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https://github.com/pjreddie/darknet.git
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small parser change
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parent
75db98db25
commit
2b4e07f13e
13
src/parser.c
13
src/parser.c
@ -102,7 +102,6 @@ deconvolutional_layer parse_deconvolutional(list *options, size_params params)
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#ifdef GPU
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#ifdef GPU
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if(weights || biases) push_deconvolutional_layer(layer);
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if(weights || biases) push_deconvolutional_layer(layer);
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#endif
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#endif
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -131,7 +130,6 @@ convolutional_layer parse_convolutional(list *options, size_params params)
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#ifdef GPU
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#ifdef GPU
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if(weights || biases) push_convolutional_layer(layer);
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if(weights || biases) push_convolutional_layer(layer);
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#endif
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#endif
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -150,7 +148,6 @@ connected_layer parse_connected(list *options, size_params params)
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#ifdef GPU
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#ifdef GPU
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if(weights || biases) push_connected_layer(layer);
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if(weights || biases) push_connected_layer(layer);
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#endif
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#endif
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -158,7 +155,6 @@ softmax_layer parse_softmax(list *options, size_params params)
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{
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{
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int groups = option_find_int(options, "groups",1);
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int groups = option_find_int(options, "groups",1);
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softmax_layer layer = make_softmax_layer(params.batch, params.inputs, groups);
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softmax_layer layer = make_softmax_layer(params.batch, params.inputs, groups);
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -171,7 +167,6 @@ detection_layer parse_detection(list *options, size_params params)
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int objectness = option_find_int(options, "objectness", 0);
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int objectness = option_find_int(options, "objectness", 0);
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int background = option_find_int(options, "background", 0);
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int background = option_find_int(options, "background", 0);
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detection_layer layer = make_detection_layer(params.batch, params.inputs, classes, coords, joint, rescore, background, objectness);
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detection_layer layer = make_detection_layer(params.batch, params.inputs, classes, coords, joint, rescore, background, objectness);
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -180,7 +175,6 @@ cost_layer parse_cost(list *options, size_params params)
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char *type_s = option_find_str(options, "type", "sse");
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char *type_s = option_find_str(options, "type", "sse");
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COST_TYPE type = get_cost_type(type_s);
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COST_TYPE type = get_cost_type(type_s);
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cost_layer layer = make_cost_layer(params.batch, params.inputs, type);
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cost_layer layer = make_cost_layer(params.batch, params.inputs, type);
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -201,7 +195,6 @@ crop_layer parse_crop(list *options, size_params params)
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if(!(h && w && c)) error("Layer before crop layer must output image.");
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if(!(h && w && c)) error("Layer before crop layer must output image.");
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crop_layer l = make_crop_layer(batch,h,w,c,crop_height,crop_width,flip, angle, saturation, exposure);
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crop_layer l = make_crop_layer(batch,h,w,c,crop_height,crop_width,flip, angle, saturation, exposure);
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option_unused(options);
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return l;
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return l;
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}
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}
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@ -218,7 +211,6 @@ maxpool_layer parse_maxpool(list *options, size_params params)
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if(!(h && w && c)) error("Layer before maxpool layer must output image.");
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if(!(h && w && c)) error("Layer before maxpool layer must output image.");
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maxpool_layer layer = make_maxpool_layer(batch,h,w,c,size,stride);
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maxpool_layer layer = make_maxpool_layer(batch,h,w,c,size,stride);
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -226,7 +218,6 @@ dropout_layer parse_dropout(list *options, size_params params)
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{
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{
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float probability = option_find_float(options, "probability", .5);
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float probability = option_find_float(options, "probability", .5);
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dropout_layer layer = make_dropout_layer(params.batch, params.inputs, probability);
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dropout_layer layer = make_dropout_layer(params.batch, params.inputs, probability);
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -237,7 +228,6 @@ layer parse_normalization(list *options, size_params params)
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float kappa = option_find_float(options, "kappa", 1);
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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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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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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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return l;
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}
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}
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@ -278,7 +268,6 @@ route_layer parse_route(list *options, size_params params, network net)
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}
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}
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}
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}
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option_unused(options);
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return layer;
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return layer;
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}
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}
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@ -298,7 +287,6 @@ void parse_net_options(list *options, network *net)
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net->c = option_find_int_quiet(options, "channels",0);
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net->c = option_find_int_quiet(options, "channels",0);
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net->inputs = option_find_int_quiet(options, "inputs", net->h * net->w * net->c);
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net->inputs = option_find_int_quiet(options, "inputs", net->h * net->w * net->c);
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if(!net->inputs && !(net->h && net->w && net->c)) error("No input parameters supplied");
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if(!net->inputs && !(net->h && net->w && net->c)) error("No input parameters supplied");
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option_unused(options);
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}
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}
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network parse_network_cfg(char *filename)
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network parse_network_cfg(char *filename)
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@ -359,6 +347,7 @@ network parse_network_cfg(char *filename)
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fprintf(stderr, "Type not recognized: %s\n", s->type);
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fprintf(stderr, "Type not recognized: %s\n", s->type);
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}
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}
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l.dontload = option_find_int_quiet(options, "dontload", 0);
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l.dontload = option_find_int_quiet(options, "dontload", 0);
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option_unused(options);
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net.layers[count] = l;
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net.layers[count] = l;
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free_section(s);
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free_section(s);
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n = n->next;
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n = n->next;
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