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Feature Scope

Data Types

Table 1 Supported data type combinations (input and output data types being the same)

src1 Data Type

src2 Data Type

...

srcN Data Type

dst Data Type

f32

f32

f32

f32

f32

f16

f16

f16

f16

f16

bf16

bf16

bf16

bf16

bf16

s32

s32

s32

s32

s32

s8

s8

s8

s8

s8

u8

u8

u8

u8

u8

Data Layout

A maximum of 5 dimensions are supported. Input tensors must have the same dimension and dimension values. The following data layout formats are supported, and the data layout of the input and output tensors must be the same.

Tensor Dimension

src1/…/srcn/dst

1D

a

2D

ab,ba

3D

abc,acb,bac,bca,cab,cba

4D

abcd,abdc,acbd,acdb,adbc,adcb,bacd,bcda,cdab,cdba,dcab

5D

abcde,abced,abdec,acbde,acdeb,adecb,bacde,bcdea,cdeab,cdeba,decab

Parameter Constraints

Field

Description

Value Range

--dst

src data type

f32

f16

bf16

s32

s8

u8

--ddt

dst data type

f32

f16

bf16

s32

s8

u8

--stag

src data layout

a

ab

ba

abc

acb

bac

bca

cab

cba

abcd

abdc

acbd

acdb

adbc

adcb

bacd

bcda

cdab

cdba

dcab

abcde

abced

abdec

acbde

acdeb

adecb

bacde

bcdea

cdeab

cdeba

decab

--dtag

dst data layout

a

ab

ba

abc

acb

bac

bca

cab

cba

abcd

abdc

acbd

acdb

adbc

adcb

bacd

bcda

cdab

cdba

dcab

abcde

abced

abdec

acbde

acdeb

adecb

bacde

bcdea

cdeab

cdeba

decab

--axis

Concatenation direction

[0, dim_num - 1]

[problem dim]

src0 scale: src1 scale

N1xN11xN3xN4xN5: N1xN12xN3xN4xN5

It is required that the lengths of other dimensions be the same except that of the concatenation dimension.

Concat requires that the memory layout of input and output tensors be the same and the corresponding data types be the same.