Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)  0.21.0
Performance library for Deep Learning
Functions

A primitive to perform softmax. More...

Functions

mkldnn_status_t MKLDNN_API mkldnn_softmax_forward_desc_init (mkldnn_softmax_desc_t *softmax_desc, mkldnn_prop_kind_t prop_kind, const mkldnn_memory_desc_t *data_desc, int softmax_axis)
 Initializes a softmax_desc for forward propagation using prop_kind (possible values are mkldnn_forward_training and mkldnn_forward_inference) and memory descriptor data_desc. More...
 
mkldnn_status_t MKLDNN_API mkldnn_softmax_backward_desc_init (mkldnn_softmax_desc_t *softmax_desc, const mkldnn_memory_desc_t *diff_desc, const mkldnn_memory_desc_t *data_desc, int softmax_axis)
 Initializes a softmax_desc for backward propagation using memory descriptors diff_desc and data_desc. More...
 

Detailed Description

A primitive to perform softmax.

\[dst[u][c][in] = \frac{\exp(src[ou][c][in]) - \max\limits_{c}(src[ou][c][in])} {\sum\limits_{c}\{\exp(src[ou][c][in]) - \max\limits_{c}(src[ou][c][in])\}},\]

where $ou, iu$ are outer and inner sizes repectively, defined by data_desc.dims and softmax_axis.

Function Documentation

◆ mkldnn_softmax_forward_desc_init()

mkldnn_status_t MKLDNN_API mkldnn_softmax_forward_desc_init ( mkldnn_softmax_desc_t softmax_desc,
mkldnn_prop_kind_t  prop_kind,
const mkldnn_memory_desc_t data_desc,
int  softmax_axis 
)

Initializes a softmax_desc for forward propagation using prop_kind (possible values are mkldnn_forward_training and mkldnn_forward_inference) and memory descriptor data_desc.

Order of inputs:

Order of outputs:

◆ mkldnn_softmax_backward_desc_init()

mkldnn_status_t MKLDNN_API mkldnn_softmax_backward_desc_init ( mkldnn_softmax_desc_t softmax_desc,
const mkldnn_memory_desc_t diff_desc,
const mkldnn_memory_desc_t data_desc,
int  softmax_axis 
)

Initializes a softmax_desc for backward propagation using memory descriptors diff_desc and data_desc.

Order of inputs:

Order of outputs: