mirror/darknet
1
0
Fork 0
mirror of https://github.com/pjreddie/darknet.git synced 2023-08-10 21:13:14 +03:00
Code Issues Projects Releases Wiki Activity

small parser change

Browse Source
This commit is contained in:
Joseph Redmon 2015-07-10 16:27:29 -07:00
parent 75db98db25
commit 2b4e07f13e
1 changed files with 1 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
src/parser.c
View File

@ -102,7 +102,6 @@ deconvolutional_layer parse_deconvolutional(list *options, size_params params)
#ifdef GPU
if(weights || biases) push_deconvolutional_layer(layer);
#endif
option_unused(options);
return layer;
}
@ -131,7 +130,6 @@ convolutional_layer parse_convolutional(list *options, size_params params)
#ifdef GPU
if(weights || biases) push_convolutional_layer(layer);
#endif
option_unused(options);
return layer;
}
@ -150,7 +148,6 @@ connected_layer parse_connected(list *options, size_params params)
#ifdef GPU
if(weights || biases) push_connected_layer(layer);
#endif
option_unused(options);
return layer;
}
@ -158,7 +155,6 @@ softmax_layer parse_softmax(list *options, size_params params)
{
int groups = option_find_int(options, "groups",1);
softmax_layer layer = make_softmax_layer(params.batch, params.inputs, groups);
option_unused(options);
return layer;
}
@ -171,7 +167,6 @@ detection_layer parse_detection(list *options, size_params params)
int objectness = option_find_int(options, "objectness", 0);
int background = option_find_int(options, "background", 0);
detection_layer layer = make_detection_layer(params.batch, params.inputs, classes, coords, joint, rescore, background, objectness);
option_unused(options);
return layer;
}
@ -180,7 +175,6 @@ cost_layer parse_cost(list *options, size_params params)
char *type_s = option_find_str(options, "type", "sse");
COST_TYPE type = get_cost_type(type_s);
cost_layer layer = make_cost_layer(params.batch, params.inputs, type);
option_unused(options);
return layer;
}
@ -201,7 +195,6 @@ crop_layer parse_crop(list *options, size_params params)
if(!(h && w && c)) error("Layer before crop layer must output image.");
crop_layer l = make_crop_layer(batch,h,w,c,crop_height,crop_width,flip, angle, saturation, exposure);
option_unused(options);
return l;
}
@ -218,7 +211,6 @@ maxpool_layer parse_maxpool(list *options, size_params params)
if(!(h && w && c)) error("Layer before maxpool layer must output image.");
maxpool_layer layer = make_maxpool_layer(batch,h,w,c,size,stride);
option_unused(options);
return layer;
}
@ -226,7 +218,6 @@ dropout_layer parse_dropout(list *options, size_params params)
{
float probability = option_find_float(options, "probability", .5);
dropout_layer layer = make_dropout_layer(params.batch, params.inputs, probability);
option_unused(options);
return layer;
}
@ -237,7 +228,6 @@ layer parse_normalization(list *options, size_params params)
float kappa = option_find_float(options, "kappa", 1);
int size = option_find_int(options, "size", 5);
layer l = make_normalization_layer(params.batch, params.w, params.h, params.c, size, alpha, beta, kappa);
option_unused(options);
return l;
}
@ -278,7 +268,6 @@ route_layer parse_route(list *options, size_params params, network net)
}
}
option_unused(options);
return layer;
}
@ -298,7 +287,6 @@ void parse_net_options(list *options, network *net)
net->c = option_find_int_quiet(options, "channels",0);
net->inputs = option_find_int_quiet(options, "inputs", net->h * net->w * net->c);
if(!net->inputs && !(net->h && net->w && net->c)) error("No input parameters supplied");
option_unused(options);
}
network parse_network_cfg(char *filename)
@ -359,6 +347,7 @@ network parse_network_cfg(char *filename)
fprintf(stderr, "Type not recognized: %s\n", s->type);
}
l.dontload = option_find_int_quiet(options, "dontload", 0);
option_unused(options);
net.layers[count] = l;
free_section(s);
n = n->next;