ConvTranspose

General

ConvTranspose operation performs the same computation as calculating the gradient with regard to \(\src\) of Convolution operation. To see the difference visually, you can go to visualization page.

Operation attributes

Attribute Name

Description

Value Type

Supported Values

Required or Optional

strides

Controls the strides the weights tensor is moved when computing convolution

s64

A s64 list containing positive values

Required

pads_begin

Controls number of zeros to be add to the front/top/left of spatial dimensions

s64

A s64 list containing non-negative values

Required

pads_end

Controls number of zeros to be add to the back/bottom/right of spatial dimensions

s64

A s64 list containing non-negative values

Required

dilations

Controls the amount of stretching the kernel before convolution ( visualization link )

s64

A s64 list containing positive values (>1 means dilated convolution)

Required

auto_pad

Controls how the padding is calculated

string

none (default), same_upper , same_lower , valid

Optional

output_padding

Adds additional amount of padding per each spatial axis in dst .

s64

A s64 list containing non-negative values, all zeros by default

Optional

groups

Controls how input channels and output channels are divided into

s64

A positive s64 value, 1 by default

Optional

data_format

Controls how to interpret the shape of src and dst .

string

NCX , NXC (default)

Optional

weights_format

Controls how to interpret the shape of weights

string

OIX , XIO (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

weights

Required

2

bias

Optional

Note

The shape of \(\weights\) is \((in\_channels / groups, out\_channels, spatial\_shape)\) for IOX format or \((spatial\_shape, out\_channels, in\_channels / groups)\) for XOI format. Both \(in\_channels\) and \(out\_channels\) must be divisible by groups attribute.

Outputs

Index

Argument Name

Required or Optional

0

dst

Required

Supported data types

ConvTranspose operation supports the following data type combinations.

Src

Weights

Bias

Dst

f32

f32

f32

f32

bf16

bf16

bf16

bf16

f16

f16

f16

f16