🚨🚨 Fix and simplify attention implementation dispatch and subconfigs handling (#39423)

* first try

* Update modeling_utils.py

* Update modeling_utils.py

* big refactor

* Update modeling_utils.py

* style

* docstrings and simplify inner workings of configs

* remove all trace of _internal

* Update modeling_utils.py

* fix logic error

* Update modeling_utils.py

* recursive on config

* Update configuration_utils.py

* fix

* Update configuration_dpt.py

* Update configuration_utils.py

* Update configuration_utils.py

* Update modeling_idefics.py

* Update modeling_utils.py

* fix for old models

* more old models fixup

* Update modeling_utils.py

* Update configuration_utils.py

* Remove outdated test

* remove the deepcopy!! 🥵🥵

* Update test_modeling_gpt_bigcode.py

* fix qwen dispatch

* restrict to only models supporting it

* style

* switch name

* Update modeling_utils.py

* Update modeling_utils.py

* add tests!

* fix

* rypo

* remove bad copies

* fix

* Update modeling_utils.py

* additional check

* Update modeling_utils.py

* Update modeling_utils.py

* Update modeling_utils.py

* Update modeling_utils.py

* Update modeling_utils.py

* fix

* skip

utils/test_module/custom_modeling.py

@@ -2,7 +2,7 @@ import torch
 
 from transformers import PreTrainedModel
 
-from .custom_configuration import CustomConfig, NoSuperInitConfig
+from .custom_configuration import CustomConfig
 
 
 class CustomModel(PreTrainedModel):
@@ -17,17 +17,3 @@ class CustomModel(PreTrainedModel):
 
     def _init_weights(self, module):
         pass
-
-
-class NoSuperInitModel(PreTrainedModel):
-    config_class = NoSuperInitConfig
-
-    def __init__(self, config):
-        super().__init__(config)
-        self.linear = torch.nn.Linear(config.attribute, config.attribute)
-
-    def forward(self, x):
-        return self.linear(x)
-
-    def _init_weights(self, module):
-        pass