ConvTranspose

ConvTranspose operation performs the same computation as in ConvolutionBackwardData, except the source and destination are swapped.

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	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 the 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