openvino/docs/ops/normalization/GRN_1.md

GRN

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.. meta:: :description: Learn about GRN-1 - a normalization operation, which can be performed on a single input tensor.

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:

.. math::

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

.. code-block:: xml :force:

<layer ... type="GRN"> 1 20 224 224 1 20 224 224

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