| # Copyright 2024 Bytedance Ltd. and/or its affiliates | |
| # | |
| # 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. | |
| from abc import ABC, abstractmethod | |
| from verl import DataProto | |
| __all__ = ["BaseRollout"] | |
| class BaseRollout(ABC): | |
| def __init__(self): | |
| """ | |
| Args: | |
| dataloader: an Iterable of TensorDict that consistently generates prompts. Note that the dataloader | |
| should handle when the training stops. | |
| """ | |
| super().__init__() | |
| def generate_sequences(self, prompts: DataProto) -> DataProto: | |
| """Generate sequences""" | |
| pass | |