def test_experiment():
spec = spec_util.get('demo.json', 'dqn_cartpole')
spec_util.save(spec, unit='experiment')
spec = spec_util.override_test_spec(spec)
spec_util.tick(spec, 'experiment')
experiment_df = Experiment(spec).run()
assert isinstance(experiment_df, pd.DataFrame)
def run_trial_test(spec_file, spec_name=False):
spec = spec_util.get(spec_file, spec_name)
spec = spec_util.override_test_spec(spec)
spec_util.tick(spec, 'trial')
trial = Trial(spec)
trial_metrics = trial.run()
assert isinstance(trial_metrics, dict)
def test_trial_demo():
spec = spec_util.get('demo.json', 'dqn_cartpole')
spec_util.save(spec, unit='experiment')
spec = spec_util.override_test_spec(spec)
spec_util.tick(spec, 'trial')
trial_metrics = Trial(spec).run()
assert isinstance(trial_metrics, dict)
def test_trial_demo(test_info_space):
spec = spec_util.get('demo.json', 'dqn_cartpole')
spec = spec_util.override_test_spec(spec)
spec['env'][0]['save_frequency'] = 1
test_info_space.tick('trial')
trial_data = Trial(spec, test_info_space).run()
assert isinstance(trial_data, pd.DataFrame)
def test_experiment(test_info_space):
spec = spec_util.get('demo.json', 'dqn_cartpole')
analysis.save_spec(spec, test_info_space, unit='experiment')
spec = spec_util.override_test_spec(spec)
test_info_space.tick('experiment')
experiment_data = Experiment(spec, test_info_space).run()
assert isinstance(experiment_data, pd.DataFrame)
def run_trial_test(spec_file, spec_name=False):
spec = spec_util.get(spec_file, spec_name)
spec = spec_util.override_test_spec(spec)
info_space = InfoSpace()
info_space.tick('trial')
trial = Trial(spec, info_space)
trial_data = trial.run()
assert isinstance(trial_data, pd.DataFrame)
def test_trial_demo(test_info_space):
spec = spec_util.get('demo.json', 'dqn_cartpole')
analysis.save_spec(spec, test_info_space, unit='experiment')
spec = spec_util.override_test_spec(spec)
spec['meta']['eval_frequency'] = 1
test_info_space.tick('trial')
trial_data = Trial(spec, test_info_space).run()
assert isinstance(trial_data, pd.DataFrame)
def test_prioritized_replay_memory(request):
memspec = spec_util.get('base.json', 'base_prioritized_replay_memory')
memspec = spec_util.override_test_spec(memspec)
aeb_mem_space = AEBSpace(memspec, InfoSpace())
env_space = EnvSpace(memspec, aeb_mem_space)
aeb_mem_space.init_body_space()
agent_space = AgentSpace(memspec, aeb_mem_space)
agent = agent_space.agents[0]
body = agent.nanflat_body_a[0]
res = (body.memory, ) + request.param
return res
def run_trial_test_dist(spec_file, spec_name=False):
spec = spec_util.get(spec_file, spec_name)
spec = spec_util.override_test_spec(spec)
spec_util.tick(spec, 'trial')
spec['meta']['distributed'] = 'synced'
spec['meta']['max_session'] = 2
trial = Trial(spec)
# manually run the logic to obtain global nets for testing to ensure global net gets updated
global_nets = trial.init_global_nets()
# only test first network
if ps.is_list(global_nets): # multiagent only test first
net = list(global_nets[0].values())[0]
else:
net = list(global_nets.values())[0]
session_metrics_list = trial.parallelize_sessions(global_nets)
trial_metrics = analysis.analyze_trial(spec, session_metrics_list)
trial.close()
assert isinstance(trial_metrics, dict)
def run_trial_test_dist(spec_file, spec_name=False):
spec = spec_util.get(spec_file, spec_name)
spec = spec_util.override_test_spec(spec)
info_space = InfoSpace()
info_space.tick('trial')
spec['meta']['distributed'] = True
spec['meta']['max_session'] = 2
trial = Trial(spec, info_space)
# manually run the logic to obtain global nets for testing to ensure global net gets updated
global_nets = trial.init_global_nets()
# only test first network
if ps.is_list(global_nets): # multiagent only test first
net = list(global_nets[0].values())[0]
else:
net = list(global_nets.values())[0]
session_datas = trial.parallelize_sessions(global_nets)
trial.session_data_dict = {data.index[0]: data for data in session_datas}
trial_data = analysis.analyze_trial(trial)
trial.close()
assert isinstance(trial_data, pd.DataFrame)
def test_spec():
spec = spec_util.get('experimental/misc/base.json', 'base_case_openai')
spec = spec_util.override_test_spec(spec)
return spec
def test_spec():
global spec
spec = spec_util.get('base.json', 'base_case_openai')
spec = spec_util.override_test_spec(spec)
return spec
