ConvolutionBackwardWeights

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, the attribute will be ignored when auto_pad attribute is specified to same_upper, same_lower or valid	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, the attribute will be ignored when auto_pad attribute is specified to same_upper, same_lower or valid	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
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 the 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