add parameter set_batch_size_to_split_size to DatasetDict.map (#155)

* implement set_batch_size_to_split_size

* improve docstring

* add test

src/pie_datasets/core/dataset_dict.py

@@ -348,6 +348,7 @@ def map(  # type: ignore
         self,
         function: Optional[Union[Callable, str]] = None,
         result_document_type: Optional[Union[str, Type[Document]]] = None,
+        set_batch_size_to_split_size: bool = False,
         **kwargs,
     ) -> "DatasetDict":
         """Applies a function to all documents in the dataset.
@@ -370,6 +371,9 @@ def map(  # type: ignore
                 string that can be resolved to such a type. If not provided, it is tried to infer it from the
                 function signature. If this is not possible, the document type of the input dataset
                 is used.
+            set_batch_size_to_split_size: If enabled, set the batch_size to the size of the respective split
+                when calling map() on it. This is useful to transform whole splits when using it in
+                combination with batched=True.
             **kwargs: additional keyword arguments for `datasets.Dataset.map()`
         """
 
@@ -395,6 +399,8 @@ def identity(x):
         for split, dataset in self.items():
             if isinstance(func, EnterDatasetMixin):
                 func.enter_dataset(dataset=dataset, name=split)
+            if set_batch_size_to_split_size:
+                map_kwargs["batch_size"] = len(dataset)
             result_dict[split] = dataset.map(**map_kwargs)
             if isinstance(func, ExitDatasetMixin):
                 func.exit_dataset(dataset=result_dict[split], name=split)

tests/unit/core/test_dataset_dict.py

@@ -280,6 +280,25 @@ def exit_dataset_dict(self, dataset_dict: DatasetDict) -> None:
             assert doc1 == doc2
 
 
+def test_map_set_max_batch_size(dataset_dict):
+    def join_docs(docs):
+        return [TextBasedDocument(text=" ".join([doc.text for doc in docs]))]
+
+    dataset_dict_mapped = dataset_dict.map(
+        join_docs,
+        batched=True,
+        set_batch_size_to_split_size=True,
+        result_document_type=TextBasedDocument,
+    )
+    assert dataset_dict_mapped.document_type is TextBasedDocument
+    for split in dataset_dict:
+        assert len(dataset_dict_mapped[split]) == 1
+        new_doc = dataset_dict_mapped[split][0]
+        assert isinstance(new_doc, TextBasedDocument)
+        original_texts = [doc.text for doc in dataset_dict[split]]
+        assert new_doc.text == " ".join(original_texts)
+
+
 def test_select(dataset_dict):
     # select documents by index
     dataset_dict_selected = dataset_dict.select(