Refactor embedding input/output getter/setter (#39339)

* simplify common get/set

* remove some noise

* change some 5 years old modeling utils

* update examples

* fix copies

* revert some changes

* fixes, gah

* format

* move to Mixin

* remove smolvlm specific require grad

* skip

* force defaults

* remodularise some stuff

* remodularise more stuff

* add safety for audio models

* style

* have a correct fallback, you daft donkey

* remove this argh

* change heuristic for audio models

* fixup

* revert

* this works

* revert again

* 🧠

* aaah ESM has two modelings aaah

* add informative but short comment

* add `input_embed_layer` mixin attribute

* style

* walrus has low precedence

* modular fix

* this was breaking parser

examples/modular-transformers/modeling_my_new_model2.py

@@ -333,12 +333,6 @@ class MyNewModel2Model(MyNewModel2PreTrainedModel):
         # Initialize weights and apply final processing
         self.post_init()
 
-    def get_input_embeddings(self):
-        return self.embed_tokens
-
-    def set_input_embeddings(self, value):
-        self.embed_tokens = value
-
     @check_model_inputs
     @auto_docstring
     def forward(
@@ -433,12 +427,6 @@ class MyNewModel2ForSequenceClassification(MyNewModel2PreTrainedModel):
         # Initialize weights and apply final processing
         self.post_init()
 
-    def get_input_embeddings(self):
-        return self.model.embed_tokens
-
-    def set_input_embeddings(self, value):
-        self.model.embed_tokens = value
-
     @can_return_tuple
     @auto_docstring
     def forward(

examples/modular-transformers/modeling_new_task_model.py

@@ -389,12 +389,6 @@ class NewTaskModelForNewTask(NewTaskModelPreTrainedModel, GenerationMixin):
     def set_input_embeddings(self, value):
         self.model.set_input_embeddings(value)
 
-    def get_output_embeddings(self):
-        return self.lm_head
-
-    def set_output_embeddings(self, new_embeddings):
-        self.lm_head = new_embeddings
-
     def set_decoder(self, decoder):
         self.model.set_decoder(decoder)
 

examples/modular-transformers/modeling_super.py

@@ -332,12 +332,6 @@ class SuperModel(SuperPreTrainedModel):
         # Initialize weights and apply final processing
         self.post_init()
 
-    def get_input_embeddings(self):
-        return self.embed_tokens
-
-    def set_input_embeddings(self, value):
-        self.embed_tokens = value
-
     @check_model_inputs
     @auto_docstring
     def forward(