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UID title description helpviewer_keywords old-location tech.root ms.assetid ms.date req.header req.include-header req.target-type req.target-min-winverclnt req.target-min-winversvr req.kmdf-ver req.umdf-ver req.ddi-compliance req.unicode-ansi req.idl req.max-support req.namespace req.assembly req.type-library req.lib req.dll req.irql targetos req.typenames req.redist ms.custom f1_keywords dev_langs topic_type api_type api_location api_name
NS:directml.DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC
DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC
Computes the identity for each element of *InputTensor*, placing the result into the corresponding element of *OutputTensor*.
DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC
DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC structure
direct3d12.dml_element_wise_identity_operator_desc
directml/DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC
direct3d12\dml_element_wise_identity_operator_desc.htm
directml
2DA260F4-5995-4D9A-B5A8-D37E0927579E
10/29/2020
directml.h
Windows
Windows
19H1
DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC
directml/DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC
c++
APIRef
kbSyntax
HeaderDef
DirectML.h
DML_ELEMENT_WISE_IDENTITY_OPERATOR_DESC

-description

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

f(x) = x

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

The identity operation is often used to copy a tensor.

It can also be used to transform the layout of tensors by manipulating strides (see Using strides to express padding and memory layout).

Availability

This operator was introduced in DML_FEATURE_LEVEL_1_0.

Tensor constraints

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

Tensor support

DML_FEATURE_LEVEL_4_1 and above

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 1 to 8 FLOAT64, FLOAT32, FLOAT16, INT64, INT32, INT16, INT8, UINT64, UINT32, UINT16, UINT8
OutputTensor Output 1 to 8 FLOAT64, FLOAT32, FLOAT16, INT64, INT32, INT16, INT8, UINT64, UINT32, UINT16, UINT8

DML_FEATURE_LEVEL_3_0 and above

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 1 to 8 FLOAT32, FLOAT16, INT32, INT16, INT8, UINT32, UINT16, UINT8
OutputTensor Output 1 to 8 FLOAT32, FLOAT16, INT32, INT16, INT8, UINT32, UINT16, UINT8

DML_FEATURE_LEVEL_2_1 and above

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 4 to 5 FLOAT32, FLOAT16, INT32, INT16, INT8, UINT32, UINT16, UINT8
OutputTensor Output 4 to 5 FLOAT32, FLOAT16, INT32, INT16, INT8, UINT32, UINT16, UINT8

DML_FEATURE_LEVEL_1_0 and above

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 4 to 5 FLOAT32, FLOAT16
OutputTensor Output 4 to 5 FLOAT32, FLOAT16