A bit of cleaning 🧹🧹 (#37215)

* cleaning

* CIs

src/transformers/modeling_utils.py

@@ -298,24 +298,6 @@ def get_parameter_device(parameter: Union[nn.Module, "ModuleUtilsMixin"]):
         return first_tuple[1].device
 
 
-def get_first_parameter_dtype(parameter: Union[nn.Module, "ModuleUtilsMixin"]):
-    """
-    Returns the first parameter dtype (can be non-floating) or asserts if none were found.
-    """
-    try:
-        return next(parameter.parameters()).dtype
-    except StopIteration:
-        # For nn.DataParallel compatibility in PyTorch > 1.5
-
-        def find_tensor_attributes(module: nn.Module) -> List[Tuple[str, Tensor]]:
-            tuples = [(k, v) for k, v in module.__dict__.items() if torch.is_tensor(v)]
-            return tuples
-
-        gen = parameter._named_members(get_members_fn=find_tensor_attributes)
-        first_tuple = next(gen)
-        return first_tuple[1].dtype
-
-
 def get_parameter_dtype(parameter: Union[nn.Module, "ModuleUtilsMixin"]):
     """
     Returns the first found floating dtype in parameters if there is one, otherwise returns the last dtype it found.
@@ -365,17 +347,6 @@ def get_parameter_dtype(parameter: Union[nn.Module, "ModuleUtilsMixin"]):
     return last_dtype
 
 
-def get_state_dict_float_dtype(state_dict):
-    """
-    Returns the first found floating dtype in `state_dict` or asserts if none were found.
-    """
-    for t in state_dict.values():
-        if t.is_floating_point():
-            return t.dtype
-
-    raise ValueError("couldn't find any floating point dtypes in state_dict")
-
-
 def get_state_dict_dtype(state_dict):
     """
     Returns the first found floating dtype in `state_dict` if there is one, otherwise returns the first dtype.