First pass at integrating xP3#60
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viraat
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Apr 14, 2023
viraat
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- Add scripts to generate task constants for xP3 datasets
- Get started on a task_config generator for xP3:
- integrates P3 config generator with existing hugging face loader from c4ai loading script: https://github.com/for-ai/benchmarking-multilingual-model/blob/neel_xp3/xp3_folder/tasks.py
- Add scripts to generate task constants for xP3 datasets - Get started on a task_config generator for xP3: - integrates P3 config generator with existing hugging face loader
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Added some comments to help @shayne-longpre understand where to pay attention.
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This file is in progress atm. It's going to need a few more tweaks to get going.
I went with the same approach at P3 (T0) as it seemed to make the most sense to me. If this is the wrong path to go down, happy to discuss.
I separated the file out for hackability. It can go back into one of the task_config files later.
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| """Constants relate to xP3""" | |||
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| XP3_TRAIN_TASKS_SPLIT = { | |||
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This is incomplete, I have the script running but it's slow
| continue | ||
| # Do not process T0 variants with negative examples. | ||
| # We still keep the variants of these sets in a different format. | ||
| # if "_score_eval" in subtask_id: |
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Right now, I've only generated the splits for the training datasets.
| # We still keep the variants of these sets in a different format. | ||
| # if "_score_eval" in subtask_id: | ||
| # continue | ||
| # elif constants_t0.T0_TRAIN_TASK_METADATA[task_name][ |
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I wasn't sure how the metadata for the task was filled, this is something I'll need help with.
| task_name=subtask_id, task_source="P3") | ||
| XP3_TASK_CONFIGS[task_name] = TaskConfig( | ||
| source=seqio.TfdsDataSource( | ||
| tfds_name=f"huggingface:{ds_name}/{subset_name}", |
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From an eye test I think this works: https://www.tensorflow.org/datasets/community_catalog/huggingface seems to have the datasets I checked randomly.
There's some custom version picking in xP3 that will need to be brought over. I plan to put that into the metadata and use it here.
| # elif constants_t0.T0_TRAIN_TASK_METADATA[task_name][ | ||
| # "task_type"] == "t0_question_answer": | ||
| # preprocessors = [functools.partial(prep.t0, multiple_choice=False)] | ||
| # if constants_t0.T0_TRAIN_TASK_METADATA[task_name]["seq_len"]["max"] == 1: |
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Plan to use something similar and add to the metadata to do the custom preprocessing that happens in xP3. example fn
| # pip install -q datasets | ||
| import datasets | ||
| # git clone -b tr13 https://github.com/Muennighoff/promptsource.git && cd promptsource; pip install -e . | ||
| from promptsource.templates import DatasetTemplates |
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I'd be happy to get rid of using promptsource here. It's just used to get all the possible prompt templates for a given dataset. I'm assuming FC has that builtin already, but wasn't sure where to look.
- Add some try catch to log those datasets, and put dummy values
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