def __init__(self, observation_spaces_dict: Dict[Union[str, int],
spaces.Dict],
action_spaces_dict: Dict[Union[str, int], spaces.Dict],
networks: CollectionOfConfigType):
super().__init__(observation_spaces_dict, action_spaces_dict)
assert len(networks) == 1
network = networks[0]
flat_action_space = flat_structured_space(self._action_spaces_dict)
obs_shapes_flat = flat_structured_shapes(self._obs_shapes)
# Infer the critic out shapes. When all action heads in a given state are discrete the discrete version of the
# state-action critic is used that outputs a value for each possible action (for each action). Otherwise
# the more general version is used which returns one value for a given state and action.
critic_output_shapes = dict()
if all(self._only_discrete_spaces.values()):
for act_key, act_space in flat_action_space.spaces.items():
critic_output_shapes[act_key + '_q_values'] = (act_space.n, )
else:
for act_key, act_space in flat_action_space.spaces.items():
if isinstance(act_space, spaces.Discrete):
obs_shapes_flat[act_key] = (act_space.n, )
else:
obs_shapes_flat[act_key] = act_space.sample().shape
critic_output_shapes['q_value'] = (1, )
# initialize critic
model_registry = Factory(base_type=nn.Module)
self._critics = {
0:
model_registry.instantiate(network,
obs_shapes=obs_shapes_flat,
output_shapes=critic_output_shapes)
}
def __init__(self, observation_spaces_dict: Dict[Union[str, int],
spaces.Dict],
agent_counts_dict: Dict[StepKeyType, int],
networks: CollectionOfConfigType):
super().__init__(observation_spaces_dict, agent_counts_dict)
# initialize critic
model_registry = Factory(base_type=nn.Module)
networks = list_to_dict(networks)
self._critics = dict()
for idx, (key, net_config) in enumerate(networks.items()):
step_obs_shapes = self._obs_shapes[key]
if idx > 0:
step_obs_shapes = {
**step_obs_shapes, self.prev_value_key:
self.prev_value_shape
}
self._critics[key] = model_registry.instantiate(
networks[key], obs_shapes=step_obs_shapes)
def __init__(self, observation_spaces_dict: Dict[StepKeyType, spaces.Dict],
agent_counts_dict: Dict[StepKeyType, int],
networks: ConfigType, stack_observations: bool):
super().__init__(observation_spaces_dict, agent_counts_dict)
assert len(networks) == 1
self.stack_observations = stack_observations
network = networks[0]
obs_shapes_flat = self._obs_shapes
if self.stack_observations:
obs_shapes_flat = stacked_shapes(obs_shapes_flat,
self._agent_counts_dict)
obs_shapes_flat = flat_structured_shapes(obs_shapes_flat)
self._obs_shapes = {0: obs_shapes_flat}
# initialize critic
model_registry = Factory(base_type=nn.Module)
self._critics = {
0: model_registry.instantiate(network, obs_shapes=obs_shapes_flat)
}
def test_raises_exception_on_invalid_registry_value():
with pytest.raises(ImportError):
registry = Factory(base_type=DummyObservationConversion)
registry.instantiate(config={"_target_": "wrong_key"})
def test_raises_exception_on_invalid_type():
with pytest.raises(AssertionError):
registry = Factory(base_type=DummyObservationConversion)
registry.instantiate(config=DictActionConversion())
def test_returns_if_arg_already_instantiated():
obs_conv = CustomDummyObservationConversion(attr=1)
registry = Factory(base_type=DummyObservationConversion)
obj = registry.instantiate(config=obs_conv)
assert obj == obj
