darknet  v3
layer.c
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1 #include "layer.h"
2 #include "cuda.h"
3 
4 #include <stdlib.h>
5 
7 {
8  if(l.type == DROPOUT){
9  if(l.rand) free(l.rand);
10 #ifdef GPU
11  if(l.rand_gpu) cuda_free(l.rand_gpu);
12 #endif
13  return;
14  }
15  if(l.cweights) free(l.cweights);
16  if(l.indexes) free(l.indexes);
17  if(l.input_layers) free(l.input_layers);
18  if(l.input_sizes) free(l.input_sizes);
19  if(l.map) free(l.map);
20  if(l.rand) free(l.rand);
21  if(l.cost) free(l.cost);
22  if(l.state) free(l.state);
23  if(l.prev_state) free(l.prev_state);
24  if(l.forgot_state) free(l.forgot_state);
25  if(l.forgot_delta) free(l.forgot_delta);
26  if(l.state_delta) free(l.state_delta);
27  if(l.concat) free(l.concat);
28  if(l.concat_delta) free(l.concat_delta);
29  if(l.binary_weights) free(l.binary_weights);
30  if(l.biases) free(l.biases);
31  if(l.bias_updates) free(l.bias_updates);
32  if(l.scales) free(l.scales);
33  if(l.scale_updates) free(l.scale_updates);
34  if(l.weights) free(l.weights);
35  if(l.weight_updates) free(l.weight_updates);
36  if(l.delta) free(l.delta);
37  if(l.output) free(l.output);
38  if(l.squared) free(l.squared);
39  if(l.norms) free(l.norms);
40  if(l.spatial_mean) free(l.spatial_mean);
41  if(l.mean) free(l.mean);
42  if(l.variance) free(l.variance);
43  if(l.mean_delta) free(l.mean_delta);
44  if(l.variance_delta) free(l.variance_delta);
45  if(l.rolling_mean) free(l.rolling_mean);
46  if(l.rolling_variance) free(l.rolling_variance);
47  if(l.x) free(l.x);
48  if(l.x_norm) free(l.x_norm);
49  if(l.m) free(l.m);
50  if(l.v) free(l.v);
51  if(l.z_cpu) free(l.z_cpu);
52  if(l.r_cpu) free(l.r_cpu);
53  if(l.h_cpu) free(l.h_cpu);
54  if(l.binary_input) free(l.binary_input);
55 
56 #ifdef GPU
57  if(l.indexes_gpu) cuda_free((float *)l.indexes_gpu);
58 
59  if(l.z_gpu) cuda_free(l.z_gpu);
60  if(l.r_gpu) cuda_free(l.r_gpu);
61  if(l.h_gpu) cuda_free(l.h_gpu);
62  if(l.m_gpu) cuda_free(l.m_gpu);
63  if(l.v_gpu) cuda_free(l.v_gpu);
64  if(l.prev_state_gpu) cuda_free(l.prev_state_gpu);
65  if(l.forgot_state_gpu) cuda_free(l.forgot_state_gpu);
66  if(l.forgot_delta_gpu) cuda_free(l.forgot_delta_gpu);
67  if(l.state_gpu) cuda_free(l.state_gpu);
68  if(l.state_delta_gpu) cuda_free(l.state_delta_gpu);
69  if(l.gate_gpu) cuda_free(l.gate_gpu);
70  if(l.gate_delta_gpu) cuda_free(l.gate_delta_gpu);
71  if(l.save_gpu) cuda_free(l.save_gpu);
72  if(l.save_delta_gpu) cuda_free(l.save_delta_gpu);
73  if(l.concat_gpu) cuda_free(l.concat_gpu);
74  if(l.concat_delta_gpu) cuda_free(l.concat_delta_gpu);
75  if(l.binary_input_gpu) cuda_free(l.binary_input_gpu);
76  if(l.binary_weights_gpu) cuda_free(l.binary_weights_gpu);
77  if(l.mean_gpu) cuda_free(l.mean_gpu);
78  if(l.variance_gpu) cuda_free(l.variance_gpu);
79  if(l.rolling_mean_gpu) cuda_free(l.rolling_mean_gpu);
80  if(l.rolling_variance_gpu) cuda_free(l.rolling_variance_gpu);
81  if(l.variance_delta_gpu) cuda_free(l.variance_delta_gpu);
82  if(l.mean_delta_gpu) cuda_free(l.mean_delta_gpu);
83  if(l.x_gpu) cuda_free(l.x_gpu);
84  if(l.x_norm_gpu) cuda_free(l.x_norm_gpu);
85  if(l.weights_gpu) cuda_free(l.weights_gpu);
86  if(l.weight_updates_gpu) cuda_free(l.weight_updates_gpu);
87  if(l.biases_gpu) cuda_free(l.biases_gpu);
88  if(l.bias_updates_gpu) cuda_free(l.bias_updates_gpu);
89  if(l.scales_gpu) cuda_free(l.scales_gpu);
90  if(l.scale_updates_gpu) cuda_free(l.scale_updates_gpu);
91  if(l.output_gpu) cuda_free(l.output_gpu);
92  if(l.delta_gpu) cuda_free(l.delta_gpu);
93  if(l.rand_gpu) cuda_free(l.rand_gpu);
94  if(l.squared_gpu) cuda_free(l.squared_gpu);
95  if(l.norms_gpu) cuda_free(l.norms_gpu);
96 #endif
97 }
float * norms
Definition: darknet.h:249
float * scales
Definition: darknet.h:239
float * mean
Definition: darknet.h:252
float * biases
Definition: darknet.h:236
float * rand
Definition: darknet.h:221
float * weight_updates
Definition: darknet.h:243
int * map
Definition: darknet.h:218
float * forgot_state
Definition: darknet.h:225
float * rolling_variance
Definition: darknet.h:259
float * x
Definition: darknet.h:261
float * state_delta
Definition: darknet.h:227
float * binary_input
Definition: darknet.h:293
float * spatial_mean
Definition: darknet.h:251
void free_layer(layer l)
Definition: layer.c:6
float * variance_delta
Definition: darknet.h:256
float * v
Definition: darknet.h:265
float * h_cpu
Definition: darknet.h:275
float * z_cpu
Definition: darknet.h:273
float * state
Definition: darknet.h:223
int * input_layers
Definition: darknet.h:216
float * delta
Definition: darknet.h:245
float * x_norm
Definition: darknet.h:262
int * input_sizes
Definition: darknet.h:217
float * output
Definition: darknet.h:246
float * rolling_mean
Definition: darknet.h:258
float * r_cpu
Definition: darknet.h:274
float * mean_delta
Definition: darknet.h:255
float * bias_updates
Definition: darknet.h:237
float * forgot_delta
Definition: darknet.h:226
float * concat
Definition: darknet.h:231
int * indexes
Definition: darknet.h:215
LAYER_TYPE type
Definition: darknet.h:120
float * scale_updates
Definition: darknet.h:240
float * prev_state
Definition: darknet.h:224
float * binary_weights
Definition: darknet.h:234
float * squared
Definition: darknet.h:248
float * m
Definition: darknet.h:264
float * variance
Definition: darknet.h:253
float * concat_delta
Definition: darknet.h:232
char * cweights
Definition: darknet.h:214
float * cost
Definition: darknet.h:222
Definition: darknet.h:119
float * weights
Definition: darknet.h:242