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normalization layer
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21
src/parser.c
21
src/parser.c
@ -7,6 +7,7 @@
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#include "crop_layer.h"
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#include "cost_layer.h"
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#include "convolutional_layer.h"
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#include "normalization_layer.h"
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#include "deconvolutional_layer.h"
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#include "connected_layer.h"
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#include "maxpool_layer.h"
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@ -30,6 +31,7 @@ int is_connected(section *s);
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int is_maxpool(section *s);
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int is_dropout(section *s);
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int is_softmax(section *s);
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int is_normalization(section *s);
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int is_crop(section *s);
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int is_cost(section *s);
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int is_detection(section *s);
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@ -228,6 +230,17 @@ dropout_layer parse_dropout(list *options, size_params params)
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return layer;
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}
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layer parse_normalization(list *options, size_params params)
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{
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float alpha = option_find_float(options, "alpha", .0001);
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float beta = option_find_float(options, "beta" , .75);
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float kappa = option_find_float(options, "kappa", 1);
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int size = option_find_int(options, "size", 5);
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layer l = make_normalization_layer(params.batch, params.w, params.h, params.c, size, alpha, beta, kappa);
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option_unused(options);
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return l;
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}
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route_layer parse_route(list *options, size_params params, network net)
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{
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char *l = option_find(options, "layers");
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@ -328,6 +341,8 @@ network parse_network_cfg(char *filename)
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l = parse_detection(options, params);
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}else if(is_softmax(s)){
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l = parse_softmax(options, params);
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}else if(is_normalization(s)){
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l = parse_normalization(options, params);
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}else if(is_maxpool(s)){
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l = parse_maxpool(options, params);
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}else if(is_route(s)){
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@ -403,6 +418,12 @@ int is_dropout(section *s)
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return (strcmp(s->type, "[dropout]")==0);
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}
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int is_normalization(section *s)
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{
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return (strcmp(s->type, "[lrn]")==0
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|| strcmp(s->type, "[normalization]")==0);
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}
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int is_softmax(section *s)
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{
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return (strcmp(s->type, "[soft]")==0
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