DML_ACTIVATION_HARD_SIGMOID_OPERATOR_DESC structure (directml.h)

Article
02/22/2024

Performs a hard sigmoid function on every element in InputTensor, placing the result into the corresponding element of OutputTensor.

f(x) = max(0, min(Alpha * x + Beta, 1))

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 the output tensor is permitted to alias InputTensor during binding.

Syntax

struct DML_ACTIVATION_HARD_SIGMOID_OPERATOR_DESC {
  const DML_TENSOR_DESC *InputTensor;
  const DML_TENSOR_DESC *OutputTensor;
  FLOAT                 Alpha;
  FLOAT                 Beta;
};

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.

Alpha

Type: FLOAT

The alpha coefficient. A typical default for this value is 0.2.

Beta

Type: FLOAT

The beta coefficient. A typical default for this value is 0.5.

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_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 to 5	FLOAT32, FLOAT16
OutputTensor	Output	4 to 5	FLOAT32, FLOAT16

DML_FEATURE_LEVEL_1_0 and above

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

Requirements

Requirement	Value
Header	directml.h