Refactoring: Deleting base pipeline

pipelines/base.py

@@ -3,26 +3,6 @@
 from torch.utils.data import DataLoader
 
 
-class BaseRunner(ABC):
-    @abstractmethod
-    def run(self, *args, **kwargs):
-        pass
-
-
-class BasePipeline(ABC):
-    @abstractmethod
-    def preprocess(self):
-        pass
-
-    @abstractmethod
-    def train(self):
-        pass
-
-    @abstractmethod
-    def evaluate(self):
-        pass
-
-
 class BaseDataLoaders(ABC):
     @property
     @abstractmethod
@@ -38,3 +18,9 @@ def validation_dataloader(self) -> DataLoader:
     @abstractmethod
     def test_dataloader(self) -> DataLoader:
         pass
+
+
+class BaseRunner(ABC):
+    @abstractmethod
+    def run(self, *args, **kwargs):
+        pass

pipelines/trainer.py

@@ -1,5 +1,5 @@
 import os
-from typing import Callable, Dict, List, Optional, TypedDict, cast
+from typing import Callable, Dict, List, NotRequired, Optional, TypedDict, cast
 
 import pandas as pd
 import torch
@@ -13,6 +13,16 @@
 from pipelines.utils.early_stopping import EarlyStopping
 
 
+class TrainingParams(TypedDict):
+    epochs: int
+    batch_size: int
+    loss_criterion: nn.Module
+    accuracy_criterion: nn.Module
+    optimizer: nn.Module
+    early_stopping: EarlyStopping
+    metrics_filename: NotRequired[str]
+
+
 class TrainingMetrics(TypedDict):
     train_loss: List[float]
     validation_loss: List[float]