Support datasets library #7
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| cls_doc = getattr(callable_, "__doc__", None) | ||
| return "" if cls_doc is None else cls_doc | ||
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| def append_parent_docstr(cls: Type = None, parent_id: int = 0): |
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Optionally, we can adopt the common convention as "klass" for such naming.
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I personally don't like "klass". Moreover, type hint reveal its type and cls is also commonly used including IDE stubs.
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cls is common keyword for classmethods that's why I suggested a change though it's kinda optional ofc.
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| def append_callable_docstr( | ||
| cls: Type = None, callable_: Union[Type, Callable] = None |
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+1 above (my comment)
devrimcavusoglu
requested changes
Sep 20, 2021
…DatasetReader make DatasetReader their common base class.
- Drop the support for the regular file based dataset readers. - Introduce DatasetLoader class that wraps the load_dataset function from the datasets library. - Introduce TransformerDataProcessor class that performs the previous dataset reader's most job.
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devrimcavusoglu
requested changes
Sep 20, 2021
devrimcavusoglu
requested changes
Sep 20, 2021
devrimcavusoglu
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Sep 20, 2021
This was referenced Sep 20, 2021
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Replace the dataset reader classes with data processors and a dataset loader class. TransformerDataProcessor contains the optimizer and is responsible from tokenization and pre-processing e.g. append special tokens and truncation etc. The DatasetLoader is currently a single class that can load datasets from the datasets library through the load_dataset function. It also processes the datasets using its TransformerDataProcessor attribute and can directly provide IndexedDataset to the TransformerTrainer.
Fixes:
#2
#5
#6