ReduceMin¶

General¶

ReduceMin operation performs the reduction with finding the minimum value on a given src data along dimensions specified by axes.

Take channel axis = 0 and keep_dims = True as an example:

${dst}_{0,\cdots,\cdots} = \min\{src_{i,\cdots,\cdots}\} ,i \in [0,channelNum-1]$

Operation attributes¶

Attribute Name

Description

Value Type

Supported Values

Required or Optional

axes

Specify indices of src 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 src tensor, a single reduction value is calculated for the entire src tensor. Exactly one of attribute axes and the second input tensor axes should be available.

s64

A s64 list values which is in the range of [-r, r-1] where r = rank(src). Empty list(default)

Optional

keep_dims

If set to true it holds axes that are used for reduction. For each such axes, dst dimension is equal to 1.

bool

true , false (default)

Optional

Execution arguments¶

The inputs and outputs must be provided according to below index order when constructing an operation.

Inputs¶

Index

Argument Name

Required or Optional

0

src

Required

1

axes

Optional

Note

axes is a 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 src tensor. Exactly one of attribute axes and the second input tensor axes should be available.

Outputs¶

Index

Argument Name

Required or Optional

0

dst

Required

Note

The result of ReduceMin function applied to src 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 dst otherwise.

Supported data types¶

ReduceMin operation supports the following data type combinations.

Src

Dst

Axes

f32

f32

s32

bf16

bf16

s32

f16

f16

s32