Closed cagdasbas closed 8 years ago
Hi,
I run into trouble of running Main_Char_LSTM.m. I've fixed the issue with these changes: train_lstm.m line 94-97
[ net{1},res.Gate,opts ] = opts.parameters.learning_method( net{1},res.Gate,opts); [ net{2},res.Input,opts ] = opts.parameters.learning_method (net{2},res.Input,opts ); [ net{3},res.Cell,opts ] = opts.parameters.learning_method( net{3},res.Cell,opts ); [ net{4},res.Fit,opts ] = opts.parameters.learning_method( net{4},res.Fit,opts ); changed to: [ net{1},res.Gate,opts ] = feval(opts.parameters.learning_method,net{1},res.Gate,opts); [ net{2},res.Input,opts ] = feval(opts.parameters.learning_method,net{2},res.Input,opts ); [ net{3},res.Cell,opts ] = feval(opts.parameters.learning_method, net{3},res.Cell,opts ); [ net{4},res.Fit,opts ] = feval(opts.parameters.learning_method,net{4},res.Fit,opts );
[ net{1},res.Gate,opts ] = opts.parameters.learning_method( net{1},res.Gate,opts); [ net{2},res.Input,opts ] = opts.parameters.learning_method (net{2},res.Input,opts ); [ net{3},res.Cell,opts ] = opts.parameters.learning_method( net{3},res.Cell,opts ); [ net{4},res.Fit,opts ] = opts.parameters.learning_method( net{4},res.Fit,opts );
[ net{1},res.Gate,opts ] = feval(opts.parameters.learning_method,net{1},res.Gate,opts); [ net{2},res.Input,opts ] = feval(opts.parameters.learning_method,net{2},res.Input,opts ); [ net{3},res.Cell,opts ] = feval(opts.parameters.learning_method, net{3},res.Cell,opts ); [ net{4},res.Fit,opts ] = feval(opts.parameters.learning_method,net{4},res.Fit,opts );
Thank you! We have incorporated this fix.
Hi,
I run into trouble of running Main_Char_LSTM.m. I've fixed the issue with these changes: train_lstm.m line 94-97
[ net{1},res.Gate,opts ] = opts.parameters.learning_method( net{1},res.Gate,opts); [ net{2},res.Input,opts ] = opts.parameters.learning_method (net{2},res.Input,opts ); [ net{3},res.Cell,opts ] = opts.parameters.learning_method( net{3},res.Cell,opts ); [ net{4},res.Fit,opts ] = opts.parameters.learning_method( net{4},res.Fit,opts );
changed to:[ net{1},res.Gate,opts ] = feval(opts.parameters.learning_method,net{1},res.Gate,opts); [ net{2},res.Input,opts ] = feval(opts.parameters.learning_method,net{2},res.Input,opts ); [ net{3},res.Cell,opts ] = feval(opts.parameters.learning_method, net{3},res.Cell,opts ); [ net{4},res.Fit,opts ] = feval(opts.parameters.learning_method,net{4},res.Fit,opts );