Rename KerasNLP symbols for a multi-modal future #1803
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This PR (if it's been done right), should not break any existing
functionality. It's adds a lot a new aliases for existing symbols,
that going forward will be the main way we document them.
- `Classifier` -> `TextClassifier` and `XXClassifer` -> `XXTextClassifier`.
- Add new base classes `keras_nlp.models.TextClassifierPrepreprocessor`,
`keras_nlp.models.CausalLMPreprocessor` and
`keras_nlp.models.MaskedLMPreprocessor.
There's no need to update if you don't want to, we will continue to
to support the existing usages indefinitely. This is primarily to
reduce confusion in our own docs; we want `ImageClasssifier` and
`TextClassifier` can have obviously distinct usage.
This new base classes enable a cross-model way of writing task code with
split preprocessing.
```
preprocessor = keras_nlp.models.TextClassifierPrepreprocessor.from_preset(
"bert_base_en",
)
classifier = keras_nlp.models.TextClassifier(
"bert_base_en",
num_classes=2,
)
... run prepreprocessing and training separately
```
As a follow up, I think we can remove a lot of code by pushing common
code onto base classes. But I will do that in a later PR to keep this
from getting to big.
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This PR (if it's been done right), should not break any existing functionality. It's adds a lot a new aliases for existing symbols, that going forward will be the main way we document them.
Classifier->TextClassifierandXXClassifer->XXTextClassifier.keras_nlp.models.TextClassifierPrepreprocessor,keras_nlp.models.CausalLMPreprocessorandkeras_nlp.models.MaskedLMPreprocessor.There's no need to update if you don't want to, we will continue to to support the existing usages indefinitely. This is primarily to reduce confusion in our own docs; we want
ImageClasssifierandTextClassifierto have obviously distinct usage.This new base classes also enable a cross-model way of writing task code with split preprocessing.
As a follow up, I think we can remove a lot of code by pushing common code onto base classes. But I will do that in a later PR to keep this from getting to big.