ReduceL1
ReduceL1#
Versioned name: ReduceL1-1
Category: Reduction
Short description: ReduceL1 operation performs the reduction with finding the L1 norm (sum of absolute values) 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 tensor, 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]
wherer
= 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]
, wherer
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 result of ReduceL1 function applied to input tensor.shape[i] = shapeOf(data)[i]
for alli
that is not in the list of axes from the second input. For dimensions fromaxes
,shape[i] == 1
ifkeep_dims == True
, ori
-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.