Deep Neural Network Library (DNNL)  1.3.0
Performance library for Deep Learning
Public Member Functions | List of all members
dnnl::deconvolution_forward::desc Struct Reference

Descriptor for a deconvolution forward propagation primitive. More...

#include <dnnl.hpp>

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Public Member Functions

 desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
 Constructs a descriptor for a deconvolution forward propagation primitive with bias. More...
 
 desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &padding_l, const memory::dims &padding_r)
 Constructs a descriptor for a deconvolution forward propagation primitive without bias. More...
 
 desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &bias_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
 Constructs a descriptor for a dilated deconvolution forward propagation primitive with bias. More...
 
 desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &src_desc, const memory::desc &weights_desc, const memory::desc &dst_desc, const memory::dims &strides, const memory::dims &dilates, const memory::dims &padding_l, const memory::dims &padding_r)
 Constructs a descriptor for a dilated deconvolution forward propagation primitive without bias. More...
 

Detailed Description

Descriptor for a deconvolution forward propagation primitive.

Constructor & Destructor Documentation

◆ desc() [1/4]

dnnl::deconvolution_forward::desc::desc ( prop_kind  prop_kind,
algorithm  algorithm,
const memory::desc src_desc,
const memory::desc weights_desc,
const memory::desc bias_desc,
const memory::desc dst_desc,
const memory::dims strides,
const memory::dims padding_l,
const memory::dims padding_r 
)
inline

Constructs a descriptor for a deconvolution forward propagation primitive with bias.

Note
Memory descriptors can be initialized with dnnl::memory::format_tag::any value of format_tag.

Inputs:

Outputs:

Parameters
prop_kindPropagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithmDeconvolution algorithm: dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd.
src_descSource memory descriptor.
weights_descWeights memory descriptor.
bias_descBias memory descriptor. Passing zero memory descriptor disables the bias term.
dst_descDestination memory descriptor.
stridesVector of strides for spatial dimension.
padding_lVector of padding values for low indices for each spatial dimension (front, top, left).
padding_rVector of padding values for high indices for each spatial dimension (back, bottom, right).

◆ desc() [2/4]

dnnl::deconvolution_forward::desc::desc ( prop_kind  prop_kind,
algorithm  algorithm,
const memory::desc src_desc,
const memory::desc weights_desc,
const memory::desc dst_desc,
const memory::dims strides,
const memory::dims padding_l,
const memory::dims padding_r 
)
inline

Constructs a descriptor for a deconvolution forward propagation primitive without bias.

Note
Memory descriptors can be initialized with dnnl::memory::format_tag::any value of format_tag.

Inputs:

Outputs:

Parameters
prop_kindPropagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithmDeconvolution algorithm: dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd.
src_descSource memory descriptor.
weights_descWeights memory descriptor.
dst_descDestination memory descriptor.
stridesVector of strides for spatial dimension.
padding_lVector of padding values for low indices for each spatial dimension (front, top, left).
padding_rVector of padding values for high indices for each spatial dimension (back, bottom, right).

◆ desc() [3/4]

dnnl::deconvolution_forward::desc::desc ( prop_kind  prop_kind,
algorithm  algorithm,
const memory::desc src_desc,
const memory::desc weights_desc,
const memory::desc bias_desc,
const memory::desc dst_desc,
const memory::dims strides,
const memory::dims dilates,
const memory::dims padding_l,
const memory::dims padding_r 
)
inline

Constructs a descriptor for a dilated deconvolution forward propagation primitive with bias.

Note
Memory descriptors can be initialized with dnnl::memory::format_tag::any value of format_tag.

Inputs:

Outputs:

Parameters
prop_kindPropagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithmDeconvolution algorithm: dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd.
src_descSource memory descriptor.
weights_descWeights memory descriptor.
bias_descBias memory descriptor. Passing zero memory descriptor disables the bias term.
dst_descDestination memory descriptor.
stridesVector of strides for spatial dimension.
dilatesDilations for each spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_lVector of padding values for low indices for each spatial dimension (front, top, left).
padding_rVector of padding values for high indices for each spatial dimension (back, bottom, right).

◆ desc() [4/4]

dnnl::deconvolution_forward::desc::desc ( prop_kind  prop_kind,
algorithm  algorithm,
const memory::desc src_desc,
const memory::desc weights_desc,
const memory::desc dst_desc,
const memory::dims strides,
const memory::dims dilates,
const memory::dims padding_l,
const memory::dims padding_r 
)
inline

Constructs a descriptor for a dilated deconvolution forward propagation primitive without bias.

Note
Memory descriptors can be initialized with dnnl::memory::format_tag::any value of format_tag.

Inputs:

Outputs:

Parameters
prop_kindPropagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithmDeconvolution algorithm: dnnl::algorithm::deconvolution_direct, and dnnl::algorithm::deconvolution_winograd.
src_descSource memory descriptor.
weights_descWeights memory descriptor.
dst_descDestination memory descriptor.
stridesVector of strides for spatial dimension.
dilatesDilations for each spatial dimension. A zero value means no dilation in the corresponding dimension.
padding_lVector of padding values for low indices for each spatial dimension (front, top, left).
padding_rVector of padding values for high indices for each spatial dimension (back, bottom, right).

The documentation for this struct was generated from the following file: