A bug when importing pytorch_forecasting

[kkckk1110]

• PyTorch-Forecasting version: 1.0.0
• Torch version: 2.1.2
• Python version: 3.9.19
• Operating System: Windows 64

Expected behavior

I executed code from pytorch_forecasting.models.temporal_fusion_transformer.tuning import optimize_hyperparameters
but have the following error:

TypeError Traceback (most recent call last)
Cell In[10], line 18
16 from pytorch_forecasting.data import GroupNormalizer
17 from pytorch_forecasting.metrics import MAE, MAPE,SMAPE, MAPE,PoissonLoss, QuantileLoss
---> 18 from pytorch_forecasting.models.temporal_fusion_transformer.tuning import optimize_hyperparameters
19 from pytorch_forecasting.data.examples import get_stallion_data
20 import datetime

File D:\Anaconda\envs\torch\lib\site-packages\pytorch_forecasting\models\temporal_fusion_transformer\tuning.py:29
25 optuna_logger = logging.getLogger("optuna")
28 # need to inherit from callback for this to work
---> 29 class PyTorchLightningPruningCallbackAdjusted(pl.Callback, PyTorchLightningPruningCallback):
30 pass
33 def optimize_hyperparameters(
34 train_dataloaders: DataLoader,
35 val_dataloaders: DataLoader,
(...)
52 **kwargs,
53 ) -> optuna.Study:

TypeError: Cannot create a consistent method resolution
order (MRO) for bases Callback, PyTorchLightningPruningCallback
del should be also included.

[ruuttt]

For me it worked to downgrade to optuna version 3.4 and pytorch 2.0.1
pip install torch==2.0.1 pytorch-lightning==2.0.2 pytorch_forecasting==1.0.0 torchaudio==2.0.2 torchdata==0.6.1 torchtext==0.15.2 torchvision==0.15.2 optuna==3.4

[flight505]

same issue, optuna version 3.5, pytorch 2.2 and pytorch_forecasting==1.0.0
hope to see it resolved

[Superzero31]

same issue with:
optuna==3.5
pytorch-lightning==2.2.1
pytorch_forecasting==1.0.0

[tty666]

I agree I have the same issue here with :

torch 2.2.1
optuna 3.6.0
pytorch-lightning 2.2.1
pytorch-forecasting 1.0.0

[Xinyu-Wu-0000]

also see #1468