50 references to ExpOperator_Single
System.Numerics.Tensors (50)
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)
87Vector128<float> z = ExpOperator<float>.Invoke(y - Vector128.Create((float)Single_LOGV)); 96Vector128<double> z = ExpOperator<double>.Invoke(y - Vector128.Create(Double_LOGV)); 108Vector256<float> z = ExpOperator<float>.Invoke(y - Vector256.Create((float)Single_LOGV)); 117Vector256<double> z = ExpOperator<double>.Invoke(y - Vector256.Create(Double_LOGV)); 129Vector512<float> z = ExpOperator<float>.Invoke(y - Vector512.Create((float)Single_LOGV)); 138Vector512<double> z = ExpOperator<double>.Invoke(y - Vector512.Create(Double_LOGV));
System\Numerics\Tensors\netcore\TensorPrimitives.Exp.cs (2)
32if (typeof(T) == typeof(Half) && TryUnaryInvokeHalfAsInt16<T, ExpOperator<float>>(x, destination)) 37InvokeSpanIntoSpan<T, ExpOperator<T>>(x, destination);
System\Numerics\Tensors\netcore\TensorPrimitives.Exp10.cs (3)
44public static Vector128<T> Invoke(Vector128<T> x) => ExpOperator<T>.Invoke(x * Vector128.Create(T.CreateTruncating(NaturalLog10))); 45public static Vector256<T> Invoke(Vector256<T> x) => ExpOperator<T>.Invoke(x * Vector256.Create(T.CreateTruncating(NaturalLog10))); 46public static Vector512<T> Invoke(Vector512<T> x) => ExpOperator<T>.Invoke(x * Vector512.Create(T.CreateTruncating(NaturalLog10)));
System\Numerics\Tensors\netcore\TensorPrimitives.Exp2.cs (3)
44public static Vector128<T> Invoke(Vector128<T> x) => ExpOperator<T>.Invoke(x * Vector128.Create(T.CreateTruncating(NaturalLog2))); 45public static Vector256<T> Invoke(Vector256<T> x) => ExpOperator<T>.Invoke(x * Vector256.Create(T.CreateTruncating(NaturalLog2))); 46public static Vector512<T> Invoke(Vector512<T> x) => ExpOperator<T>.Invoke(x * Vector512.Create(T.CreateTruncating(NaturalLog2)));
System\Numerics\Tensors\netcore\TensorPrimitives.ExpM1.cs (4)
39public static bool Vectorizable => ExpOperator<T>.Vectorizable; 42public static Vector128<T> Invoke(Vector128<T> x) => ExpOperator<T>.Invoke(x) - Vector128<T>.One; 43public static Vector256<T> Invoke(Vector256<T> x) => ExpOperator<T>.Invoke(x) - Vector256<T>.One; 44public 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)
44public static bool Vectorizable => ExpOperator<T>.Vectorizable; 46public static Vector128<T> Invoke(Vector128<T> x) => Vector128.Create(T.One) / (Vector128.Create(T.One) + ExpOperator<T>.Invoke(-x)); 47public static Vector256<T> Invoke(Vector256<T> x) => Vector256.Create(T.One) / (Vector256.Create(T.One) + ExpOperator<T>.Invoke(-x)); 48public 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)
69Vector128<float> z = ExpOperator<float>.Invoke(y - Vector128.Create((float)Single_LOGV)); 80Vector128<double> z = ExpOperator<double>.Invoke(y - Vector128.Create(Double_LOGV)); 94Vector256<float> z = ExpOperator<float>.Invoke(y - Vector256.Create((float)Single_LOGV)); 105Vector256<double> z = ExpOperator<double>.Invoke(y - Vector256.Create(Double_LOGV)); 119Vector512<float> z = ExpOperator<float>.Invoke(y - Vector512.Create((float)Single_LOGV)); 130Vector512<double> z = ExpOperator<double>.Invoke(y - Vector512.Create(Double_LOGV));
System\Numerics\Tensors\netcore\TensorPrimitives.SoftMax.cs (1)
39InvokeSpanIntoSpan<T, ExpOperator<T>>(x, destination);
System\Numerics\Tensors\TensorPrimitives.Single.cs (2)
290InvokeSpanIntoSpan<ExpOperator_Single>(x, destination); 862InvokeSpanIntoSpan<ExpOperator_Single>(x, destination);