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DML_LOCAL_RESPONSE_NORMALIZATION_OPERATOR_DESC structure (directml.h)

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Performs a local response normalization (LRN) function on the input. This operator performs the following computation.

Output = Input / (Bias + (Alpha / LocalSize) * sum(Input^2 for every Input in the local region))^Beta

The data type and size of the input and output tensors must be the same.

Syntax

struct DML_LOCAL_RESPONSE_NORMALIZATION_OPERATOR_DESC {
  const DML_TENSOR_DESC *InputTensor;
  const DML_TENSOR_DESC *OutputTensor;
  BOOL                  CrossChannel;
  UINT                  LocalSize;
  FLOAT                 Alpha;
  FLOAT                 Beta;
  FLOAT                 Bias;
};

Members

InputTensor

Type: const DML_TENSOR_DESC*

The tensor containing the input data. This tensor's Sizes should be { BatchCount, ChannelCount, Height, Width }.

OutputTensor

Type: const DML_TENSOR_DESC*

The tensor to write the results to. This tensor's Sizes should match the InputTensor.

CrossChannel

Type: BOOL

TRUE if the LRN layer sums across channels; otherwise, FALSE.

LocalSize

Type: UINT

The number of elements to sum over per dimension: Width, Height, and optionally Channel (if CrossChannel is set). This value must be at least 1.

Alpha

Type: FLOAT

The value of the scaling parameter. A value of 0.0001 is recommended as default.

Beta

Type: FLOAT

The value of the exponent. A value of 0.75 is recommended as default.

Bias

Type: FLOAT

The value of bias. A value of 1 is recommended as default.

Availability

This operator was introduced in DML_FEATURE_LEVEL_1_0.

Tensor constraints

InputTensor and OutputTensor must have the same DataType and Sizes.

Tensor support

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

Requirements

Requirement Value
Header directml.h