DML_ELEMENT_WISE_CLIP1_OPERATOR_DESC structure (directml.h)

Performs the following operation for each element of InputTensor, placing the result into the corresponding element of OutputTensor. This operator clamps (or limits) every element in the input within the closed interval [Min, Max].

f(x) = max(Min, min(x, Max))

Where max(a,b) returns the larger of the two values, and min(a,b) returns the smaller of the two values a,b.

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

Syntax

struct DML_ELEMENT_WISE_CLIP1_OPERATOR_DESC {
  const DML_TENSOR_DESC *InputTensor;
  const DML_TENSOR_DESC *OutputTensor;
  const DML_SCALE_BIAS  *ScaleBias;
  DML_TENSOR_DATA_TYPE  MinMaxDataType;
  DML_SCALAR_UNION      Min;
  DML_SCALAR_UNION      Max;
};

Members

InputTensor

Type: const DML_TENSOR_DESC*

The input tensor to read from.

OutputTensor

Type: const DML_TENSOR_DESC*

The output tensor to write the results to.

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.

MinMaxDataType

Type: DML_TENSOR_DATA_TYPE

The data type of the Min and Max members, which must match OutputTensor.DataType.

Min

Type: DML_SCALAR_UNION

The minimum value, below which the operator replaces the value with Min. MinMaxDataType determines how to interpret the field.

Max

Type: DML_SCALAR_UNION

The maximum value, above which the operator replaces the value with Max. MinMaxDataType determines how to interpret the field.

Remarks

Availability

This operator was introduced in DML_FEATURE_LEVEL_5_0.

Tensor constraints

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

Tensor support

Requirements