# HG changeset patch
# User siwaa
# Date 1733414629 0
# Node ID 60778af2dd78a00cf9ca2c55b98477d0dd0585a7
# Parent  b5f69f836e034c5bc0de323e2bd70635219ea18d
planemo upload for repository https://forgemia.inra.fr/nathalie.rousse/use/-/tree/dnn/DNN/galaxy-tools/wine_quality_train_eval commit e7fd13c34ec074a7ebc246301b5a80069dcbcc3a-dirty

diff -r b5f69f836e03 -r 60778af2dd78 toto_wine_quality_train_eval.py
--- a/toto_wine_quality_train_eval.py	Thu Dec 05 15:55:00 2024 +0000
+++ b/toto_wine_quality_train_eval.py	Thu Dec 05 16:03:49 2024 +0000
@@ -100,7 +100,7 @@
 import torchvision.transforms as T
 ##toto## from IPython.display import display, HTML ##toto## HTML
 from torch.utils.data import DataLoader, random_split
-from model_wine_lightning.modules.progressbar import CustomTrainProgressBar
+##toto## from model_wine_lightning.modules.progressbar import CustomTrainProgressBar
 from model_wine_lightning.modules.data_load import WineQualityDataset
 from model_wine_lightning.modules.data_load import Normalize, ToTensor
 from model_wine_lightning.modules.model import LitRegression
@@ -277,7 +277,8 @@
     # train model
     trainer = pl.Trainer(accelerator='auto', max_epochs=100,
                        logger=logger, num_sanity_val_steps=0,
-                       callbacks=[savemodel_callback,CustomTrainProgressBar()])
+                       callbacks=[savemodel_callback])
+                       ##toto##callbacks=[savemodel_callback,CustomTrainProgressBar()])
     trainer.fit(model=reg, train_dataloaders=train_loader,
                 val_dataloaders=test_loader)