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)