def test_bad_config():
brain_params = make_brain_parameters(discrete_action=False,
visual_inputs=0,
vec_obs_size=6)
# Test that we throw an error if we have sequence length greater than batch size
with pytest.raises(TrainerConfigError):
TrainerSettings(
network_settings=NetworkSettings(
memory=NetworkSettings.MemorySettings(sequence_length=64)),
hyperparameters=PPOSettings(batch_size=32),
)
_ = PPOTrainer(brain_params, 0, dummy_config, True, False, 0, "0")
EnvironmentParametersChannel,
)
from mlagents_envs.communicator_objects.demonstration_meta_pb2 import (
DemonstrationMetaProto,
)
from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
from mlagents_envs.communicator_objects.space_type_pb2 import discrete, continuous
BRAIN_NAME = "1D"
PPO_CONFIG = TrainerSettings(
trainer_type=TrainerType.PPO,
hyperparameters=PPOSettings(
learning_rate=5.0e-3,
learning_rate_schedule=ScheduleType.CONSTANT,
batch_size=16,
buffer_size=64,
),
network_settings=NetworkSettings(num_layers=1, hidden_units=32),
summary_freq=500,
max_steps=3000,
threaded=False,
)
SAC_CONFIG = TrainerSettings(
trainer_type=TrainerType.SAC,
hyperparameters=SACSettings(
learning_rate=5.0e-3,
learning_rate_schedule=ScheduleType.CONSTANT,
batch_size=8,
buffer_init_steps=100,