MLFlowLogger.save_dir mishandles absolute file: URIs on Windows

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### Bug description

When passing an absolute file path as tracking_uri on Windows, MLFlowLogger.save_dir does not handle the file: URI correctly, causing a malformed local path.

This results in writing to an invalid path like ///C:/..., resulting in FileNotFoundError: [WinError 161] The specified path is invalid.

I am aware that using mlflow.set_tracking_uri("http://localhost:8080") or mlflow.set_tracking_uri("file:./mlruns") is a valid workaround.

This is not related to #20669. I am willing to contribute a fix and a test case if needed.

```python
# example

import mlflow
from lightning.pytorch import Trainer
from lightning.pytorch.demos import BoringModel
from lightning.pytorch.loggers import MLFlowLogger

model = BoringModel()

mlflow.pytorch.autolog()
with mlflow.start_run() as run:
logger = MLFlowLogger(
tracking_uri=mlflow.get_tracking_uri(), # file:///C:/Dev/example/mlruns
run_id=run.info.run_id,
)

trainer = Trainer(
max_epochs=1,
logger=logger,
limit_train_batches=1,
limit_val_batches=1,
)

trainer.fit(model)
```

```python
# this code mishandles absolute paths on Windows
# tracking_uri
# file:///C:/Dev/example/mlruns
# result:
# ///C:/Dev/example/mlruns
# expected:
# C:/Dev/example/mlruns

@property
@override
def save_dir(self) -> Optional[str]:
"""The root file directory in which MLflow experiments are saved.

Return:
Local path to the root experiment directory if the tracking uri is local.
Otherwise returns `None`.

"""
if self._tracking_uri.startswith(LOCAL_FILE_URI_PREFIX):
return self._tracking_uri[len(LOCAL_FILE_URI_PREFIX) :]
return None
```

```python
# suggested fix

@property
@override
def save_dir(self) -> Optional[str]:
"""The root file directory in which MLflow experiments are saved.

Return:
Local path to the root experiment directory if the tracking uri is local.
Otherwise returns `None`.

"""
from urllib.parse import urlparse
from urllib.request import url2pathname

if self._tracking_uri.startswith(LOCAL_FILE_URI_PREFIX):
p = urlparse(self._tracking_uri)
return url2pathname(p.path)
return None
```

### What version are you seeing the problem on?

v2.5

### Reproduced in studio

_No response_

### How to reproduce the bug

```python

```

### Error messages and logs

```
Traceback (most recent call last):
File "C:\Dev\example\main.py", line 23, in
trainer.fit(model)
File "C:\Dev\example\venv\Lib\site-packages\mlflow\utils\autologging_utils\safety.py", line 484, in safe_patch_function
patch_function(call_original, *args, **kwargs)
File "C:\Dev\example\venv\Lib\site-packages\mlflow\utils\autologging_utils\safety.py", line 182, in patch_with_managed_run
result = patch_function(original, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\mlflow\pytorch\_lightning_autolog.py", line 544, in patched_fit
result = original(self, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\mlflow\utils\autologging_utils\safety.py", line 475, in call_original
return call_original_fn_with_event_logging(_original_fn, og_args, og_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\mlflow\utils\autologging_utils\safety.py", line 426, in call_original_fn_with_event_logging
original_fn_result = original_fn(*og_args, **og_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\mlflow\utils\autologging_utils\safety.py", line 472, in _original_fn
original_result = original(*_og_args, **_og_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\trainer.py", line 561, in fit
call._call_and_handle_interrupt(
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\call.py", line 48, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\trainer.py", line 599, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\trainer.py", line 1012, in _run
results = self._run_stage()
^^^^^^^^^^^^^^^^^
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\trainer.py", line 1056, in _run_stage
self.fit_loop.run()
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\loops\fit_loop.py", line 217, in run
self.on_advance_end()
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\loops\fit_loop.py", line 470, in on_advance_end
call._call_callback_hooks(trainer, "on_train_epoch_end", monitoring_callbacks=True)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\call.py", line 227, in _call_callback_hooks
fn(trainer, trainer.lightning_module, *args, **kwargs)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\callbacks\model_checkpoint.py", line 329, in on_train_epoch_end
self._save_topk_checkpoint(trainer, monitor_candidates)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\callbacks\model_checkpoint.py", line 391, in _save_topk_checkpoint
self._save_none_monitor_checkpoint(trainer, monitor_candidates)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\callbacks\model_checkpoint.py", line 719, in _save_none_monitor_checkpoint
self._save_checkpoint(trainer, filepath)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\callbacks\model_checkpoint.py", line 394, in _save_checkpoint
trainer.save_checkpoint(filepath, self.save_weights_only)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\trainer\trainer.py", line 1397, in save_checkpoint
self.strategy.save_checkpoint(checkpoint, filepath, storage_options=storage_options)
File "C:\Dev\example\venv\Lib\site-packages\lightning\pytorch\strategies\strategy.py", line 491, in save_checkpoint
self.checkpoint_io.save_checkpoint(checkpoint, filepath, storage_options=storage_options)
File "C:\Dev\example\venv\Lib\site-packages\lightning\fabric\plugins\io\torch_io.py", line 57, in save_checkpoint
fs.makedirs(os.path.dirname(path), exist_ok=True)
File "C:\Dev\example\venv\Lib\site-packages\fsspec\implementations\local.py", line 53, in makedirs
os.makedirs(path, exist_ok=exist_ok)
File "", line 215, in makedirs
File "", line 215, in makedirs
File "", line 215, in makedirs
[Previous line repeated 3 more times]
File "", line 225, in makedirs
FileNotFoundError: [WinError 161] The specified path is invalid: '///C:/'
```

### Environment

Current environment

```
#- PyTorch Lightning Version (e.g., 2.5.0): 2.5.2
#- PyTorch Version (e.g., 2.5): 2.7.1
#- Python version (e.g., 3.12): 3.12.4
#- OS (e.g., Linux): Windows 10
#- CUDA/cuDNN version: N/A
#- GPU models and configuration: N/A
#- How you installed Lightning(`conda`, `pip`, source): pip
```

### More info

_No response_

cc @lantiga @borda

Start at MLFlowLogger.save_dir, using the property implementation and Windows example in the issue to trace how the file: URI is converted into a local path. Reproduce the case with file:///C:/Dev/example/mlruns and verify that the resulting save directory is C:/Dev/example/mlruns rather than ///C:/....

Written by the indexing model from the issue text.