DML_ELEMENT_WISE_CLIP_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_CLIP_OPERATOR_DESC {
  const DML_TENSOR_DESC *InputTensor;
  const DML_TENSOR_DESC *OutputTensor;
  const DML_SCALE_BIAS  *ScaleBias;
  FLOAT                 Min;
  FLOAT                 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.

Min

Type: FLOAT

The minimum value, below which the operator replaces the value with Min.

Max

Type: FLOAT

The maximum value, above which the operator replaces the value with Max.

Remarks

If the tensor data type is not float, then Min and Max are cast to the tensor data type before applying the clipping operation (which for integers means truncating toward zero; and for floating point values rounding to the nearest even).

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_5_0 and above

DML_FEATURE_LEVEL_3_0 and above

DML_FEATURE_LEVEL_2_1 and above

DML_FEATURE_LEVEL_1_0 and above

Requirements