.Create((float)Single_LOGV)); 89Vector128<double> z = ExpOperator<double>.Invoke(y - Vector128.Create(Double_LOGV)); 101Vector256<float> z = ExpOperator<float>.Invoke(y - Vector256.Create((float)Single_LOGV)); 110Vector256<double> z = ExpOperator<double>.Invoke(y - Vector256.Create(Double_LOGV)); 122Vector512<float> z = ExpOperator<float>.Invoke(y - Vector512.Create((float)Single_LOGV)); 131Vector512<double> z = ExpOperator<double>.Invoke(y - Vector512.Create(Double_LOGV));
System\Numerics\Tensors\netcore\TensorPrimitives.Exp.cs (1)
31InvokeSpanIntoSpan<T, ExpOperator<T>>(x, destination);
System\Numerics\Tensors\netcore\TensorPrimitives.Exp10.cs (3)
37public static Vector128<T> Invoke(Vector128<T> x) => ExpOperator<T>.Invoke(x * Vector128.Create(T.CreateTruncating(NaturalLog10))); 38public static Vector256<T> Invoke(Vector256<T> x) => ExpOperator<T>.Invoke(x * Vector256.Create(T.CreateTruncating(NaturalLog10))); 39public static Vector512<T> Invoke(Vector512<T> x) => ExpOperator<T>.Invoke(x * Vector512.Create(T.CreateTruncating(NaturalLog10)));
System\Numerics\Tensors\netcore\TensorPrimitives.Exp2.cs (3)
37public static Vector128<T> Invoke(Vector128<T> x) => ExpOperator<T>.Invoke(x * Vector128.Create(T.CreateTruncating(NaturalLog2))); 38public static Vector256<T> Invoke(Vector256<T> x) => ExpOperator<T>.Invoke(x * Vector256.Create(T.CreateTruncating(NaturalLog2))); 39public static Vector512<T> Invoke(Vector512<T> x) => ExpOperator<T>.Invoke(x * Vector512.Create(T.CreateTruncating(NaturalLog2)));
System\Numerics\Tensors\netcore\TensorPrimitives.ExpM1.cs (4)
32public static bool Vectorizable => ExpOperator<T>.Vectorizable; 35public static Vector128<T> Invoke(Vector128<T> x) => ExpOperator<T>.Invoke(x) - Vector128<T>.One; 36public static Vector256<T> Invoke(Vector256<T> x) => ExpOperator<T>.Invoke(x) - Vector256<T>.One; 37public static Vector512<T> Invoke(Vector512<T> x) => ExpOperator<T>.Invoke(x) - Vector512<T>.One;
System\Numerics\Tensors\netcore\TensorPrimitives.Pow.cs (6)
70return ExpOperator<float>.Invoke(y.AsSingle() * LogOperator<float>.Invoke(x.AsSingle())).As<float, T>(); 75return ExpOperator<double>.Invoke(y.AsDouble() * LogOperator<double>.Invoke(x.AsDouble())).As<double, T>(); 83return ExpOperator<float>.Invoke(y.AsSingle() * LogOperator<float>.Invoke(x.AsSingle())).As<float, T>(); 88return ExpOperator<double>.Invoke(y.AsDouble() * LogOperator<double>.Invoke(x.AsDouble())).As<double, T>(); 96return ExpOperator<float>.Invoke(y.AsSingle() * LogOperator<float>.Invoke(x.AsSingle())).As<float, T>(); 101return ExpOperator<double>.Invoke(y.AsDouble() * LogOperator<double>.Invoke(x.AsDouble())).As<double, T>();
System\Numerics\Tensors\netcore\TensorPrimitives.RootN.cs (6)
39return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector128.Create((float)_n)).As<float, T>(); 44return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector128.Create((double)_n)).As<double, T>(); 52return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector256.Create((float)_n)).As<float, T>(); 57return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector256.Create((double)_n)).As<double, T>(); 65return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector512.Create((float)_n)).As<float, T>(); 70return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector512.Create((double)_n)).As<double, T>();
System\Numerics\Tensors\netcore\TensorPrimitives.Sigmoid.cs (4)
39public static bool Vectorizable => ExpOperator<T>.Vectorizable; 41public static Vector128<T> Invoke(Vector128<T> x) => Vector128.Create(T.One) / (Vector128.Create(T.One) + ExpOperator<T>.Invoke(-x)); 42public static Vector256<T> Invoke(Vector256<T> x) => Vector256.Create(T.One) / (Vector256.Create(T.One) + ExpOperator<T>.Invoke(-x)); 43public static Vector512<T> Invoke(Vector512<T> x) => Vector512.Create(T.One) / (Vector512.Create(T.One) + ExpOperator<T>.Invoke(-x));
System\Numerics\Tensors\netcore\TensorPrimitives.Single.netcore.cs (1)
16global using ExpOperator_Single = System.Numerics.Tensors.TensorPrimitives.ExpOperator<float>;
System\Numerics\Tensors\netcore\TensorPrimitives.Sinh.cs (6)
62Vector128<float> z = ExpOperator<float>.Invoke(y - Vector128.Create((float)Single_LOGV)); 73Vector128<double> z = ExpOperator<double>.Invoke(y - Vector128.Create(Double_LOGV)); 87Vector256<float> z = ExpOperator<float>.Invoke(y - Vector256.Create((float)Single_LOGV)); 98Vector256<double> z = ExpOperator<double>.Invoke(y - Vector256.Create(Double_LOGV)); 112Vector512<float> z = ExpOperator<float>.Invoke(y - Vector512.Create((float)Single_LOGV)); 123Vector512<double> z = ExpOperator<double>.Invoke(y - Vector512.Create(Double_LOGV));
System\Numerics\Tensors\netcore\TensorPrimitives.SoftMax.cs (2)
39T expSum = Aggregate<T, ExpOperator<T>, AddOperator<T>>(x); 41InvokeSpanScalarIntoSpan<T, ExpOperator<T>, DivideOperator<T>>(x, expSum, destination);
System\Numerics\Tensors\TensorPrimitives.Single.cs (3)
290InvokeSpanIntoSpan<ExpOperator_Single>(x, destination); 862float expSum = Aggregate<ExpOperator_Single, AddOperator_Single>(x); 864InvokeSpanScalarIntoSpan<ExpOperator_Single, DivideOperator_Single>(x, expSum, destination);