[minor] Add DatatypeHelper func to split data by fold

parlai/utils/data.py

@@ -115,20 +115,15 @@ def is_streaming(cls, datatype: str) -> bool:
         return 'stream' in datatype
 
     @classmethod
-    def split_domains_by_fold(
+    def split_data_by_fold(
         cls,
         fold: str,
-        domains: List[List],
+        data: List,
         train_frac: float,
         valid_frac: float,
         test_frac: float,
         seed: int = 42,
     ):
-        """
-        Need to be careful about how we setup random to not leak examples between trains
-        if we're in a scenario where a single dataset has different ways of mixing +
-        matching subcomponents.
-        """
         assert train_frac + valid_frac + test_frac == 1
         if "train" in fold:
             start = 0.0
@@ -140,9 +135,30 @@ def split_domains_by_fold(
             start = train_frac + valid_frac
             end = 1.0
 
+        random.Random(seed).shuffle(data)
+        return data[int(start * len(data)) : int(end * len(data))]
+
+    @classmethod
+    def split_domains_by_fold(
+        cls,
+        fold: str,
+        domains: List[List],
+        train_frac: float,
+        valid_frac: float,
+        test_frac: float,
+        seed: int = 42,
+    ):
+        """
+        Need to be careful about how we setup random to not leak examples between trains
+        if we're in a scenario where a single dataset has different ways of mixing +
+        matching subcomponents.
+        """
         result = []
         for domain in domains:
-            random.Random(seed).shuffle(domain)
-            result.extend(domain[int(start * len(domain)) : int(end * len(domain))])
+            result.extend(
+                cls.split_data_by_fold(
+                    fold, domain, train_frac, valid_frac, test_frac, seed
+                )
+            )
         random.Random(seed).shuffle(result)
         return result