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 https://github.com/vdumoulin/conv_arithmetic/blob/master/README.md “visualization page”.

Operation attributes¶

Attribute Name	De
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	`IOX` , `XOI` (default)	Optional

Execution arguments¶

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

Inputs¶

Index	Argu
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	Argu
0	`dst`	Required

Supported data types¶

ConvTranspose operation supports the following data type combinations.

Src	Weights
f32	f32	f32	f32
bf16	bf16	bf16	bf16
f16	f16	f16	f16

ConvolutionBackwardWeights ConvTransposeBackwardData