def create_model(cls, **kwargs) -> nn.Module:
return ResnetTensorObjectNavActorCritic(
action_space=gym.spaces.Discrete(len(ObjectNavTask.class_action_names())),
observation_space=kwargs["observation_set"].observation_spaces,
goal_sensor_uuid="goal_object_type_ind",
rgb_resnet_preprocessor_uuid="rgb_resnet",
hidden_size=512,
goal_dims=32,
)
def create_model(cls, **kwargs) -> nn.Module:
has_rgb = any(isinstance(s, RGBSensor) for s in cls.SENSORS)
has_depth = any(isinstance(s, DepthSensor) for s in cls.SENSORS)
goal_sensor_uuid = next(
(s.uuid
for s in cls.SENSORS if isinstance(s, GoalObjectTypeThorSensor)),
None,
)
return ResnetTensorObjectNavActorCritic(
action_space=gym.spaces.Discrete(
len(ObjectNavTask.class_action_names())),
observation_space=kwargs["sensor_preprocessor_graph"].
observation_spaces,
goal_sensor_uuid=goal_sensor_uuid,
rgb_resnet_preprocessor_uuid="rgb_resnet" if has_rgb else None,
depth_resnet_preprocessor_uuid="depth_resnet"
if has_depth else None,
hidden_size=512,
goal_dims=32,
)
