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

ConvolutionBackwardWeights ConvTransposeBackwardData