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GRN

Versioned name : GRN-1

Category : Normalization

Short description : GRN is the Global Response Normalization with L2 norm (across channels only).

Detailed description :

GRN computes the L2 norm across channels for input tensor with shape [N, C, ...]. GRN does the following with the input tensor:

output[i0, i1, ..., iN] = x[i0, i1, ..., iN] / sqrt(sum[j = 0..C-1](x[i0, j, ..., iN]\*\*2) + bias)

Attributes :

  • bias

    • Description : bias is added to the sum of squares.

    • Range of values : a positive floating-point number

    • Type : float

    • Required : yes

Inputs

  • 1 : data - A tensor of type T and 2 <= rank <= 4. Required.

Outputs

  • 1 : The result of GRN function applied to data input tensor. Normalized tensor of the same type and shape as the data input.

Types

  • T : arbitrary supported floating-point type.

Example

<layer ... type="GRN">
    <data bias="1e-4"/>
    <input>
        <port id="0">
            <dim>1</dim>
            <dim>20</dim>
            <dim>224</dim>
            <dim>224</dim>
        </port>
    </input>
    <output>
        <port id="0" precision="f32">
            <dim>1</dim>
            <dim>20</dim>
            <dim>224</dim>
            <dim>224</dim>
        </port>
    </output>
</layer>
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