shut down the compiler...

svn path=/trunk/externals/ann/; revision=3028

1 files changed, 62 insertions, 62 deletions

diff --git a/src/ann_mlp.c b/src/ann_mlp.c
index e83aea3..e01b203 100755
--- a/src/ann_mlp.c
+++ b/src/ann_mlp.c
@@ -30,8 +30,8 @@ typedef struct _ann_mlp {
 	int mode; // 0 = training, 1 = running

 	t_symbol *filename; // name of the file where this ann is saved

 	t_symbol *filenametrain; // name of the file with training data

-	float desired_error;
-	unsigned int max_iterations;
+	float desired_error;

+	unsigned int max_iterations;

 	unsigned int iterations_between_reports;

 	t_outlet *l_out, *f_out;

 } t_ann_mlp;

@@ -49,48 +49,48 @@ void help(t_ann_mlp *x)
 }

 

 void createFann(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv)

-{
-	unsigned int num_input = 2;
-	unsigned int num_output = 1;
-	unsigned int num_layers = 3;
-	unsigned int num_neurons_hidden = 3;
-	float connection_rate = 1;
-	float learning_rate = (float)0.7;
-
-	if (argc>0)
-		num_input = atom_getint(argv++);
-
-	if (argc>1)
-		num_output = atom_getint(argv++);
-
-	if (argc>2)
-		num_layers = atom_getint(argv++);
-
-	if (argc>3)
-		num_neurons_hidden = atom_getint(argv++);
-
-	if (argc>4)
-		connection_rate = atom_getfloat(argv++);
-
-	if (argc>5)
-		learning_rate = atom_getfloat(argv++);
-
-	if (num_input>=MAXINPUT)
-	{
-		error("too many inputs, maximum allowed is MAXINPUT");
-		return;
-	}
-
-	if (num_output>=MAXOUTPUT)
-	{
-		error("too many outputs, maximum allowed is MAXOUTPUT");
-		return;
-	}
-
-	x->ann	= fann_create(connection_rate, learning_rate, num_layers,
-		num_input, num_neurons_hidden, num_output);
-
-	fann_set_activation_function_hidden(x->ann, FANN_SIGMOID_SYMMETRIC);
+{

+	unsigned int num_input = 2;

+	unsigned int num_output = 1;

+	unsigned int num_layers = 3;

+	unsigned int num_neurons_hidden = 3;

+	float connection_rate = 1;

+	float learning_rate = (float)0.7;

+

+	if (argc>0)

+		num_input = atom_getint(argv++);

+

+	if (argc>1)

+		num_output = atom_getint(argv++);

+

+	if (argc>2)

+		num_layers = atom_getint(argv++);

+

+	if (argc>3)

+		num_neurons_hidden = atom_getint(argv++);

+

+	if (argc>4)

+		connection_rate = atom_getfloat(argv++);

+

+	if (argc>5)

+		learning_rate = atom_getfloat(argv++);

+

+	if (num_input>=MAXINPUT)

+	{

+		error("too many inputs, maximum allowed is MAXINPUT");

+		return;

+	}

+

+	if (num_output>=MAXOUTPUT)

+	{

+		error("too many outputs, maximum allowed is MAXOUTPUT");

+		return;

+	}

+

+	x->ann	= fann_create(connection_rate, learning_rate, num_layers,

+		num_input, num_neurons_hidden, num_output);

+

+	fann_set_activation_function_hidden(x->ann, FANN_SIGMOID_SYMMETRIC);

 	fann_set_activation_function_output(x->ann, FANN_SIGMOID_SYMMETRIC);

 

 	if (x->ann == 0)

@@ -150,25 +150,25 @@ void set_mode(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv)
 

 

 void train_on_file(t_ann_mlp *x, t_symbol *sl, int argc, t_atom *argv)

-{
+{

 	if (x->ann == 0)

 	{

 		error("ann not initialized");

 		return;

-	}
-
-	if (argc<1)
-	{
-		error("you must specify the filename with training data");
-		return;
-	} else
-	{
-		x->filenametrain = atom_gensym(argv);
-	}

-
-	//post("nn: starting training on file %s, please be patient and wait for my next message (it could take severeal minutes to complete training)", x->filenametrain->s_name);
-
-	fann_train_on_file(x->ann, x->filenametrain->s_name, x->max_iterations,
+	}

+

+	if (argc<1)

+	{

+		error("you must specify the filename with training data");

+		return;

+	} else

+	{

+		x->filenametrain = atom_gensym(argv);

+	}

+

+	//post("nn: starting training on file %s, please be patient and wait for my next message (it could take severeal minutes to complete training)", x->filenametrain->s_name);

+

+	fann_train_on_file(x->ann, x->filenametrain->s_name, x->max_iterations,

 		x->iterations_between_reports, x->desired_error);

 	

 	post("nn: finished training on file %s", x->filenametrain->s_name);

@@ -496,8 +496,8 @@ void *nn_new(t_symbol *s, int argc, t_atom *argv)
 	x->l_out = outlet_new(&x->x_obj, &s_list);

 	x->f_out = outlet_new(&x->x_obj, &s_float);

 

-	x->desired_error = (float)0.001;
-	x->max_iterations = 500000;
+	x->desired_error = (float)0.001;

+	x->max_iterations = 500000;

 	x->iterations_between_reports = 1000;

 	x->mode=RUN;

 

@@ -562,4 +562,4 @@ void ann_mlp_setup(void) {
 	class_sethelpsymbol(ann_mlp_class, gensym("help-ann_mlp"));

 

 

-}
\ No newline at end of file
+}