| | |
| | | NETWORK, |
| | | XNOR, |
| | | REGION, |
| | | YOLO, |
| | | REORG, |
| | | UPSAMPLE, |
| | | REORG_OLD, |
| | | BLANK |
| | | } LAYER_TYPE; |
| | |
| | | SSE, MASKED, SMOOTH |
| | | } COST_TYPE; |
| | | |
| | | typedef struct { |
| | | int batch; |
| | | float learning_rate; |
| | | float momentum; |
| | | float decay; |
| | | int adam; |
| | | float B1; |
| | | float B2; |
| | | float eps; |
| | | int t; |
| | | } update_args; |
| | | |
| | | struct layer{ |
| | | LAYER_TYPE type; |
| | | ACTIVATION activation; |
| | |
| | | int out_h, out_w, out_c; |
| | | int n; |
| | | int max_boxes; |
| | | int small_object; |
| | | int groups; |
| | | int size; |
| | | int side; |
| | |
| | | float exposure; |
| | | float shift; |
| | | float ratio; |
| | | int focal_loss; |
| | | int softmax; |
| | | int classes; |
| | | int coords; |
| | |
| | | int noadjust; |
| | | int reorg; |
| | | int log; |
| | | int tanh; |
| | | int *mask; |
| | | int total; |
| | | |
| | | int adam; |
| | | float B1; |
| | |
| | | float coord_scale; |
| | | float object_scale; |
| | | float noobject_scale; |
| | | float mask_scale; |
| | | float class_scale; |
| | | int bias_match; |
| | | int random; |
| | | float ignore_thresh; |
| | | float truth_thresh; |
| | | float thresh; |
| | | float focus; |
| | | int classfix; |
| | | int absolute; |
| | | |
| | |
| | | #ifdef CUDNN |
| | | cudnnTensorDescriptor_t srcTensorDesc, dstTensorDesc; |
| | | cudnnTensorDescriptor_t dsrcTensorDesc, ddstTensorDesc; |
| | | cudnnTensorDescriptor_t normTensorDesc, normDstTensorDesc; |
| | | cudnnFilterDescriptor_t weightDesc; |
| | | cudnnFilterDescriptor_t dweightDesc; |
| | | cudnnConvolutionDescriptor_t convDesc; |