Intel® oneAPI Deep Neural Network Developer Guide and Reference
A newer version of this document is available. Customers should click here to go to the newest version.
Reduction
Overview
A primitive to compute reduction operation on data tensor using min, max, mul, sum, mean and norm_lp operations. More…
// structs
struct dnnl::reduction;
// global functions
dnnl_status_t DNNL_API dnnl_reduction_primitive_desc_create(
dnnl_primitive_desc_t* primitive_desc,
dnnl_engine_t engine,
dnnl_alg_kind_t alg_kind,
const_dnnl_memory_desc_t src_desc,
const_dnnl_memory_desc_t dst_desc,
float p,
float eps,
const_dnnl_primitive_attr_t attr
);Detailed Documentation
A primitive to compute reduction operation on data tensor using min, max, mul, sum, mean and norm_lp operations.
See also:
Reduction in developer guide
Global Functions
dnnl_status_t DNNL_API dnnl_reduction_primitive_desc_create(
dnnl_primitive_desc_t* primitive_desc,
dnnl_engine_t engine,
dnnl_alg_kind_t alg_kind,
const_dnnl_memory_desc_t src_desc,
const_dnnl_memory_desc_t dst_desc,
float p,
float eps,
const_dnnl_primitive_attr_t attr
)Creates a primitive descriptor for a reduction primitive.
Parameters:
primitive_desc |
Output primitive descriptor. |
engine |
Engine to use. |
alg_kind |
reduction algorithm kind. Possible values: dnnl_reduction_max, dnnl_reduction_min, dnnl_reduction_sum, dnnl_reduction_mul, dnnl_reduction_mean, dnnl_reduction_norm_lp_max, dnnl_reduction_norm_lp_sum, dnnl_reduction_norm_lp_power_p_max, dnnl_reduction_norm_lp_power_p_sum. |
p |
Algorithm specific parameter. |
eps |
Algorithm specific parameter. |
src_desc |
Source memory descriptor. |
dst_desc |
Destination memory descriptor. |
attr |
Primitive attributes (can be NULL). |
Returns:
dnnl_success on success and a status describing the error otherwise.