ConvolutionBackwardWeights¶

General¶

ConvolutionBackwardWeights operation accepts \(\src\), \(\diffdst\) and optional weights shape as inputs, and compute the \(\diffweights\).

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
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
weights_shape	Denotes the shape of the `weights` tensor.	s64	A s64 list containing positive values	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	`diff_dst`	Required
2	`weights_shape`	Optional

Note

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

Note Either weights_shape input or weights_shape attribute should be provided. If both provided, weights_shape input will precede over weights_shape attribute.

Outputs¶

Index	Argument Name	Required or Optional
0	`diff_weights`	Required

Supported data types¶

ConvolutionBackwardWeights operation supports the following data type combinations.

Src	Diff_dst	Diff_weights	Weights_shape
f32	f32	f32	s32
bf16	bf16	bf16	s32
f16	f16	f16	s32

ConvolutionBackwardData ConvTranspose