From 168af40fe9a3cc81c6ee16b3e81f154780c36bdb Mon Sep 17 00:00:00 2001
From: Scheaven <xuepengqiang>
Date: 星期四, 03 六月 2021 15:03:27 +0800
Subject: [PATCH] up new v4
---
lib/detecter_tools/darknet/layer.h | 676 ++++++++++++++++++++++++++++----------------------------
1 files changed, 338 insertions(+), 338 deletions(-)
diff --git a/lib/detecter_tools/darknet/layer.h b/lib/detecter_tools/darknet/layer.h
index 0b23334..e92d3b4 100644
--- a/lib/detecter_tools/darknet/layer.h
+++ b/lib/detecter_tools/darknet/layer.h
@@ -1,338 +1,338 @@
-#ifndef BASE_LAYER_H
-#define BASE_LAYER_H
-
-#include "activations.h"
-#include "stddef.h"
-#include "tree.h"
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-//struct network_state;
-
-//struct layer;
-//typedef struct layer layer;
-
-//typedef enum {
-// CONVOLUTIONAL,
-// DECONVOLUTIONAL,
-// CONNECTED,
-// MAXPOOL,
-// SOFTMAX,
-// DETECTION,
-// DROPOUT,
-// CROP,
-// ROUTE,
-// COST,
-// NORMALIZATION,
-// AVGPOOL,
-// LOCAL,
-// SHORTCUT,
-// ACTIVE,
-// RNN,
-// GRU,
-// CRNN,
-// BATCHNORM,
-// NETWORK,
-// XNOR,
-// REGION,
-// YOLO,
-// REORG,
-// UPSAMPLE,
-// REORG_OLD,
-// BLANK
-//} LAYER_TYPE;
-
-//typedef enum{
-// 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;
- COST_TYPE cost_type;
- void (*forward) (struct layer, struct network_state);
- void (*backward) (struct layer, struct network_state);
- void (*update) (struct layer, int, float, float, float);
- void (*forward_gpu) (struct layer, struct network_state);
- void (*backward_gpu) (struct layer, struct network_state);
- void (*update_gpu) (struct layer, int, float, float, float);
- int batch_normalize;
- int shortcut;
- int batch;
- int forced;
- int flipped;
- int inputs;
- int outputs;
- int truths;
- int h,w,c;
- int out_h, out_w, out_c;
- int n;
- int max_boxes;
- int groups;
- int size;
- int side;
- int stride;
- int reverse;
- int spatial;
- int pad;
- int sqrt;
- int flip;
- int index;
- int binary;
- int xnor;
- int use_bin_output;
- int steps;
- int hidden;
- float dot;
- float angle;
- float jitter;
- float saturation;
- float exposure;
- float shift;
- float ratio;
- float learning_rate_scale;
- int focal_loss;
- int noloss;
- int softmax;
- int classes;
- int coords;
- int background;
- int rescore;
- int objectness;
- int does_cost;
- int joint;
- int noadjust;
- int reorg;
- int log;
- int tanh;
- int *mask;
- int total;
- float bflops;
-
- int adam;
- float B1;
- float B2;
- float eps;
-
- int t;
- float *m;
- float *v;
- float * bias_m;
- float * bias_v;
- float * scale_m;
- float * scale_v;
-
- tree *softmax_tree;
- int *map;
-
- float alpha;
- float beta;
- float kappa;
-
- 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;
-
- int onlyforward;
- int stopbackward;
- int dontload;
- int dontloadscales;
-
- float temperature;
- float probability;
- float scale;
-
- int *indexes;
- float *rand;
- float *cost;
- char *cweights;
- float *state;
- float *prev_state;
- float *forgot_state;
- float *forgot_delta;
- float *state_delta;
-
- float *concat;
- float *concat_delta;
-
- float *binary_weights;
-
- float *biases;
- float *bias_updates;
-
- float *scales;
- float *scale_updates;
-
- float *weights;
- float *weight_updates;
-
- char *align_bit_weights_gpu;
- float *mean_arr_gpu;
- float *align_workspace_gpu;
- float *transposed_align_workspace_gpu;
- int align_workspace_size;
-
- char *align_bit_weights;
- float *mean_arr;
- int align_bit_weights_size;
- int lda_align;
- int new_lda;
- int bit_align;
-
- float *col_image;
- int * input_layers;
- int * input_sizes;
- float * delta;
- float * output;
- float * loss;
- float * squared;
- float * norms;
-
- float * spatial_mean;
- float * mean;
- float * variance;
-
- float * mean_delta;
- float * variance_delta;
-
- float * rolling_mean;
- float * rolling_variance;
-
- float * x;
- float * x_norm;
-
- struct layer *input_layer;
- struct layer *self_layer;
- struct layer *output_layer;
-
- struct layer *input_gate_layer;
- struct layer *state_gate_layer;
- struct layer *input_save_layer;
- struct layer *state_save_layer;
- struct layer *input_state_layer;
- struct layer *state_state_layer;
-
- struct layer *input_z_layer;
- struct layer *state_z_layer;
-
- struct layer *input_r_layer;
- struct layer *state_r_layer;
-
- struct layer *input_h_layer;
- struct layer *state_h_layer;
-
- float *z_cpu;
- float *r_cpu;
- float *h_cpu;
-
- float *binary_input;
-
- size_t workspace_size;
-
-#ifdef GPU
- float *z_gpu;
- float *r_gpu;
- float *h_gpu;
-
- int *indexes_gpu;
- float * prev_state_gpu;
- float * forgot_state_gpu;
- float * forgot_delta_gpu;
- float * state_gpu;
- float * state_delta_gpu;
- float * gate_gpu;
- float * gate_delta_gpu;
- float * save_gpu;
- float * save_delta_gpu;
- float * concat_gpu;
- float * concat_delta_gpu;
-
- // adam
- float *m_gpu;
- float *v_gpu;
- float *bias_m_gpu;
- float *scale_m_gpu;
- float *bias_v_gpu;
- float *scale_v_gpu;
-
- float *binary_input_gpu;
- float *binary_weights_gpu;
-
- float * mean_gpu;
- float * variance_gpu;
-
- float * rolling_mean_gpu;
- float * rolling_variance_gpu;
-
- float * variance_delta_gpu;
- float * mean_delta_gpu;
-
- float * col_image_gpu;
-
- float * x_gpu;
- float * x_norm_gpu;
- float * weights_gpu;
- float * weight_updates_gpu;
-
- float * weights_gpu16;
- float * weight_updates_gpu16;
-
- float * biases_gpu;
- float * bias_updates_gpu;
-
- float * scales_gpu;
- float * scale_updates_gpu;
-
- float * output_gpu;
- float * loss_gpu;
- float * delta_gpu;
- float * rand_gpu;
- float * squared_gpu;
- float * norms_gpu;
- #ifdef CUDNN
- cudnnTensorDescriptor_t srcTensorDesc, dstTensorDesc;
- cudnnTensorDescriptor_t srcTensorDesc16, dstTensorDesc16;
- cudnnTensorDescriptor_t dsrcTensorDesc, ddstTensorDesc;
- cudnnTensorDescriptor_t dsrcTensorDesc16, ddstTensorDesc16;
- cudnnTensorDescriptor_t normTensorDesc, normDstTensorDesc, normDstTensorDescF16;
- cudnnFilterDescriptor_t weightDesc, weightDesc16;
- cudnnFilterDescriptor_t dweightDesc, dweightDesc16;
- cudnnConvolutionDescriptor_t convDesc;
- cudnnConvolutionFwdAlgo_t fw_algo, fw_algo16;
- cudnnConvolutionBwdDataAlgo_t bd_algo, bd_algo16;
- cudnnConvolutionBwdFilterAlgo_t bf_algo, bf_algo16;
- cudnnPoolingDescriptor_t poolingDesc;
- #endif // CUDNN
-#endif // GPU
-};
-*/
-//void free_layer(layer);
-
-#ifdef __cplusplus
-}
-#endif
-#endif
+#ifndef BASE_LAYER_H
+#define BASE_LAYER_H
+
+#include "activations.h"
+#include "stddef.h"
+#include "tree.h"
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+//struct network_state;
+
+//struct layer;
+//typedef struct layer layer;
+
+//typedef enum {
+// CONVOLUTIONAL,
+// DECONVOLUTIONAL,
+// CONNECTED,
+// MAXPOOL,
+// SOFTMAX,
+// DETECTION,
+// DROPOUT,
+// CROP,
+// ROUTE,
+// COST,
+// NORMALIZATION,
+// AVGPOOL,
+// LOCAL,
+// SHORTCUT,
+// ACTIVE,
+// RNN,
+// GRU,
+// CRNN,
+// BATCHNORM,
+// NETWORK,
+// XNOR,
+// REGION,
+// YOLO,
+// REORG,
+// UPSAMPLE,
+// REORG_OLD,
+// BLANK
+//} LAYER_TYPE;
+
+//typedef enum{
+// 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;
+ COST_TYPE cost_type;
+ void (*forward) (struct layer, struct network_state);
+ void (*backward) (struct layer, struct network_state);
+ void (*update) (struct layer, int, float, float, float);
+ void (*forward_gpu) (struct layer, struct network_state);
+ void (*backward_gpu) (struct layer, struct network_state);
+ void (*update_gpu) (struct layer, int, float, float, float);
+ int batch_normalize;
+ int shortcut;
+ int batch;
+ int forced;
+ int flipped;
+ int inputs;
+ int outputs;
+ int truths;
+ int h,w,c;
+ int out_h, out_w, out_c;
+ int n;
+ int max_boxes;
+ int groups;
+ int size;
+ int side;
+ int stride;
+ int reverse;
+ int spatial;
+ int pad;
+ int sqrt;
+ int flip;
+ int index;
+ int binary;
+ int xnor;
+ int use_bin_output;
+ int steps;
+ int hidden;
+ float dot;
+ float angle;
+ float jitter;
+ float saturation;
+ float exposure;
+ float shift;
+ float ratio;
+ float learning_rate_scale;
+ int focal_loss;
+ int noloss;
+ int softmax;
+ int classes;
+ int coords;
+ int background;
+ int rescore;
+ int objectness;
+ int does_cost;
+ int joint;
+ int noadjust;
+ int reorg;
+ int log;
+ int tanh;
+ int *mask;
+ int total;
+ float bflops;
+
+ int adam;
+ float B1;
+ float B2;
+ float eps;
+
+ int t;
+ float *m;
+ float *v;
+ float * bias_m;
+ float * bias_v;
+ float * scale_m;
+ float * scale_v;
+
+ tree *softmax_tree;
+ int *map;
+
+ float alpha;
+ float beta;
+ float kappa;
+
+ 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;
+
+ int onlyforward;
+ int stopbackward;
+ int dontload;
+ int dontloadscales;
+
+ float temperature;
+ float probability;
+ float scale;
+
+ int *indexes;
+ float *rand;
+ float *cost;
+ char *cweights;
+ float *state;
+ float *prev_state;
+ float *forgot_state;
+ float *forgot_delta;
+ float *state_delta;
+
+ float *concat;
+ float *concat_delta;
+
+ float *binary_weights;
+
+ float *biases;
+ float *bias_updates;
+
+ float *scales;
+ float *scale_updates;
+
+ float *weights;
+ float *weight_updates;
+
+ char *align_bit_weights_gpu;
+ float *mean_arr_gpu;
+ float *align_workspace_gpu;
+ float *transposed_align_workspace_gpu;
+ int align_workspace_size;
+
+ char *align_bit_weights;
+ float *mean_arr;
+ int align_bit_weights_size;
+ int lda_align;
+ int new_lda;
+ int bit_align;
+
+ float *col_image;
+ int * input_layers;
+ int * input_sizes;
+ float * delta;
+ float * output;
+ float * loss;
+ float * squared;
+ float * norms;
+
+ float * spatial_mean;
+ float * mean;
+ float * variance;
+
+ float * mean_delta;
+ float * variance_delta;
+
+ float * rolling_mean;
+ float * rolling_variance;
+
+ float * x;
+ float * x_norm;
+
+ struct layer *input_layer;
+ struct layer *self_layer;
+ struct layer *output_layer;
+
+ struct layer *input_gate_layer;
+ struct layer *state_gate_layer;
+ struct layer *input_save_layer;
+ struct layer *state_save_layer;
+ struct layer *input_state_layer;
+ struct layer *state_state_layer;
+
+ struct layer *input_z_layer;
+ struct layer *state_z_layer;
+
+ struct layer *input_r_layer;
+ struct layer *state_r_layer;
+
+ struct layer *input_h_layer;
+ struct layer *state_h_layer;
+
+ float *z_cpu;
+ float *r_cpu;
+ float *h_cpu;
+
+ float *binary_input;
+
+ size_t workspace_size;
+
+#ifdef GPU
+ float *z_gpu;
+ float *r_gpu;
+ float *h_gpu;
+
+ int *indexes_gpu;
+ float * prev_state_gpu;
+ float * forgot_state_gpu;
+ float * forgot_delta_gpu;
+ float * state_gpu;
+ float * state_delta_gpu;
+ float * gate_gpu;
+ float * gate_delta_gpu;
+ float * save_gpu;
+ float * save_delta_gpu;
+ float * concat_gpu;
+ float * concat_delta_gpu;
+
+ // adam
+ float *m_gpu;
+ float *v_gpu;
+ float *bias_m_gpu;
+ float *scale_m_gpu;
+ float *bias_v_gpu;
+ float *scale_v_gpu;
+
+ float *binary_input_gpu;
+ float *binary_weights_gpu;
+
+ float * mean_gpu;
+ float * variance_gpu;
+
+ float * rolling_mean_gpu;
+ float * rolling_variance_gpu;
+
+ float * variance_delta_gpu;
+ float * mean_delta_gpu;
+
+ float * col_image_gpu;
+
+ float * x_gpu;
+ float * x_norm_gpu;
+ float * weights_gpu;
+ float * weight_updates_gpu;
+
+ float * weights_gpu16;
+ float * weight_updates_gpu16;
+
+ float * biases_gpu;
+ float * bias_updates_gpu;
+
+ float * scales_gpu;
+ float * scale_updates_gpu;
+
+ float * output_gpu;
+ float * loss_gpu;
+ float * delta_gpu;
+ float * rand_gpu;
+ float * squared_gpu;
+ float * norms_gpu;
+ #ifdef CUDNN
+ cudnnTensorDescriptor_t srcTensorDesc, dstTensorDesc;
+ cudnnTensorDescriptor_t srcTensorDesc16, dstTensorDesc16;
+ cudnnTensorDescriptor_t dsrcTensorDesc, ddstTensorDesc;
+ cudnnTensorDescriptor_t dsrcTensorDesc16, ddstTensorDesc16;
+ cudnnTensorDescriptor_t normTensorDesc, normDstTensorDesc, normDstTensorDescF16;
+ cudnnFilterDescriptor_t weightDesc, weightDesc16;
+ cudnnFilterDescriptor_t dweightDesc, dweightDesc16;
+ cudnnConvolutionDescriptor_t convDesc;
+ cudnnConvolutionFwdAlgo_t fw_algo, fw_algo16;
+ cudnnConvolutionBwdDataAlgo_t bd_algo, bd_algo16;
+ cudnnConvolutionBwdFilterAlgo_t bf_algo, bf_algo16;
+ cudnnPoolingDescriptor_t poolingDesc;
+ #endif // CUDNN
+#endif // GPU
+};
+*/
+//void free_layer(layer);
+
+#ifdef __cplusplus
+}
+#endif
+#endif
--
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