ReduceMin

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 the 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