Contents

Select

General

The select operation returns a tensor filled with the elements from the second or the third input, depending on the condition (the first input) value.

dst[i] = cond[i] ? src_0[i] : src_1[i]

Broadcasting is supported.

Broadcasting rules

If the auto_broadcast attribute is not none, the select operation takes a two-step broadcast before performing the selection:

  • Step 1 : Input tensors src_0 and src_1 are broadcasted to dst_shape according to the Numpy broadcast rules.

  • Step 2 : Then, the cond tensor will be one-way broadcasted to the dst_shape of broadcasted src_0 and src_1. To be more specific, we align the two shapes to the right and compare them from right to left. Each dimension should be either equal or the dimension of cond should be 1.

  • example :

    • cond={4, 5}, dst_shape={2, 3, 4, 5} => dst = {2, 3, 4, 5}

    • cond={3, 1, 5}, dst_shape={2, 3, 4, 5} => dst = {2, 3, 4, 5}

    • cond={3,5}, dst_shape={2, 3, 4, 5} => dst = invalid_shape

Operation attributes

Attribute Name

Description

Value Type

Supported Values

Required or Optional

auto_broadcast

Specifies rules used for auto-broadcasting of src tensors.

string

none , numpy (default)

Optional

Execution arguments

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

Inputs

Index

Argument Name

Required or Optional

0

cond

Required

1

src_0

Required

2

src_1

Required

Note

All input shapes should match and no broadcasting is allowed if the auto_broadcast attribute is set to none, or can be broadcasted according to the broadcasting rules mentioned above if auto_broadcast attribute is set to numpy.

Outputs

Index

Argument Name

Required or Optional

0

dst

Required

Supported data types

Select operation supports the following data type combinations.

Cond

Src_0 / Src_1

Dst

boolean

f32

f32

boolean

bf16

bf16

boolean

f16

f16
Round Sigmoid