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UID title description tech.root ms.date targetos req.construct-type req.ddi-compliance req.dll req.header req.include-header req.kmdf-ver req.lib req.max-support req.redist req.target-min-winverclnt req.target-min-winversvr req.target-type req.typenames req.umdf-ver req.unicode-ansi topic_type api_type api_location api_name f1_keywords dev_langs
NS:directml.DML_ELEMENT_WISE_ASINH_OPERATOR_DESC
DML_ELEMENT_WISE_ASINH_OPERATOR_DESC
Computes the hyperbolic arcsine for each element of *InputTensor*, placing the result into the corresponding element of *OutputTensor*.
directml
10/29/2020
Windows
structure
directml.h
Windows 10, version 2004 (10.0; Build 19041)
Windows Server, version 2004 (10.0; Build 19041)
Windows
APIRef
kbSyntax
HeaderDef
directml.h
DML_ELEMENT_WISE_ASINH_OPERATOR_DESC
DML_ELEMENT_WISE_ASINH_OPERATOR_DESC
directml/DML_ELEMENT_WISE_ASINH_OPERATOR_DESC
c++

-description

Computes the hyperbolic arcsine for each element of InputTensor, placing the result into the corresponding element of OutputTensor.

f(x) = asinh(x) // ln(x + sqrt(x * x + 1))

This operator supports in-place execution, meaning that OutputTensor is permitted to alias InputTensor during binding.

-struct-fields

-field InputTensor

Type: const DML_TENSOR_DESC*

The input tensor to read from.

-field OutputTensor

Type: const DML_TENSOR_DESC*

The output tensor to write the results to.

-field ScaleBias

Type: _Maybenull_ const DML_SCALE_BIAS*

An optional scale and bias to apply to the input. If present, this has the effect of applying the function g(x) = x * scale + bias to each input element prior to computing this operator.

-remarks

Availability

This operator was introduced in DML_FEATURE_LEVEL_2_0.

Tensor constraints

InputTensor and OutputTensor must have the same DataType, DimensionCount, and Sizes.

Tensor support

DML_FEATURE_LEVEL_3_0 and above

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 1 to 8 FLOAT32, FLOAT16
OutputTensor Output 1 to 8 FLOAT32, FLOAT16

DML_FEATURE_LEVEL_2_0 and above

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 4 FLOAT32, FLOAT16
OutputTensor Output 4 FLOAT32, FLOAT16

-see-also