# 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>