Merge branch 'dev' into feature/pyproject.toml

Author: aditya0by0

chebai/trainer/CustomTrainer.py

@@ -25,7 +25,7 @@ def __init__(self, *args, **kwargs):
         """
         self.init_args = args
         self.init_kwargs = kwargs
-        super().__init__(*args, **kwargs)
+        super().__init__(*args, **kwargs, deterministic=True)
         # instantiation custom logger connector
         self._logger_connector.on_trainer_init(self.logger, 1)
         # log additional hyperparameters to wandb

tests/unit/dataset_classes/testDynamicDataset.py

@@ -85,8 +85,10 @@ def test_get_test_split_valid(self) -> None:
         """
         Test splitting the dataset into train and test sets and verify balance and non-overlap.
         """
-        self.dataset.train_split = 0.5
+        # self.dataset.train_split = 0.5
         # Test size will be 0.25 * 16 = 4
+        self.dataset.test_split = 0.25
+        self.dataset.validation_split = 0.25
         train_df, test_df = self.dataset.get_test_split(self.data_df, seed=0)
 
         # Assert the correct number of rows in train and test sets
@@ -149,7 +151,9 @@ def test_get_train_val_splits_given_test(self) -> None:
         Test splitting the dataset into train and validation sets and verify balance and non-overlap.
         """
         self.dataset.use_inner_cross_validation = False
-        self.dataset.train_split = 0.5
+        # self.dataset.train_split = 0.5
+        self.dataset.test_split = 0.25
+        self.dataset.validation_split = 0.25
         df_train_main, test_df = self.dataset.get_test_split(self.data_df, seed=0)
         train_df, val_df = self.dataset.get_train_val_splits_given_test(
             df_train_main, test_df, seed=42
@@ -220,7 +224,9 @@ def test_get_test_split_stratification(self) -> None:
         """
         Test that the split into train and test sets maintains the stratification of labels.
         """
-        self.dataset.train_split = 0.5
+        # self.dataset.train_split = 0.5
+        self.dataset.test_split = 0.25
+        self.dataset.validation_split = 0.25
         train_df, test_df = self.dataset.get_test_split(self.data_df, seed=0)
 
         number_of_labels = len(self.data_df["labels"][0])
@@ -288,7 +294,10 @@ def test_get_train_val_splits_given_test_stratification(self) -> None:
         Test that the split into train and validation sets maintains the stratification of labels.
         """
         self.dataset.use_inner_cross_validation = False
-        self.dataset.train_split = 0.5
+        # self.dataset.train_split = 0.5
+        self.dataset.test_split = 0.25
+        self.dataset.validation_split = 0.25
+
         df_train_main, test_df = self.dataset.get_test_split(self.data_df, seed=0)
         train_df, val_df = self.dataset.get_train_val_splits_given_test(
             df_train_main, test_df, seed=42