【Feature】add fd plugins && rm model_classes (#3123)

* add fd plugins && rm model_classed

* fix reviews

* add docs

* fix

* fix unitest ci

fastdeploy/model_executor/models/model_base.py

@@ -20,6 +20,7 @@ from typing import Dict, Union
 import numpy as np
 import paddle
 from paddle import nn
+from paddleformers.transformers import PretrainedModel
 
 
 class ModelRegistry:
@@ -27,21 +28,46 @@ class ModelRegistry:
     Used to register and retrieve model classes.
     """
 
-    _registry = {}
+    _arch_to_model_cls = {}
+    _arch_to_pretrained_model_cls = {}
 
     @classmethod
-    def register(cls, model_class):
+    def register_model_class(cls, model_class):
         """register model class"""
         if issubclass(model_class, ModelForCasualLM) and model_class is not ModelForCasualLM:
-            cls._registry[model_class.name()] = model_class
+            cls._arch_to_model_cls[model_class.name()] = model_class
         return model_class
 
+    @classmethod
+    def register_pretrained_model(cls, pretrained_model):
+        """register pretrained model class"""
+        if (
+            issubclass(pretrained_model, PretrainedModel)
+            and pretrained_model is not PretrainedModel
+            and hasattr(pretrained_model, "arch_name")
+        ):
+            cls._arch_to_pretrained_model_cls[pretrained_model.arch_name()] = pretrained_model
+
+        return pretrained_model
+
+    @classmethod
+    def get_pretrain_cls(cls, architectures: str):
+        """get_pretrain_cls"""
+        return cls._arch_to_pretrained_model_cls[architectures]
+
     @classmethod
     def get_class(cls, name):
         """get model class"""
-        if name not in cls._registry:
+        if name not in cls._arch_to_model_cls:
             raise ValueError(f"Model '{name}' is not registered!")
-        return cls._registry[name]
+        return cls._arch_to_model_cls[name]
+
+    @classmethod
+    def get_supported_archs(cls):
+        assert len(cls._arch_to_model_cls) == len(
+            cls._arch_to_model_cls
+        ), "model class / pretrained model registry num is not same"
+        return [key for key in cls._arch_to_model_cls.keys()]
 
 
 class ModelForCasualLM(nn.Layer, ABC):