def modelSubmission(): debug('In model submission method') if request.method == 'POST': n = network.get_network(networks, request.form['network']) if n == None: debug("Error, can't find the network") return if request.form['btn'] == 'Train': debug("Training network") method = request.form['method'] number_of_epochs_logistic = int(request.form['epochsLogistic']) number_of_epochs_multilayer = int(request.form['epochsMultilayer']) k = int(request.form['k']) learning_rate_deep = float(request.form['learningRate']) layers = int(request.form['layers']) stop_at_100_accuracy = request.form.getlist('100') if not n.initialized or method != n.method_initialized: n.initialize(method, learning_rate_deep, layers) n.train(method, number_of_epochs_logistic, number_of_epochs_multilayer, stop_at_100_accuracy=stop_at_100_accuracy) #todo : update progress #t = threading.Thread(target=train_and_redirect, args=(n,)) #t.start() elif request.form['btn'] == 'Reset': n.initialized = False n.best_accuracy = 0 n.accuracy = 0 n.epochs_for_best_accuracy = 0 n.epochs_for_accuracy = 0 n.method_initialized = None n.trained = False elif request.form['btn'] == 'Delete': n.deleteModel() networks.remove(n) global summary_initialization, summary_training, summary_output summary_initialization = False summary_training = True summary_output = False return redirect('/')
def output(path): debug('In output method') if request.method == 'POST': n = network.get_network(networks, path) debug('network = ' + str(n)) inputs = [] for i in range(n.number_of_inputs): inputs.append(request.form[str(i)]) debug('input ' + str(i) + ' = ' + request.form[str(i)]) global result result = n.get_output(map(int, inputs)) global summary_initialization, summary_training, summary_output summary_initialization = False summary_training = False summary_output = True return redirect('/')