Merge pull request #216 from CustomProgrammingSolutions/refactor-kwargs

[MRG] Make optional arguments keyword args

persephone/corpus.py

@@ -114,8 +114,10 @@ class Corpus:
     """
 
     def __init__(self, feat_type: str, label_type: str, tgt_dir: Path,
+                 *,
                  labels: Optional[Set[str]] = None,
-                 max_samples:int=1000, speakers: Optional[Sequence[str]] = None) -> None:
+                 max_samples: int=1000,
+                 speakers: Optional[Sequence[str]] = None) -> None:
         """ Construct a `Corpus` instance from preprocessed data.
 
         Assumes that the corpus data has been preprocessed and is
@@ -235,6 +237,7 @@ def __init__(self, feat_type: str, label_type: str, tgt_dir: Path,
     @classmethod
     def from_elan(cls: Type[CorpusT], org_dir: Path, tgt_dir: Path,
                   feat_type: str = "fbank", label_type: str = "phonemes",
+                  *,
                   utterance_filter: Callable[[Utterance], bool] = None,
                   label_segmenter: Optional[LabelSegmenter] = None,
                   speakers: List[str] = None, lazy: bool = True,
@@ -461,7 +464,7 @@ def write_prefixes(prefixes: List[str], prefix_fn: Path) -> None:
                 print(prefix, file=prefix_f)
 
     @staticmethod
-    def divide_prefixes(prefixes: List[str], seed:int=0) -> Tuple[List[str], List[str], List[str]]:
+    def divide_prefixes(prefixes: List[str], *, seed:int=0) -> Tuple[List[str], List[str], List[str]]:
         """Divide data into training, validation and test subsets"""
         if len(prefixes) < 3:
             raise PersephoneException(

persephone/model.py

@@ -302,7 +302,7 @@ def output_best_scores(self, best_epoch_str: str) -> None:
                   "w", encoding=ENCODING) as best_f:
             print(best_epoch_str, file=best_f, flush=True)
 
-    def train(self, early_stopping_steps: int = 10, min_epochs: int = 30,
+    def train(self, *, early_stopping_steps: int = 10, min_epochs: int = 30,
               max_valid_ler: float = 1.0, max_train_ler: float = 0.3,
               max_epochs: int = 100, restore_model_path: Optional[str]=None,
               epoch_callback: Optional[Callable[[Dict], None]]=None) -> None:

persephone/tests/experiments/test_na.py

@@ -86,7 +86,7 @@ def test_tutorial():
 
     # Test the first setup encouraged in the tutorial
     labels = corpus.determine_labels(Path(na_example_dir), "phonemes")
-    corp = corpus.Corpus("fbank", "phonemes", Path(na_example_dir), labels)
+    corp = corpus.Corpus("fbank", "phonemes", Path(na_example_dir), labels=labels)
 
     exp_dir = experiment.train_ready(corp, directory=EXP_BASE_DIR)
 
@@ -111,7 +111,7 @@ def test_fast():
 
     labels = corpus.determine_labels(Path(tiny_example_dir), "phonemes")
 
-    corp = corpus.Corpus("fbank", "phonemes", Path(tiny_example_dir), labels)
+    corp = corpus.Corpus("fbank", "phonemes", Path(tiny_example_dir), labels=labels)
     exp_dir = experiment.prep_exp_dir(directory=EXP_BASE_DIR)
     model = experiment.get_simple_model(exp_dir, corp)
     model.train(min_epochs=2, max_epochs=5)