src.model.fit.fitWrapper module

Fit function Wrapper

src.model.fit.fitWrapper.Fit_Selector(function, *args, **kwargs)

src.model.fit.fitWrapper.RLTrnFrz_External_AfterTrivial(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, rl_model, slReps: int = 2, slInRLReps: int = 10, rlReps: int = 10, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.RLTrnFrz_External_graysAfterFit(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, rl_model, slReps: int = 2, slInRLReps: int = 10, rlReps: int = 10, correct_exp_threshold: int = 1, last_exp_to_consider: int = 10, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.RLTrnFrz_graysAfterFit(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, rl_model, reps: int = 10, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.default(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.get_rl_controller(callbacks: List[Callback], cls_name: str = 'augmented_cls', controller_name: str = 'RL_partial_env_manager') → Tuple[int, Callback]

src.model.fit.fitWrapper.grays(model, callbacks: List[Callback], data: DatasetV2, grayAction: Generator, epochs: int = 0, skip: int | str = 0, step: int | str = 1, *args, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFit(model, callbacks: List[Callback], data: DatasetV2, grayAction: Generator, reps: int = 10, *args, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFitCURE_netReset(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, reps: int = 10, active_reset: bool = False, checkpoint_file: str | None = None, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFitReinforce(model, reinforceModel, callbacks: List[Callback], data: DatasetV2, grayAction: Generator, reps: int = 10, *args, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFit_modelCheckpoint(model, callbacks: List[Callback], data: DatasetV2, grayAction: Generator, reps: int = 10, checkpoint_file: str | None = None, *args, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFit_netReset(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, reps: int = 10, active_reset: bool = False, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFit_netReset_RLLast(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, reps: int = 10, active_reset: bool = False, rl_controller_cb: ~typing.Any | None = None, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.graysAfterFit_netReset_RLnoFirst(model, callbacks: ~typing.List[~keras.src.callbacks.callback.Callback], data: ~tensorflow.python.data.ops.dataset_ops.DatasetV2, grayAction: ~typing.Generator, reps: int = 10, active_reset: bool = False, *args, logger=None, write_msg=<function f_logger.<locals>.__dummy_log>, **kwargs) → History

src.model.fit.fitWrapper.stepFit(model, callbacks: List[Callback], data: DatasetV2, start: int, *args, verbose: str | int | None = 1, **kwargs)