[−][src]Struct onednn_sys::dnnl_lrn_desc_t

#[repr(C)]pub struct dnnl_lrn_desc_t {
    pub primitive_kind: dnnl_primitive_kind_t,
    pub prop_kind: dnnl_prop_kind_t,
    pub alg_kind: dnnl_alg_kind_t,
    pub data_desc: dnnl_memory_desc_t,
    pub diff_data_desc: dnnl_memory_desc_t,
    pub local_size: dnnl_dim_t,
    pub lrn_alpha: f32,
    pub lrn_beta: f32,
    pub lrn_k: f32,
}

A descriptor of a Local Response Normalization (LRN) operation.

Fields

primitive_kind: dnnl_primitive_kind_t

The kind of primitive. Used for self-identifying the primitive descriptor. Must be #dnnl_lrn.

prop_kind: dnnl_prop_kind_t

The kind of propagation. Possible values: #dnnl_forward_training, #dnnl_forward_inference, #dnnl_backward, and #dnnl_backward_data.

alg_kind: dnnl_alg_kind_t

LRN algorithm. Possible values: #dnnl_lrn_within_channel and #dnnl_lrn_across_channels.

data_desc: dnnl_memory_desc_t

Source and destination memory descriptor.

diff_data_desc: dnnl_memory_desc_t

Source and destination gradient memory descriptor.

local_size: dnnl_dim_t

The number of channels to sum over (for cross-channel LRN) or the side length of the square region to sum over (for within-channel LRN).

lrn_alpha: f32

LRN alpha parameter.

lrn_beta: f32

LRN beta parameter.

lrn_k: f32

LRN k parameter.

Trait Implementations

impl Clone for dnnl_lrn_desc_t[src]

impl Copy for dnnl_lrn_desc_t[src]

Auto Trait Implementations

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impl<T> Any for T where
    T: 'static + ?Sized, [src]

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    T: ?Sized, [src]

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impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, [src]

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    T: Clone, [src]

type Owned = T

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