refactor BaseEnvironment into SingleStep and MultiStep environments #1810
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initialized from HF/Pytorch/JSON/list of Dicts, remove the need for setup call and subsequently cleanup
test coverage
instead of strings and add seed for reproducibility
between simply skipping invalid datapoints in a seed dataset and throwing an exception
seed dataset to ensure they are defined before the other functions are
to store data in Seed Dataset
changes in base.py
requirements
getitem and cast len(data) to a Sized to pass mypy tests
…of Seed Dataset to ensure proper validation & add additional logging to init from JSON
call helper functions for each type of data
initialising with PyTorch Datasets
properly cover all 4 initialization functions & add tests for sampling
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TO DO:
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Description
At the moment,
BaseEnvironmentis very general. However, if we categorize intoSingleStepandMultiStepenvironments, we can be more efficient with our code. For example, normally, when doing RL with LLMs, the environment is symbolically single step - we sample a question, get an answer and compute a reward based on that answer. Then, we start a new episode. This is the priority for the Loong project.MultiStepenvironments, i.e. those that do not follow the pattern described above, e.g. Chess or Tic Tac Toe, are a bit more complicated and should be handled separately. This PR will provide an implementation ofSingleStepandMultiStepenvironment.This PR builds upon #1801.
This PR closes #1736.
Checklist
Go over all the following points, and put an
xin all the boxes that apply.Fixes #issue-numberin the PR description (required)pyproject.tomlanduv lockIf you are unsure about any of these, don't hesitate to ask. We are here to help!