`modules_to_save` raises TypeError when a name is a suffix of a LoRA sub-module (e.g. "out", "A")

### System Info

- peft: main (`fd570a5f`), 0.21.0
- transformers: 5.17.0
- torch: 2.14.0
- accelerate: 1.15.0
- Python: 3.11
- Platform: Linux, CPU only

### Who can help?

@BenjaminBossan

### Reproduction

```python
import torch
from torch import nn
from peft import LoraConfig, get_peft_model

class Net(nn.Module):
def __init__(self):
super().__init__()
self.lin = nn.Linear(8, 8)
self.out = nn.Linear(8, 2)

def forward(self, x):
return self.out(self.lin(x))

config = LoraConfig(r=4, target_modules=["lin"], modules_to_save=["out"])
get_peft_model(Net(), config)
```

```
Traceback (most recent call last):
...
File ".../peft/utils/other.py", line 1118, in _set_trainable
new_module = wrapper_cls(target, adapter_name, **wrapper_kwargs)
File ".../peft/utils/other.py", line 605, in __init__
super().__init__(module_to_save, adapter_name, tied_module=tied_module)
File ".../peft/utils/other.py", line 327, in __init__
self.check_module()
File ".../peft/utils/other.py", line 352, in check_module
raise TypeError(f"{self._error_message_name()} cannot be applied to modules of type {cls_name}")
TypeError: modules_to_save cannot be applied to modules of type
```

The same happens with `modules_to_save=["A"]` (matches `lin.lora_A`) or `["B"]` (matches `lin.lora_B`).

### Cause

`_set_trainable` (`src/peft/utils/other.py`) matches `modules_to_save` entries with `key.endswith(target_key)`. The wrapping runs after the LoRA layers are injected, so at that point the model also contains `lin.lora_dropout`, `lin.lora_A`, `lin.lora_B`, and `"lin.lora_dropout".endswith("out")` is true. The LoRA layer's own `ModuleDict` is then passed to `ModulesToSaveWrapper`, whose type check raises.

There is already a guard for the adapter-name collision case (`lin.lora_A.default` when the adapter is called `default`), which checks whether the *grandparent* is a `BaseTunerLayer`. The case where the *parent* is the tuner layer isn't covered.

### Expected behavior

Only the real `out` module is wrapped in `ModulesToSaveWrapper`; the sub-modules that a PEFT layer creates for itself (`lora_A`, `lora_B`, `lora_dropout`, ...) should never be `modules_to_save` candidates.

### Proposed fix

In `_set_trainable`, skip a match whose parent is a `BaseTunerLayer` (`continue`). This keeps the existing suffix matching untouched (I saw #1917, where it was explained that this must stay for backwards compatibility) and only stops PEFT from matching its own internals.

I have the fix (5 lines) and a parametrized regression test in `tests/test_initialization.py` next to `test_modules_to_save_targets_lora_layer_raises` ready. The test fails on `main` and passes with the fix; `tests/test_initialization.py`, `tests/test_other.py`, `tests/test_trainable_tokens.py` and the `modules_to_save`/`trainable_token` tests in `tests/test_custom_models.py` are unchanged otherwise, and `make quality` passes. I intend to provide the PR once approved.

AI assistance (Claude) was used to investigate and draft this; I have reviewed the change and run the tests myself.