ReduceMean#

Versioned name: ReduceMean-1

Category: Reduction

Short description: ReduceMean operation performs the reduction with finding the arithmetic mean on a given input data along dimensions specified by axes.

OpenVINO description: This OP is as same as OpenVINO OP

Attributes

  • axes

    • Description: specify indices of input data, along which the reduction is performed. If axes is a list, reduce over all of them. If axes is empty, corresponds to the identity operation. If axes contains all dimensions of input tensor, a single reduction value is calculated for the entire input tensor. Exactly one of attribute axes and the second input tensor axes should be available.

    • Range of values: [-r, r-1] where r = rank(input)

    • Type: s64[]

    • Default value: empty list

    • Required: no

  • keep_dims

    • Description: If set to True it holds axes that are used for reduction. For each such axes, output dimension is equal to 1.

    • Range of values: True or False

    • Type: bool

    • Default value: False

    • Required: no

Inputs

  • 1: input - input tensor. Required.

    • Type: T1

  • 2: axes - 1-D tensor specifying the axis along which the reduction is performed. 1D tensor of unique elements. The range of elements is [-r, r-1], where r is the rank of input tensor. Exactly one of attribute axes and the second input tensor axes should be available. Optional..

    • Type: T2

Outputs

  • 1: output - the he result of ReduceMean function applied to input tensor. shape[i] = shapeOf(data)[i] for all i that is not in the list of axes from the second input. For dimensions from axes, shape[i] == 1 if keep_dims == True, or i-th dimension is removed from the output otherwise.

    • Type: T1

Types:

  • T1: f32, f16, bf16.

  • T2: s32.

  • Note: The input tensor and the result tensor have the same data type denoted by T1. For example, if input is f32 tensor, then result tensor has f32 data type.