# Copyright 2021 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Configuration definitions for multi-task training.""" from typing import Optional, Tuple import dataclasses from official.core import config_definitions as cfg from official.modeling.hyperparams import base_config @dataclasses.dataclass class TaskRoutine(base_config.Config): task_name: str = "" task_config: cfg.TaskConfig = None mixing_steps: int = 1 eval_steps: Optional[int] = None task_weight: Optional[float] = None @dataclasses.dataclass class MultiTaskConfig(base_config.Config): init_checkpoint: str = "" model: base_config.Config = None task_routines: Tuple[TaskRoutine, ...] = () @dataclasses.dataclass class MultiEvalExperimentConfig(base_config.Config): """An experiment config for single-task training and multi-task evaluation. Attributes: task: the single-stream training task. eval_tasks: individual evaluation tasks. trainer: the trainer configuration. runtime: the runtime configuration. """ task: cfg.TaskConfig = cfg.TaskConfig() eval_tasks: MultiTaskConfig = MultiTaskConfig() trainer: cfg.TrainerConfig = cfg.TrainerConfig() runtime: cfg.RuntimeConfig = cfg.RuntimeConfig()