mllooper.Module#
- class mllooper.Module(name: Optional[str] = None, log_level: int = 10, log_time_delta: timedelta = datetime.timedelta(seconds=10))[source]#
Bases:
ABC- initialise(modules: Dict[str, Module]) None[source]#
Perform initialization steps of the module.
This might be needed to preform initialization steps that rely on other modules. The method receives a dictionary with other already initialised modules. Theses can be used for the own initialization.
This method should always be called before
mllooper.module.Module.step()is called.This method should only be used when the initialisation depends on other modules. If this is not the case use
self.__init__().- Parameters:
modules (Dict[str, Module]) – Dictionary of other modules which are already initialised
- load_state_dict(state_dict: Dict[str, any], strict: bool = True) None[source]#
Load the modules state from a dictionary.
- Parameters:
state_dict (Dict[str, any]) – The state dictionary to load
strict (bool) – If true rise an error on missing or additional keys in the state dict. If false these keys will be ignored.
- log(state: State) bool[source]#
Log information from the module.
The logic for logging should be implemented in
mllooper.module.Module._log()- Parameters:
state (State) – The current state
- run(state: Optional[State] = None) State[source]#
Initialise all modules, perform a step and teardown all modules.
- state_dict() Dict[str, Any][source]#
Return the state of the module as dictionary.
All items of the dictionary should be serializable by pickle.
- Returns:
The modules current state as dictionary
- Return type:
Dict[str, Any]
- step(state: State) None[source]#
Perform a step of the module on the state.
- Parameters:
state (State) – The current state