def test_trainersettings_structure():
"""
Test structuring method for TrainerSettings
"""
trainersettings_dict = {
"trainer_type": "sac",
"hyperparameters": {
"batch_size": 1024
},
"max_steps": 1.0,
"reward_signals": {
"curiosity": {
"encoding_size": 64
}
},
}
trainer_settings = TrainerSettings.structure(trainersettings_dict,
TrainerSettings)
assert isinstance(trainer_settings.hyperparameters, SACSettings)
assert trainer_settings.trainer_type == TrainerType.SAC
assert isinstance(trainer_settings.max_steps, int)
assert RewardSignalType.CURIOSITY in trainer_settings.reward_signals
# Check invalid trainer type
with pytest.raises(ValueError):
trainersettings_dict = {
"trainer_type": "puppo",
"hyperparameters": {
"batch_size": 1024
},
"max_steps": 1.0,
}
TrainerSettings.structure(trainersettings_dict, TrainerSettings)
# Check invalid hyperparameter
with pytest.raises(TrainerConfigError):
trainersettings_dict = {
"trainer_type": "ppo",
"hyperparameters": {
"notahyperparam": 1024
},
"max_steps": 1.0,
}
TrainerSettings.structure(trainersettings_dict, TrainerSettings)
# Check non-dict
with pytest.raises(TrainerConfigError):
TrainerSettings.structure("notadict", TrainerSettings)
# Check hyperparameters specified but trainer type left as default.
# This shouldn't work as you could specify non-PPO hyperparameters.
with pytest.raises(TrainerConfigError):
trainersettings_dict = {"hyperparameters": {"batch_size": 1024}}
TrainerSettings.structure(trainersettings_dict, TrainerSettings)
def test_trainersettingsschedules_structure():
"""
Test structuring method for Trainer Settings Schedule
"""
trainersettings_dict = {
"trainer_type": "ppo",
"hyperparameters": {
"learning_rate_schedule": "linear",
"beta_schedule": "constant",
},
}
trainer_settings = TrainerSettings.structure(trainersettings_dict, TrainerSettings)
assert isinstance(trainer_settings.hyperparameters, PPOSettings)
assert (
trainer_settings.hyperparameters.learning_rate_schedule == ScheduleType.LINEAR
)
assert trainer_settings.hyperparameters.beta_schedule == ScheduleType.CONSTANT
assert trainer_settings.hyperparameters.epsilon_schedule == ScheduleType.LINEAR
