add documentation

freqtrade/freqai/base_models/PyTorchModelTrainer.py

@@ -54,10 +54,7 @@ class PyTorchModelTrainer:
 
     def fit(self, data_dictionary: Dict[str, pd.DataFrame]):
         """
-        general training loop:
-        - converting data to tensors
-        - calculating n_epochs
-        -
+        General training loop.
         """
         data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary)
         epochs = self.calc_n_epochs(
@@ -117,6 +114,9 @@ class PyTorchModelTrainer:
             self,
             data_dictionary: Dict[str, pd.DataFrame]
     ) -> Dict[str, DataLoader]:
+        """
+        Converts the input data to PyTorch tensors using a data loader.
+        """
         data_loader_dictionary = {}
         for split in ['train', 'test']:
             labels_shape = data_dictionary[f'{split}_labels'].shape
@@ -141,6 +141,10 @@ class PyTorchModelTrainer:
 
     @staticmethod
     def calc_n_epochs(n_obs: int, batch_size: int, n_iters: int) -> int:
+        """
+        Calculates the number of epochs required to reach the maximum number
+        of iterations specified in the model training parameters.
+        """
         n_batches = n_obs // batch_size
         epochs = n_iters // n_batches
         return epochs