[−][src]Struct darknet_sys::layer

#[repr(C)]pub struct layer {
    pub type_: LAYER_TYPE,
    pub activation: ACTIVATION,
    pub cost_type: COST_TYPE,
    pub forward: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>,
    pub backward: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>,
    pub update: Option<unsafe extern "C" fn(arg1: layer, arg2: update_args)>,
    pub forward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>,
    pub backward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>,
    pub update_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: update_args)>,
    pub batch_normalize: c_int,
    pub shortcut: c_int,
    pub batch: c_int,
    pub forced: c_int,
    pub flipped: c_int,
    pub inputs: c_int,
    pub outputs: c_int,
    pub nweights: c_int,
    pub nbiases: c_int,
    pub extra: c_int,
    pub truths: c_int,
    pub h: c_int,
    pub w: c_int,
    pub c: c_int,
    pub out_h: c_int,
    pub out_w: c_int,
    pub out_c: c_int,
    pub n: c_int,
    pub max_boxes: c_int,
    pub groups: c_int,
    pub size: c_int,
    pub side: c_int,
    pub stride: c_int,
    pub reverse: c_int,
    pub flatten: c_int,
    pub spatial: c_int,
    pub pad: c_int,
    pub sqrt: c_int,
    pub flip: c_int,
    pub index: c_int,
    pub binary: c_int,
    pub xnor: c_int,
    pub steps: c_int,
    pub hidden: c_int,
    pub truth: c_int,
    pub smooth: f32,
    pub dot: f32,
    pub angle: f32,
    pub jitter: f32,
    pub saturation: f32,
    pub exposure: f32,
    pub shift: f32,
    pub ratio: f32,
    pub learning_rate_scale: f32,
    pub clip: f32,
    pub noloss: c_int,
    pub softmax: c_int,
    pub classes: c_int,
    pub coords: c_int,
    pub background: c_int,
    pub rescore: c_int,
    pub objectness: c_int,
    pub joint: c_int,
    pub noadjust: c_int,
    pub reorg: c_int,
    pub log: c_int,
    pub tanh: c_int,
    pub mask: *mut c_int,
    pub total: c_int,
    pub alpha: f32,
    pub beta: f32,
    pub kappa: f32,
    pub coord_scale: f32,
    pub object_scale: f32,
    pub noobject_scale: f32,
    pub mask_scale: f32,
    pub class_scale: f32,
    pub bias_match: c_int,
    pub random: c_int,
    pub ignore_thresh: f32,
    pub truth_thresh: f32,
    pub thresh: f32,
    pub focus: f32,
    pub classfix: c_int,
    pub absolute: c_int,
    pub onlyforward: c_int,
    pub stopbackward: c_int,
    pub dontload: c_int,
    pub dontsave: c_int,
    pub dontloadscales: c_int,
    pub numload: c_int,
    pub temperature: f32,
    pub probability: f32,
    pub scale: f32,
    pub cweights: *mut c_char,
    pub indexes: *mut c_int,
    pub input_layers: *mut c_int,
    pub input_sizes: *mut c_int,
    pub map: *mut c_int,
    pub counts: *mut c_int,
    pub sums: *mut *mut f32,
    pub rand: *mut f32,
    pub cost: *mut f32,
    pub state: *mut f32,
    pub prev_state: *mut f32,
    pub forgot_state: *mut f32,
    pub forgot_delta: *mut f32,
    pub state_delta: *mut f32,
    pub combine_cpu: *mut f32,
    pub combine_delta_cpu: *mut f32,
    pub concat: *mut f32,
    pub concat_delta: *mut f32,
    pub binary_weights: *mut f32,
    pub biases: *mut f32,
    pub bias_updates: *mut f32,
    pub scales: *mut f32,
    pub scale_updates: *mut f32,
    pub weights: *mut f32,
    pub weight_updates: *mut f32,
    pub delta: *mut f32,
    pub output: *mut f32,
    pub loss: *mut f32,
    pub squared: *mut f32,
    pub norms: *mut f32,
    pub spatial_mean: *mut f32,
    pub mean: *mut f32,
    pub variance: *mut f32,
    pub mean_delta: *mut f32,
    pub variance_delta: *mut f32,
    pub rolling_mean: *mut f32,
    pub rolling_variance: *mut f32,
    pub x: *mut f32,
    pub x_norm: *mut f32,
    pub m: *mut f32,
    pub v: *mut f32,
    pub bias_m: *mut f32,
    pub bias_v: *mut f32,
    pub scale_m: *mut f32,
    pub scale_v: *mut f32,
    pub z_cpu: *mut f32,
    pub r_cpu: *mut f32,
    pub h_cpu: *mut f32,
    pub prev_state_cpu: *mut f32,
    pub temp_cpu: *mut f32,
    pub temp2_cpu: *mut f32,
    pub temp3_cpu: *mut f32,
    pub dh_cpu: *mut f32,
    pub hh_cpu: *mut f32,
    pub prev_cell_cpu: *mut f32,
    pub cell_cpu: *mut f32,
    pub f_cpu: *mut f32,
    pub i_cpu: *mut f32,
    pub g_cpu: *mut f32,
    pub o_cpu: *mut f32,
    pub c_cpu: *mut f32,
    pub dc_cpu: *mut f32,
    pub binary_input: *mut f32,
    pub input_layer: *mut layer,
    pub self_layer: *mut layer,
    pub output_layer: *mut layer,
    pub reset_layer: *mut layer,
    pub update_layer: *mut layer,
    pub state_layer: *mut layer,
    pub input_gate_layer: *mut layer,
    pub state_gate_layer: *mut layer,
    pub input_save_layer: *mut layer,
    pub state_save_layer: *mut layer,
    pub input_state_layer: *mut layer,
    pub state_state_layer: *mut layer,
    pub input_z_layer: *mut layer,
    pub state_z_layer: *mut layer,
    pub input_r_layer: *mut layer,
    pub state_r_layer: *mut layer,
    pub input_h_layer: *mut layer,
    pub state_h_layer: *mut layer,
    pub wz: *mut layer,
    pub uz: *mut layer,
    pub wr: *mut layer,
    pub ur: *mut layer,
    pub wh: *mut layer,
    pub uh: *mut layer,
    pub uo: *mut layer,
    pub wo: *mut layer,
    pub uf: *mut layer,
    pub wf: *mut layer,
    pub ui: *mut layer,
    pub wi: *mut layer,
    pub ug: *mut layer,
    pub wg: *mut layer,
    pub softmax_tree: *mut tree,
    pub workspace_size: usize,
}

Fields

type_: LAYER_TYPEactivation: ACTIVATIONcost_type: COST_TYPEforward: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>backward: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>update: Option<unsafe extern "C" fn(arg1: layer, arg2: update_args)>forward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>backward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network)>update_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: update_args)>batch_normalize: c_intshortcut: c_intbatch: c_intforced: c_intflipped: c_intinputs: c_intoutputs: c_intnweights: c_intnbiases: c_intextra: c_inttruths: c_inth: c_intw: c_intc: c_intout_h: c_intout_w: c_intout_c: c_intn: c_intmax_boxes: c_intgroups: c_intsize: c_intside: c_intstride: c_intreverse: c_intflatten: c_intspatial: c_intpad: c_intsqrt: c_intflip: c_intindex: c_intbinary: c_intxnor: c_intsteps: c_inthidden: c_inttruth: c_intsmooth: f32dot: f32angle: f32jitter: f32saturation: f32exposure: f32shift: f32ratio: f32learning_rate_scale: f32clip: f32noloss: c_intsoftmax: c_intclasses: c_intcoords: c_intbackground: c_intrescore: c_intobjectness: c_intjoint: c_intnoadjust: c_intreorg: c_intlog: c_inttanh: c_intmask: *mut c_inttotal: c_intalpha: f32beta: f32kappa: f32coord_scale: f32object_scale: f32noobject_scale: f32mask_scale: f32class_scale: f32bias_match: c_intrandom: c_intignore_thresh: f32truth_thresh: f32thresh: f32focus: f32classfix: c_intabsolute: c_intonlyforward: c_intstopbackward: c_intdontload: c_intdontsave: c_intdontloadscales: c_intnumload: c_inttemperature: f32probability: f32scale: f32cweights: *mut c_charindexes: *mut c_intinput_layers: *mut c_intinput_sizes: *mut c_intmap: *mut c_intcounts: *mut c_intsums: *mut *mut f32rand: *mut f32cost: *mut f32state: *mut f32prev_state: *mut f32forgot_state: *mut f32forgot_delta: *mut f32state_delta: *mut f32combine_cpu: *mut f32combine_delta_cpu: *mut f32concat: *mut f32concat_delta: *mut f32binary_weights: *mut f32biases: *mut f32bias_updates: *mut f32scales: *mut f32scale_updates: *mut f32weights: *mut f32weight_updates: *mut f32delta: *mut f32output: *mut f32loss: *mut f32squared: *mut f32norms: *mut f32spatial_mean: *mut f32mean: *mut f32variance: *mut f32mean_delta: *mut f32variance_delta: *mut f32rolling_mean: *mut f32rolling_variance: *mut f32x: *mut f32x_norm: *mut f32m: *mut f32v: *mut f32bias_m: *mut f32bias_v: *mut f32scale_m: *mut f32scale_v: *mut f32z_cpu: *mut f32r_cpu: *mut f32h_cpu: *mut f32prev_state_cpu: *mut f32temp_cpu: *mut f32temp2_cpu: *mut f32temp3_cpu: *mut f32dh_cpu: *mut f32hh_cpu: *mut f32prev_cell_cpu: *mut f32cell_cpu: *mut f32f_cpu: *mut f32i_cpu: *mut f32g_cpu: *mut f32o_cpu: *mut f32c_cpu: *mut f32dc_cpu: *mut f32binary_input: *mut f32input_layer: *mut layerself_layer: *mut layeroutput_layer: *mut layerreset_layer: *mut layerupdate_layer: *mut layerstate_layer: *mut layerinput_gate_layer: *mut layerstate_gate_layer: *mut layerinput_save_layer: *mut layerstate_save_layer: *mut layerinput_state_layer: *mut layerstate_state_layer: *mut layerinput_z_layer: *mut layerstate_z_layer: *mut layerinput_r_layer: *mut layerstate_r_layer: *mut layerinput_h_layer: *mut layerstate_h_layer: *mut layerwz: *mut layeruz: *mut layerwr: *mut layerur: *mut layerwh: *mut layeruh: *mut layeruo: *mut layerwo: *mut layeruf: *mut layerwf: *mut layerui: *mut layerwi: *mut layerug: *mut layerwg: *mut layersoftmax_tree: *mut treeworkspace_size: usize

Trait Implementations

impl Clone for layer[src]

impl Copy for layer[src]

impl Debug for layer[src]

Auto Trait Implementations

impl RefUnwindSafe for layer

impl !Send for layer

impl !Sync for layer

impl Unpin for layer

impl UnwindSafe for layer

Blanket Implementations

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

impl<T> Borrow<T> for T where
    T: ?Sized, [src]

impl<T> BorrowMut<T> for T where
    T: ?Sized, [src]

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

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

impl<T> ToOwned for T where
    T: Clone, [src]

type Owned = T

The resulting type after obtaining ownership.

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

type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, [src]

type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.