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

Descriptor for a pooling 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 &dst_desc, const memory::dims &strides, const memory::dims &kernel, const memory::dims &padding_l, const memory::dims &padding_r)
 Constructs a descriptor for pooling forward propagation primitive. More...
 

Detailed Description

Descriptor for a pooling forward propagation primitive.

Examples:
cnn_inference_f32.cpp, cnn_training_f32.cpp, and cpu_cnn_training_bf16.cpp.

Constructor & Destructor Documentation

◆ desc()

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

Constructs a descriptor for pooling forward propagation primitive.

Inputs:

Outputs:

Parameters
prop_kindPropagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithmPooling algorithm kind: either dnnl::algorithm::pooling_max, dnnl::algorithm::pooling_avg_include_padding, or dnnl::algorithm::pooling_avg (same as dnnl::algorithm::pooling_avg_exclude_padding).
src_descSource memory descriptor.
dst_descDestination memory descriptor.
stridesVector of strides for spatial dimension.
kernelVector of kernel spatial dimensions.
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: