Gh3275: sample_missing_splits in SST-2

flair/data.py

@@ -1238,15 +1238,27 @@ def __init__(
 
         # sample test data from train if none is provided
         if test is None and sample_missing_splits and train and sample_missing_splits != "only_dev":
+            test_portion = 0.1
             train_length = _len_dataset(train)
-            test_size: int = round(train_length / 10)
+            test_size: int = round(train_length * test_portion)
             test, train = randomly_split_into_two_datasets(train, test_size)
+            log.warning(
+                "No test split found. Using %.0f%% (i.e. %d samples) of the train split as test data",
+                test_portion,
+                test_size,
+            )
 
         # sample dev data from train if none is provided
         if dev is None and sample_missing_splits and train and sample_missing_splits != "only_test":
+            dev_portion = 0.1
             train_length = _len_dataset(train)
-            dev_size: int = round(train_length / 10)
+            dev_size: int = round(train_length * dev_portion)
             dev, train = randomly_split_into_two_datasets(train, dev_size)
+            log.warning(
+                "No dev split found. Using %.0f%% (i.e. %d samples) of the train split as dev data",
+                dev_portion,
+                dev_size,
+            )
 
         # set train dev and test data
         self._train: Optional[Dataset[T_co]] = train

flair/datasets/document_classification.py

@@ -324,6 +324,7 @@ def __init__(
         skip_header: bool = False,
         encoding: str = "utf-8",
         no_class_label=None,
+        sample_missing_splits: Union[bool, str] = True,
         **fmtparams,
     ) -> None:
         """Instantiates a Corpus for text classification from CSV column formatted data.
@@ -396,7 +397,7 @@ def __init__(
             else None
         )
 
-        super().__init__(train, dev, test, name=name)
+        super().__init__(train, dev, test, name=name, sample_missing_splits=sample_missing_splits)
 
 
 class CSVClassificationDataset(FlairDataset):
@@ -1488,6 +1489,7 @@ def __init__(
         tokenizer: Tokenizer = SegtokTokenizer(),
         in_memory: bool = False,
         encoding: str = "utf-8",
+        sample_missing_splits: bool = True,
         **datasetargs,
     ) -> None:
         base_path = flair.cache_root / "datasets" if not base_path else Path(base_path)
@@ -1525,6 +1527,7 @@ def __init__(
             column_name_map={0: "text", 1: "label"},
             train_file=train_file,
             dev_file=data_folder / "dev.tsv",
+            sample_missing_splits=sample_missing_splits,
             **kwargs,
         )