Expose Task and Backbone (keras-team#1506)

These are already exposed on KerasCV, and I think it is time to
also expose these in KerasNLP. This will give us a class to document
common model functionality to all backbones such as `enable_lora`
and `token_embedding` on keras.io.

It can also open up a path for writing a custom architecture outside
the library itself.

keras_nlp/models/__init__.py

@@ -20,6 +20,7 @@
 )
 from keras_nlp.models.albert.albert_preprocessor import AlbertPreprocessor
 from keras_nlp.models.albert.albert_tokenizer import AlbertTokenizer
+from keras_nlp.models.backbone import Backbone
 from keras_nlp.models.bart.bart_backbone import BartBackbone
 from keras_nlp.models.bart.bart_preprocessor import BartPreprocessor
 from keras_nlp.models.bart.bart_seq_2_seq_lm import BartSeq2SeqLM
@@ -130,6 +131,7 @@
 from keras_nlp.models.roberta.roberta_tokenizer import RobertaTokenizer
 from keras_nlp.models.t5.t5_backbone import T5Backbone
 from keras_nlp.models.t5.t5_tokenizer import T5Tokenizer
+from keras_nlp.models.task import Task
 from keras_nlp.models.whisper.whisper_audio_feature_extractor import (
     WhisperAudioFeatureExtractor,
 )

keras_nlp/models/backbone.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from keras_nlp.api_export import keras_nlp_export
 from keras_nlp.backend import config
 from keras_nlp.backend import keras
 from keras_nlp.utils.preset_utils import check_preset_class
@@ -20,7 +21,7 @@
 from keras_nlp.utils.python_utils import format_docstring
 
 
-@keras.saving.register_keras_serializable(package="keras_nlp")
+@keras_nlp_export("keras_nlp.models.Backbone")
 class Backbone(keras.Model):
     def __init__(self, *args, dtype=None, **kwargs):
         super().__init__(*args, **kwargs)

keras_nlp/models/task.py

@@ -16,6 +16,7 @@
 from rich import markup
 from rich import table as rich_table
 
+from keras_nlp.api_export import keras_nlp_export
 from keras_nlp.backend import config
 from keras_nlp.backend import keras
 from keras_nlp.utils.keras_utils import print_msg
@@ -26,7 +27,7 @@
 from keras_nlp.utils.python_utils import format_docstring
 
 
-@keras.saving.register_keras_serializable(package="keras_nlp")
+@keras_nlp_export("keras_nlp.models.Task")
 class Task(PipelineModel):
     """Base class for Task models."""