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

Descriptor for an elementwise forward propagation primitive. More...

#include <dnnl.hpp>

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Public Member Functions

 desc (prop_kind prop_kind, algorithm algorithm, const memory::desc &data_desc, float alpha=0, float beta=0)
 Constructs a descriptor for an elementwise forward propagation primitive. More...
 

Detailed Description

Descriptor for an elementwise forward propagation primitive.

Examples:
cnn_inference_f32.cpp, cnn_training_f32.cpp, cpu_cnn_training_bf16.cpp, cross_engine_reorder.cpp, getting_started.cpp, gpu_opencl_interop.cpp, and performance_profiling.cpp.

Constructor & Destructor Documentation

◆ desc()

dnnl::eltwise_forward::desc::desc ( prop_kind  prop_kind,
algorithm  algorithm,
const memory::desc data_desc,
float  alpha = 0,
float  beta = 0 
)
inline

Constructs a descriptor for an elementwise forward propagation primitive.

Inputs:

Outputs:

Parameters
prop_kindPropagation kind. Possible values are dnnl::prop_kind::forward_training, and dnnl::prop_kind::forward_inference.
algorithmElementwise algorithm kind.
data_descSource and destination memory descriptors.
alphaThe alpha parameter for the elementwise operation. Specific meaning depends on the algorithm.
betaThe beta parameter for the elementwise operation. Specific meaning depends on the algorithm.

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