minor style fixes (stanfordnlp#1921)

dspy/datasets/hotpotqa.py

@@ -6,62 +6,71 @@
 
 
 class HotPotQA(Dataset):
-    def __init__(self, *args, only_hard_examples=True, keep_details='dev_titles', unofficial_dev=True, **kwargs) -> None:
+    def __init__(
+        self,
+        *args,
+        only_hard_examples=True,
+        keep_details="dev_titles",
+        unofficial_dev=True,
+        **kwargs,
+    ) -> None:
         super().__init__(*args, **kwargs)
-        assert only_hard_examples, "Care must be taken when adding support for easy examples." \
-                                   "Dev must be all hard to match official dev, but training can be flexible."
-
-        hf_official_train = load_dataset("hotpot_qa", 'fullwiki', split='train', trust_remote_code=True)
-        hf_official_dev = load_dataset("hotpot_qa", 'fullwiki', split='validation', trust_remote_code=True)
+        assert only_hard_examples, (
+            "Care must be taken when adding support for easy examples."
+            "Dev must be all hard to match official dev, but training can be flexible."
+        )
+
+        hf_official_train = load_dataset("hotpot_qa", "fullwiki", split="train", trust_remote_code=True)
+        hf_official_dev = load_dataset("hotpot_qa", "fullwiki", split="validation", trust_remote_code=True)
 
         official_train = []
         for raw_example in hf_official_train:
-            if raw_example['level'] == 'hard':
+            if raw_example["level"] == "hard":
                 if keep_details is True:
-                    keys = ['id', 'question', 'answer', 'type', 'supporting_facts', 'context']
-                elif keep_details == 'dev_titles':
-                    keys = ['question', 'answer', 'supporting_facts']
+                    keys = ["id", "question", "answer", "type", "supporting_facts", "context"]
+                elif keep_details == "dev_titles":
+                    keys = ["question", "answer", "supporting_facts"]
                 else:
-                    keys = ['question', 'answer']
+                    keys = ["question", "answer"]
 
                 example = {k: raw_example[k] for k in keys}
-                
-                if 'supporting_facts' in example:
-                    example['gold_titles'] = set(example['supporting_facts']['title'])
-                    del example['supporting_facts']
+
+                if "supporting_facts" in example:
+                    example["gold_titles"] = set(example["supporting_facts"]["title"])
+                    del example["supporting_facts"]
 
                 official_train.append(example)
 
         rng = random.Random(0)
         rng.shuffle(official_train)
 
-        self._train = official_train[:len(official_train)*75//100]
+        self._train = official_train[: len(official_train) * 75 // 100]
 
         if unofficial_dev:
-            self._dev = official_train[len(official_train)*75//100:]
+            self._dev = official_train[len(official_train) * 75 // 100 :]
         else:
             self._dev = None
 
         for example in self._train:
-            if keep_details == 'dev_titles':
-                del example['gold_titles']
-        
+            if keep_details == "dev_titles":
+                del example["gold_titles"]
+
         test = []
         for raw_example in hf_official_dev:
-            assert raw_example['level'] == 'hard'
-            example = {k: raw_example[k] for k in ['id', 'question', 'answer', 'type', 'supporting_facts']}
-            if 'supporting_facts' in example:
-                example['gold_titles'] = set(example['supporting_facts']['title'])
-                del example['supporting_facts']
+            assert raw_example["level"] == "hard"
+            example = {k: raw_example[k] for k in ["id", "question", "answer", "type", "supporting_facts"]}
+            if "supporting_facts" in example:
+                example["gold_titles"] = set(example["supporting_facts"]["title"])
+                del example["supporting_facts"]
             test.append(example)
 
         self._test = test
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     from dsp.utils import dotdict
 
-    data_args = dotdict(train_seed=1, train_size=16, eval_seed=2023, dev_size=200*5, test_size=0)
+    data_args = dotdict(train_seed=1, train_size=16, eval_seed=2023, dev_size=200 * 5, test_size=0)
     dataset = HotPotQA(**data_args)
 
     print(dataset)

dspy/datasets/math.py

@@ -1,12 +1,13 @@
-import re
 import random
+import re
 
 
 class MATH:
     def __init__(self, subset):
-        import dspy
         from datasets import load_dataset
 
+        import dspy
+
         ds = load_dataset("lighteval/MATH", subset)
 
         # NOTE: Defaults to sub-splitting MATH's 'test' split into train/dev/test, presuming that current
@@ -21,7 +22,7 @@ def __init__(self, subset):
 
         size = min(350, len(dataset) // 3)
         random.Random(0).shuffle(dataset)
-        self.train, self.dev, self.test = dataset[:size], dataset[size:2*size], dataset[2*size:]
+        self.train, self.dev, self.test = dataset[:size], dataset[size : 2 * size], dataset[2 * size :]
 
     def metric(self, example, pred, trace=None):
         try:
@@ -36,7 +37,7 @@ def extract_answer(s):
     start = s.find("\\boxed{")
     if start == -1:
         return None
-    
+
     idx = start + len("\\boxed{")
     brace_level = 1