#[repr(C)]pub struct layer {Show 415 fields
pub type_: LAYER_TYPE,
pub activation: ACTIVATION,
pub lstm_activation: ACTIVATION,
pub cost_type: COST_TYPE,
pub forward: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>,
pub backward: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>,
pub update: Option<unsafe extern "C" fn(arg1: layer, arg2: c_int, arg3: f32, arg4: f32, arg5: f32)>,
pub forward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>,
pub backward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>,
pub update_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: c_int, arg3: f32, arg4: f32, arg5: f32, arg6: f32)>,
pub share_layer: *mut layer,
pub train: c_int,
pub avgpool: c_int,
pub batch_normalize: c_int,
pub shortcut: c_int,
pub batch: c_int,
pub dynamic_minibatch: c_int,
pub forced: c_int,
pub flipped: c_int,
pub inputs: c_int,
pub outputs: c_int,
pub mean_alpha: f32,
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 truth_size: c_int,
pub groups: c_int,
pub group_id: c_int,
pub size: c_int,
pub side: c_int,
pub stride: c_int,
pub stride_x: c_int,
pub stride_y: c_int,
pub dilation: c_int,
pub antialiasing: c_int,
pub maxpool_depth: c_int,
pub maxpool_zero_nonmax: c_int,
pub out_channels: c_int,
pub reverse: f32,
pub coordconv: 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 scale_wh: c_int,
pub binary: c_int,
pub xnor: c_int,
pub peephole: c_int,
pub use_bin_output: c_int,
pub keep_delta_gpu: c_int,
pub optimized_memory: c_int,
pub steps: c_int,
pub history_size: c_int,
pub bottleneck: c_int,
pub time_normalizer: f32,
pub state_constrain: c_int,
pub hidden: c_int,
pub truth: c_int,
pub smooth: f32,
pub dot: f32,
pub deform: c_int,
pub grad_centr: c_int,
pub sway: c_int,
pub rotate: c_int,
pub stretch: c_int,
pub stretch_sway: c_int,
pub angle: f32,
pub jitter: f32,
pub resize: f32,
pub saturation: f32,
pub exposure: f32,
pub shift: f32,
pub ratio: f32,
pub learning_rate_scale: f32,
pub clip: f32,
pub focal_loss: c_int,
pub classes_multipliers: *mut f32,
pub label_smooth_eps: f32,
pub noloss: c_int,
pub softmax: c_int,
pub classes: c_int,
pub detection: c_int,
pub embedding_layer_id: c_int,
pub embedding_output: *mut f32,
pub embedding_size: c_int,
pub sim_thresh: f32,
pub track_history_size: c_int,
pub dets_for_track: c_int,
pub dets_for_show: c_int,
pub track_ciou_norm: f32,
pub coords: c_int,
pub background: c_int,
pub rescore: c_int,
pub objectness: c_int,
pub does_cost: 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 bflops: f32,
pub adam: c_int,
pub B1: f32,
pub B2: f32,
pub eps: f32,
pub t: 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: f32,
pub ignore_thresh: f32,
pub truth_thresh: f32,
pub iou_thresh: f32,
pub thresh: f32,
pub focus: f32,
pub classfix: c_int,
pub absolute: c_int,
pub assisted_excitation: c_int,
pub onlyforward: c_int,
pub stopbackward: c_int,
pub train_only_bn: c_int,
pub dont_update: c_int,
pub burnin_update: 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 dropblock_size_rel: f32,
pub dropblock_size_abs: c_int,
pub dropblock: c_int,
pub scale: f32,
pub receptive_w: c_int,
pub receptive_h: c_int,
pub receptive_w_scale: c_int,
pub receptive_h_scale: c_int,
pub cweights: *mut c_char,
pub indexes: *mut c_int,
pub input_layers: *mut c_int,
pub input_sizes: *mut c_int,
pub layers_output: *mut *mut f32,
pub layers_delta: *mut *mut f32,
pub weights_type: WEIGHTS_TYPE_T,
pub weights_normalization: WEIGHTS_NORMALIZATION_T,
pub map: *mut c_int,
pub counts: *mut c_int,
pub sums: *mut *mut f32,
pub rand: *mut f32,
pub cost: *mut f32,
pub labels: *mut c_int,
pub class_ids: *mut c_int,
pub contrastive_neg_max: c_int,
pub cos_sim: *mut f32,
pub exp_cos_sim: *mut f32,
pub p_constrastive: *mut f32,
pub contrast_p_gpu: *mut contrastive_params,
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_ema: *mut f32,
pub biases_ema: *mut f32,
pub scales_ema: *mut f32,
pub weights: *mut f32,
pub weight_updates: *mut f32,
pub scale_x_y: f32,
pub objectness_smooth: c_int,
pub new_coords: c_int,
pub show_details: c_int,
pub max_delta: f32,
pub uc_normalizer: f32,
pub iou_normalizer: f32,
pub obj_normalizer: f32,
pub cls_normalizer: f32,
pub delta_normalizer: f32,
pub iou_loss: IOU_LOSS,
pub iou_thresh_kind: IOU_LOSS,
pub nms_kind: NMS_KIND,
pub beta_nms: f32,
pub yolo_point: YOLO_POINT,
pub align_bit_weights_gpu: *mut c_char,
pub mean_arr_gpu: *mut f32,
pub align_workspace_gpu: *mut f32,
pub transposed_align_workspace_gpu: *mut f32,
pub align_workspace_size: c_int,
pub align_bit_weights: *mut c_char,
pub mean_arr: *mut f32,
pub align_bit_weights_size: c_int,
pub lda_align: c_int,
pub new_lda: c_int,
pub bit_align: c_int,
pub col_image: *mut f32,
pub delta: *mut f32,
pub output: *mut f32,
pub activation_input: *mut f32,
pub delta_pinned: c_int,
pub output_pinned: c_int,
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 stored_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 stored_c_cpu: *mut f32,
pub dc_cpu: *mut f32,
pub binary_input: *mut f32,
pub bin_re_packed_input: *mut u32,
pub t_bit_input: *mut c_char,
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 vo: *mut layer,
pub uf: *mut layer,
pub wf: *mut layer,
pub vf: *mut layer,
pub ui: *mut layer,
pub wi: *mut layer,
pub vi: *mut layer,
pub ug: *mut layer,
pub wg: *mut layer,
pub softmax_tree: *mut tree,
pub workspace_size: usize,
pub indexes_gpu: *mut c_int,
pub stream: c_int,
pub wait_stream_id: c_int,
pub z_gpu: *mut f32,
pub r_gpu: *mut f32,
pub h_gpu: *mut f32,
pub stored_h_gpu: *mut f32,
pub bottelneck_hi_gpu: *mut f32,
pub bottelneck_delta_gpu: *mut f32,
pub temp_gpu: *mut f32,
pub temp2_gpu: *mut f32,
pub temp3_gpu: *mut f32,
pub dh_gpu: *mut f32,
pub hh_gpu: *mut f32,
pub prev_cell_gpu: *mut f32,
pub prev_state_gpu: *mut f32,
pub last_prev_state_gpu: *mut f32,
pub last_prev_cell_gpu: *mut f32,
pub cell_gpu: *mut f32,
pub f_gpu: *mut f32,
pub i_gpu: *mut f32,
pub g_gpu: *mut f32,
pub o_gpu: *mut f32,
pub c_gpu: *mut f32,
pub stored_c_gpu: *mut f32,
pub dc_gpu: *mut f32,
pub m_gpu: *mut f32,
pub v_gpu: *mut f32,
pub bias_m_gpu: *mut f32,
pub scale_m_gpu: *mut f32,
pub bias_v_gpu: *mut f32,
pub scale_v_gpu: *mut f32,
pub combine_gpu: *mut f32,
pub combine_delta_gpu: *mut f32,
pub forgot_state_gpu: *mut f32,
pub forgot_delta_gpu: *mut f32,
pub state_gpu: *mut f32,
pub state_delta_gpu: *mut f32,
pub gate_gpu: *mut f32,
pub gate_delta_gpu: *mut f32,
pub save_gpu: *mut f32,
pub save_delta_gpu: *mut f32,
pub concat_gpu: *mut f32,
pub concat_delta_gpu: *mut f32,
pub binary_input_gpu: *mut f32,
pub binary_weights_gpu: *mut f32,
pub bin_conv_shortcut_in_gpu: *mut f32,
pub bin_conv_shortcut_out_gpu: *mut f32,
pub mean_gpu: *mut f32,
pub variance_gpu: *mut f32,
pub m_cbn_avg_gpu: *mut f32,
pub v_cbn_avg_gpu: *mut f32,
pub rolling_mean_gpu: *mut f32,
pub rolling_variance_gpu: *mut f32,
pub variance_delta_gpu: *mut f32,
pub mean_delta_gpu: *mut f32,
pub col_image_gpu: *mut f32,
pub x_gpu: *mut f32,
pub x_norm_gpu: *mut f32,
pub weights_gpu: *mut f32,
pub weight_updates_gpu: *mut f32,
pub weight_deform_gpu: *mut f32,
pub weight_change_gpu: *mut f32,
pub weights_gpu16: *mut f32,
pub weight_updates_gpu16: *mut f32,
pub biases_gpu: *mut f32,
pub bias_updates_gpu: *mut f32,
pub bias_change_gpu: *mut f32,
pub scales_gpu: *mut f32,
pub scale_updates_gpu: *mut f32,
pub scale_change_gpu: *mut f32,
pub input_antialiasing_gpu: *mut f32,
pub output_gpu: *mut f32,
pub output_avg_gpu: *mut f32,
pub activation_input_gpu: *mut f32,
pub loss_gpu: *mut f32,
pub delta_gpu: *mut f32,
pub cos_sim_gpu: *mut f32,
pub rand_gpu: *mut f32,
pub drop_blocks_scale: *mut f32,
pub drop_blocks_scale_gpu: *mut f32,
pub squared_gpu: *mut f32,
pub norms_gpu: *mut f32,
pub gt_gpu: *mut f32,
pub a_avg_gpu: *mut f32,
pub input_sizes_gpu: *mut c_int,
pub layers_output_gpu: *mut *mut f32,
pub layers_delta_gpu: *mut *mut f32,
pub srcTensorDesc: *mut c_void,
pub dstTensorDesc: *mut c_void,
pub srcTensorDesc16: *mut c_void,
pub dstTensorDesc16: *mut c_void,
pub dsrcTensorDesc: *mut c_void,
pub ddstTensorDesc: *mut c_void,
pub dsrcTensorDesc16: *mut c_void,
pub ddstTensorDesc16: *mut c_void,
pub normTensorDesc: *mut c_void,
pub normDstTensorDesc: *mut c_void,
pub normDstTensorDescF16: *mut c_void,
pub weightDesc: *mut c_void,
pub weightDesc16: *mut c_void,
pub dweightDesc: *mut c_void,
pub dweightDesc16: *mut c_void,
pub convDesc: *mut c_void,
pub fw_algo: UNUSED_ENUM_TYPE,
pub fw_algo16: UNUSED_ENUM_TYPE,
pub bd_algo: UNUSED_ENUM_TYPE,
pub bd_algo16: UNUSED_ENUM_TYPE,
pub bf_algo: UNUSED_ENUM_TYPE,
pub bf_algo16: UNUSED_ENUM_TYPE,
pub poolingDesc: *mut c_void,
}Fields§
§type_: LAYER_TYPE§activation: ACTIVATION§lstm_activation: ACTIVATION§cost_type: COST_TYPE§forward: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>§backward: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>§update: Option<unsafe extern "C" fn(arg1: layer, arg2: c_int, arg3: f32, arg4: f32, arg5: f32)>§forward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>§backward_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: network_state)>§update_gpu: Option<unsafe extern "C" fn(arg1: layer, arg2: c_int, arg3: f32, arg4: f32, arg5: f32, arg6: f32)>§train: c_int§avgpool: c_int§batch_normalize: c_int§shortcut: c_int§batch: c_int§dynamic_minibatch: c_int§forced: c_int§flipped: c_int§inputs: c_int§outputs: c_int§mean_alpha: f32§nweights: c_int§nbiases: c_int§extra: c_int§truths: c_int§h: c_int§w: c_int§c: c_int§out_h: c_int§out_w: c_int§out_c: c_int§n: c_int§max_boxes: c_int§truth_size: c_int§groups: c_int§group_id: c_int§size: c_int§side: c_int§stride: c_int§stride_x: c_int§stride_y: c_int§dilation: c_int§antialiasing: c_int§maxpool_depth: c_int§maxpool_zero_nonmax: c_int§out_channels: c_int§reverse: f32§coordconv: c_int§flatten: c_int§spatial: c_int§pad: c_int§sqrt: c_int§flip: c_int§index: c_int§scale_wh: c_int§binary: c_int§xnor: c_int§peephole: c_int§use_bin_output: c_int§keep_delta_gpu: c_int§optimized_memory: c_int§steps: c_int§history_size: c_int§bottleneck: c_int§time_normalizer: f32§state_constrain: c_int§truth: c_int§smooth: f32§dot: f32§deform: c_int§grad_centr: c_int§sway: c_int§rotate: c_int§stretch: c_int§stretch_sway: c_int§angle: f32§jitter: f32§resize: f32§saturation: f32§exposure: f32§shift: f32§ratio: f32§learning_rate_scale: f32§clip: f32§focal_loss: c_int§classes_multipliers: *mut f32§label_smooth_eps: f32§noloss: c_int§softmax: c_int§classes: c_int§detection: c_int§embedding_layer_id: c_int§embedding_output: *mut f32§embedding_size: c_int§sim_thresh: f32§track_history_size: c_int§dets_for_track: c_int§dets_for_show: c_int§track_ciou_norm: f32§coords: c_int§background: c_int§rescore: c_int§objectness: c_int§does_cost: c_int§joint: c_int§noadjust: c_int§reorg: c_int§log: c_int§tanh: c_int§mask: *mut c_int§total: c_int§bflops: f32§adam: c_int§B1: f32§B2: f32§eps: f32§t: c_int§alpha: f32§beta: f32§kappa: f32§coord_scale: f32§object_scale: f32§noobject_scale: f32§mask_scale: f32§class_scale: f32§bias_match: c_int§random: f32§ignore_thresh: f32§truth_thresh: f32§iou_thresh: f32§thresh: f32§focus: f32§classfix: c_int§absolute: c_int§assisted_excitation: c_int§onlyforward: c_int§stopbackward: c_int§train_only_bn: c_int§dont_update: c_int§burnin_update: c_int§dontload: c_int§dontsave: c_int§dontloadscales: c_int§numload: c_int§temperature: f32§probability: f32§dropblock_size_rel: f32§dropblock_size_abs: c_int§dropblock: c_int§scale: f32§receptive_w: c_int§receptive_h: c_int§receptive_w_scale: c_int§receptive_h_scale: c_int§cweights: *mut c_char§indexes: *mut c_int§input_layers: *mut c_int§input_sizes: *mut c_int§layers_output: *mut *mut f32§layers_delta: *mut *mut f32§weights_type: WEIGHTS_TYPE_T§weights_normalization: WEIGHTS_NORMALIZATION_T§map: *mut c_int§counts: *mut c_int§sums: *mut *mut f32§rand: *mut f32§cost: *mut f32§labels: *mut c_int§class_ids: *mut c_int§contrastive_neg_max: c_int§cos_sim: *mut f32§exp_cos_sim: *mut f32§p_constrastive: *mut f32§contrast_p_gpu: *mut contrastive_params§state: *mut f32§prev_state: *mut f32§forgot_state: *mut f32§forgot_delta: *mut f32§state_delta: *mut f32§combine_cpu: *mut f32§combine_delta_cpu: *mut f32§concat: *mut f32§concat_delta: *mut f32§binary_weights: *mut f32§biases: *mut f32§bias_updates: *mut f32§scales: *mut f32§scale_updates: *mut f32§weights_ema: *mut f32§biases_ema: *mut f32§scales_ema: *mut f32§weights: *mut f32§weight_updates: *mut f32§scale_x_y: f32§objectness_smooth: c_int§new_coords: c_int§show_details: c_int§max_delta: f32§uc_normalizer: f32§iou_normalizer: f32§obj_normalizer: f32§cls_normalizer: f32§delta_normalizer: f32§iou_loss: IOU_LOSS§iou_thresh_kind: IOU_LOSS§nms_kind: NMS_KIND§beta_nms: f32§yolo_point: YOLO_POINT§align_bit_weights_gpu: *mut c_char§mean_arr_gpu: *mut f32§align_workspace_gpu: *mut f32§transposed_align_workspace_gpu: *mut f32§align_workspace_size: c_int§align_bit_weights: *mut c_char§mean_arr: *mut f32§align_bit_weights_size: c_int§lda_align: c_int§new_lda: c_int§bit_align: c_int§col_image: *mut f32§delta: *mut f32§output: *mut f32§activation_input: *mut f32§delta_pinned: c_int§output_pinned: c_int§loss: *mut f32§squared: *mut f32§norms: *mut f32§spatial_mean: *mut f32§mean: *mut f32§variance: *mut f32§mean_delta: *mut f32§variance_delta: *mut f32§rolling_mean: *mut f32§rolling_variance: *mut f32§x: *mut f32§x_norm: *mut f32§m: *mut f32§v: *mut f32§bias_m: *mut f32§bias_v: *mut f32§scale_m: *mut f32§scale_v: *mut f32§z_cpu: *mut f32§r_cpu: *mut f32§h_cpu: *mut f32§stored_h_cpu: *mut f32§prev_state_cpu: *mut f32§temp_cpu: *mut f32§temp2_cpu: *mut f32§temp3_cpu: *mut f32§dh_cpu: *mut f32§hh_cpu: *mut f32§prev_cell_cpu: *mut f32§cell_cpu: *mut f32§f_cpu: *mut f32§i_cpu: *mut f32§g_cpu: *mut f32§o_cpu: *mut f32§c_cpu: *mut f32§stored_c_cpu: *mut f32§dc_cpu: *mut f32§binary_input: *mut f32§bin_re_packed_input: *mut u32§t_bit_input: *mut c_char§input_layer: *mut layer§self_layer: *mut layer§output_layer: *mut layer§reset_layer: *mut layer§update_layer: *mut layer§state_layer: *mut layer§input_gate_layer: *mut layer§state_gate_layer: *mut layer§input_save_layer: *mut layer§state_save_layer: *mut layer§input_state_layer: *mut layer§state_state_layer: *mut layer§input_z_layer: *mut layer§state_z_layer: *mut layer§input_r_layer: *mut layer§state_r_layer: *mut layer§input_h_layer: *mut layer§state_h_layer: *mut layer§wz: *mut layer§uz: *mut layer§wr: *mut layer§ur: *mut layer§wh: *mut layer§uh: *mut layer§uo: *mut layer§wo: *mut layer§vo: *mut layer§uf: *mut layer§wf: *mut layer§vf: *mut layer§ui: *mut layer§wi: *mut layer§vi: *mut layer§ug: *mut layer§wg: *mut layer§softmax_tree: *mut tree§workspace_size: usize§indexes_gpu: *mut c_int§stream: c_int§wait_stream_id: c_int§z_gpu: *mut f32§r_gpu: *mut f32§h_gpu: *mut f32§stored_h_gpu: *mut f32§bottelneck_hi_gpu: *mut f32§bottelneck_delta_gpu: *mut f32§temp_gpu: *mut f32§temp2_gpu: *mut f32§temp3_gpu: *mut f32§dh_gpu: *mut f32§hh_gpu: *mut f32§prev_cell_gpu: *mut f32§prev_state_gpu: *mut f32§last_prev_state_gpu: *mut f32§last_prev_cell_gpu: *mut f32§cell_gpu: *mut f32§f_gpu: *mut f32§i_gpu: *mut f32§g_gpu: *mut f32§o_gpu: *mut f32§c_gpu: *mut f32§stored_c_gpu: *mut f32§dc_gpu: *mut f32§m_gpu: *mut f32§v_gpu: *mut f32§bias_m_gpu: *mut f32§scale_m_gpu: *mut f32§bias_v_gpu: *mut f32§scale_v_gpu: *mut f32§combine_gpu: *mut f32§combine_delta_gpu: *mut f32§forgot_state_gpu: *mut f32§forgot_delta_gpu: *mut f32§state_gpu: *mut f32§state_delta_gpu: *mut f32§gate_gpu: *mut f32§gate_delta_gpu: *mut f32§save_gpu: *mut f32§save_delta_gpu: *mut f32§concat_gpu: *mut f32§concat_delta_gpu: *mut f32§binary_input_gpu: *mut f32§binary_weights_gpu: *mut f32§bin_conv_shortcut_in_gpu: *mut f32§bin_conv_shortcut_out_gpu: *mut f32§mean_gpu: *mut f32§variance_gpu: *mut f32§m_cbn_avg_gpu: *mut f32§v_cbn_avg_gpu: *mut f32§rolling_mean_gpu: *mut f32§rolling_variance_gpu: *mut f32§variance_delta_gpu: *mut f32§mean_delta_gpu: *mut f32§col_image_gpu: *mut f32§x_gpu: *mut f32§x_norm_gpu: *mut f32§weights_gpu: *mut f32§weight_updates_gpu: *mut f32§weight_deform_gpu: *mut f32§weight_change_gpu: *mut f32§weights_gpu16: *mut f32§weight_updates_gpu16: *mut f32§biases_gpu: *mut f32§bias_updates_gpu: *mut f32§bias_change_gpu: *mut f32§scales_gpu: *mut f32§scale_updates_gpu: *mut f32§scale_change_gpu: *mut f32§input_antialiasing_gpu: *mut f32§output_gpu: *mut f32§output_avg_gpu: *mut f32§activation_input_gpu: *mut f32§loss_gpu: *mut f32§delta_gpu: *mut f32§cos_sim_gpu: *mut f32§rand_gpu: *mut f32§drop_blocks_scale: *mut f32§drop_blocks_scale_gpu: *mut f32§squared_gpu: *mut f32§norms_gpu: *mut f32§gt_gpu: *mut f32§a_avg_gpu: *mut f32§input_sizes_gpu: *mut c_int§layers_output_gpu: *mut *mut f32§layers_delta_gpu: *mut *mut f32§srcTensorDesc: *mut c_void§dstTensorDesc: *mut c_void§srcTensorDesc16: *mut c_void§dstTensorDesc16: *mut c_void§dsrcTensorDesc: *mut c_void§ddstTensorDesc: *mut c_void§dsrcTensorDesc16: *mut c_void§ddstTensorDesc16: *mut c_void§normTensorDesc: *mut c_void§normDstTensorDesc: *mut c_void§normDstTensorDescF16: *mut c_void§weightDesc: *mut c_void§weightDesc16: *mut c_void§dweightDesc: *mut c_void§dweightDesc16: *mut c_void§convDesc: *mut c_void§fw_algo: UNUSED_ENUM_TYPE§fw_algo16: UNUSED_ENUM_TYPE§bd_algo: UNUSED_ENUM_TYPE§bd_algo16: UNUSED_ENUM_TYPE§bf_algo: UNUSED_ENUM_TYPE§bf_algo16: UNUSED_ENUM_TYPE§poolingDesc: *mut c_voidTrait Implementations§
Auto Trait Implementations§
impl !Send for layer
impl !Sync for layer
impl Freeze for layer
impl RefUnwindSafe for layer
impl Unpin for layer
impl UnsafeUnpin for layer
impl UnwindSafe for layer
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more