Intel® oneAPI Deep Neural Network Developer Guide and Reference
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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.