refactor: Refactor code after review

Author: ktagowski

embeddings/pipeline/flair_hps_pipeline.py

@@ -1,4 +1,5 @@
 from abc import ABC
+from copy import deepcopy
 from dataclasses import dataclass, field
 from pathlib import Path
 from tempfile import TemporaryDirectory
@@ -73,6 +74,15 @@ class _OptimizedFlairPipelineDefaultsBase(_HuggingFaceOptimizedPipelineDefaultsB
         init=False, default_factory=TemporaryDirectory
     )
 
+    @staticmethod
+    def _revert_default_hps_task_train_kwargs(
+        task_train_kwargs: Dict[str, ParameterValues]
+    ) -> Dict[str, ParameterValues]:
+        out = deepcopy(task_train_kwargs)
+        out["param_selection_mode"] = False
+        out["save_final_model"] = True
+        return out
+
 
 # Mypy currently properly don't handle dataclasses with abstract methods  https://github.com/python/mypy/issues/5374
 @dataclass  # type: ignore
@@ -104,14 +114,6 @@ def _pop_sampled_parameters(
         assert isinstance(load_model_kwargs, dict)
         return embedding_name, document_embedding, task_train_kwargs, load_model_kwargs
 
-    @staticmethod
-    def _revert_default_hps_task_train_kwargs(
-        task_train_kwargs: Dict[str, ParameterValues]
-    ) -> Dict[str, ParameterValues]:
-        task_train_kwargs["param_selection_mode"] = False
-        task_train_kwargs["save_final_model"] = True
-        return task_train_kwargs
-
 
 @dataclass
 class OptimizedFlairClassificationPipeline(
@@ -396,14 +398,6 @@ def _pop_sampled_parameters(
         assert isinstance(task_model_kwargs, dict)
         return embedding_name, hidden_size, task_train_kwargs, task_model_kwargs
 
-    @staticmethod
-    def _revert_default_hps_task_train_kwargs(
-        task_train_kwargs: Dict[str, ParameterValues]
-    ) -> Dict[str, ParameterValues]:
-        task_train_kwargs["param_selection_mode"] = False
-        task_train_kwargs["save_final_model"] = True
-        return task_train_kwargs
-
     def _get_metadata(self, parameters: SampledParameters) -> FlairSequenceLabelingPipelineMetadata:
         (
             embedding_name,

embeddings/pipeline/flair_preprocessing_pipeline.py

@@ -85,7 +85,7 @@ def _get_persister(self) -> FLAIR_PERSISTERS_TYPE:
     def _get_dataset(self) -> Dataset:
         return Dataset(
             self.dataset_name_or_path,
-            **self.load_dataset_kwargs if self.load_dataset_kwargs else {}
+            **self.load_dataset_kwargs if self.load_dataset_kwargs else {},
         )
 
     def _get_dataloader(self, dataset: Dataset) -> FLAIR_DATALOADERS:
@@ -130,7 +130,7 @@ def _get_transformations(
                 DownsampleFlairCorpusTransformation(
                     *self.downsample_splits,
                     stratify=self.downsample_splits_stratification,
-                    seed=self.seed
+                    seed=self.seed,
                 )
             )