ConvolutionBackwardData

Intel® oneAPI Deep Neural Network Developer Guide and Reference

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ID 768875

Date 7/13/2023

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ConvolutionBackwardData

General

ConvolutionBackwardData operation accepts , and optional dst shape as inputs, and compute the .

If auto_pad attribute is specified to one of valid, same_upper and same_lower, pads_begin and pads_end attributes will be ignored. The paddings will be calculated by following the below formula:

Let the parameters be:

Parameter	Depth	Height	Width	Comment
Paddings: Front, top, and left				In the attributes we use `pads_begin` to indicate the corresponding vector of paddings
Padding: Back, bottom, and right				In the attributes we use `pads_end` to indicate the corresponding vector of paddings
Stride				In the attributes we use `strides` to indicate the corresponding vector of strides
Dilation				In the attributes we use `dilations` to indicate the corresponding vector of dilations

Firstly, is calculated according to and . Let be height dimension of and be height dimension of .

If auto_pad attribute is specified as valid :

If auto_pad attribute is specified as same_lower :

If auto_pad attribute is specified as same_upper :

where:

is either an attribute or an input tensor,
is an optional attribute.

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
dst_shape	Denotes the shape of the `dst` 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	`diff_dst`	Required
1	`weights`	Required
2	`dst_shape`	Optional

NOTE:

The shape of

for OIX format or

for XIO format. Both

and

must be divisible by groups attribute.

NOTE:

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

Outputs

Index	Argument Name	Required or Optional
0	`diff_src`	Required

Supported data types

ConvolutionBackwardData operation supports the following data type combinations.

Diff_dst	Weights	Diff_src	Dst_shape
f32	f32	f32	s32
bf16	bf16	bf16	s32
f16	f16	f16	s32

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Intel® oneAPI Deep Neural Network Developer Guide and Reference

ConvolutionBackwardData

General

Operation attributes

Execution arguments

Supported data types