def run_measurement(name, topology_parameters, args, debug: bool = False): """"Runs the experiment with specified params, see the parse_test_args method for arguments""" # exp_params = Params # def param_pass(gate_input_context_multiplier: int) -> Any: # return {'gate_input_context_multiplier': gate_input_context_multiplier} # scaffolding = TopologyScaffoldingFactory(GradualLearningBasicTopology, params=param_pass) scaffolding = TopologyScaffoldingFactory( GradualLearningBasicTopology, params=GradualLearningBasicTopologyParams) template = GradualLearningBasicTemplate("Gradual learning basic") params: NotForgettingExperimentParams = topology_parameters[0]['params'][ 'experiment_params'].params max_steps = params.phase_1_steps + params.phase_2_steps + params.phase_3_steps + 1 experiment_params = ExperimentParams( max_steps=max_steps, save_cache=args.save, # add --save param load_cache=args.load, # add --load param ) experiment = Experiment(template, scaffolding, topology_parameters, experiment_params) # run_experiment_with_ui(experiment, auto_start=True) run_experiment(experiment)
def run_measurement(name, topology_parameters, args, exp_pars): """"Runs the experiment with specified params, see the parse_test_args method for arguments""" scaffolding = TopologyScaffoldingFactory(Task0TaAnalysisTopology, se_group=SeNodeGroup, model=DummyModelGroup) template = Task0TaAnalysisTemplate( "Task 0 layer-wise stats and classification accuracy", exp_pars.experiment_params, exp_pars.train_test_params) runner_parameters = ExperimentParams( max_steps=exp_pars.train_test_params.max_steps, save_cache=args.save, load_cache=args.load, clear_cache=args.clear, calculate_statistics=not args.computation_only, experiment_folder=args.alternative_results_folder) experiment = Experiment(template, scaffolding, topology_parameters, runner_parameters) logger.info(f'Running model: {name}') if args.run_gui: run_experiment_with_ui(experiment) else: run_experiment(experiment) if args.show_plots: plt.show()
def run_measurement(topology_parameters, args, run_debug: bool, avg_reward_window_size: int = 100, run_gui: bool = True): max_steps = 100 if run_debug else 40000 scaffolding = TopologyScaffoldingFactory( GoalDirectedTemplateTopology, model=TwoExpertsGroup, params=GoalDirectedTemplateTopologyParams) template = GoalDirectedTemplate( "Goal Directed Behavior - Comparision of TA Hierarchies", avg_reward_window_size=avg_reward_window_size) runner_parameters = ExperimentParams( max_steps=max_steps, save_cache=args.save, load_cache=args.load, clear_cache=args.clear, calculate_statistics=not args.computation_only, experiment_folder=args.alternative_results_folder) experiment = Experiment(template, scaffolding, topology_parameters, runner_parameters) if run_gui: run_experiment_with_ui(experiment) else: run_experiment(experiment)
def run_measurement(name, topology_parameters, args, debug: bool = False): """"Runs the experiment with specified params, see the parse_test_args method for arguments""" exp_pars = debug_params if debug else full_params scaffolding = TopologyScaffoldingFactory( ClassificationAccuracyModularTopology, se_group=SeNodeGroup, model=AttentionClassificationGroup) template = Task0TrainTestClassificationAccTemplate( "Task 0 classification accuracy with and without attention", exp_pars.experiment_params, exp_pars.train_test_params) runner_parameters = ExperimentParams( max_steps=exp_pars.train_test_params.max_steps, save_cache=args.save, load_cache=args.load, clear_cache=args.clear, calculate_statistics=not args.computation_only, experiment_folder=args.alternative_results_folder) experiment = Experiment(template, scaffolding, topology_parameters, runner_parameters) logger.info(f'Running model: {name}') if args.run_gui: run_experiment_with_ui(experiment) else: run_experiment(experiment) if args.show_plots: plt.show()
def run_measurement(args, topologies_params, template_params): topology_factory = GlNnTopologyFactory() template = GradualLearningExperimentTemplate(template_params) runner_parameters = ExperimentParams( max_steps=0, save_cache=args.save, load_cache=args.load, clear_cache=args.clear, calculate_statistics=not args.computation_only, experiment_folder=args.alternative_results_folder) experiment = Experiment(template, topology_factory, topologies_params, runner_parameters) # run_experiment_with_ui(experiment) run_experiment(experiment)