Versioned name: ReduceL2-1
Short description: ReduceL2 operation performs the reduction with finding the L2 norm (square root of sum of squares) on a given input data along dimensions specified by axes input.
OpenVINO description: This OP is as same as OpenVINO OP
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 data, 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:
Default value: None
Description: If set to
Trueit holds axes that are used for reduction. For each such axes, output dimension is equal to 1.
Range of values: True or False
Default value: False
1: Input tensor x of type T1. Required.
2: Axis indices of data input tensor, along which the reduction is performed. 1D tensor of unique elements. The range of elements is
[-r, r-1], where
ris the rank of data input tensor. Exactly one of attribute axes and the second input tensor axes should be available. Optional..
1: The result of ReduceL2 function applied to data input tensor.
shape[i] = shapeOf(data)[i]for all
ithat is not in the list of axes from the second input. For dimensions from
shape[i] == 1if
keep_dims == True, or
i-th dimension is removed from the output otherwise.
T1: f32, f16, bf16.
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.