fix issue with truncated_tokens_count huggingface#2

Author: guipenedo

src/lighteval/models/dummy_model.py

@@ -66,18 +66,17 @@ def greedy_until(self, requests: list[GreedyUntilRequest], override_bs: Optional
 
     def loglikelihood(self, requests: list[LoglikelihoodRequest], override_bs: Optional[int] = None) -> list[
         LoglikelihoodReturn]:
-        return [LoglikelihoodReturn((-random.random(), False), truncated_tokens_count=0, padded_tokens_count=0)
+        return [LoglikelihoodReturn((-random.random(), False))
                 for _ in requests]
 
     def loglikelihood_rolling(self, requests: list[LoglikelihoodRollingRequest], override_bs: Optional[int] = None) -> \
             list[LoglikelihoodReturn]:
-        return [LoglikelihoodReturn((-random.random(), False), truncated_tokens_count=0, padded_tokens_count=0)
+        return [LoglikelihoodReturn((-random.random(), False))
                 for _ in requests]
 
     def loglikelihood_single_token(self, requests: list[LoglikelihoodSingleTokenRequest],
                                    override_bs: Optional[int] = None) -> list[LoglikelihoodSingleTokenReturn]:
         return [
-            LoglikelihoodSingleTokenReturn(result=[-random.random() for _ in req.tokenized_continuation],
-                                           truncated_tokens_count=0, padded_tokens_count=0)
+            LoglikelihoodSingleTokenReturn(result=[-random.random() for _ in req.tokenized_continuation])
             for req in requests
         ]

src/lighteval/models/model_output.py

@@ -31,8 +31,8 @@ class ModelReturn:
     result: Union[tuple, list, str]
     input_tokens: list[int] = field(default_factory=list)  # model inputs
     generated_tokens: list[int] = field(default_factory=list)  # model generations
-    truncated_tokens_count: Optional[int] = None  # How many tokens truncated
-    padded_tokens_count: Optional[int] = None  # How many tokens of padding
+    truncated_tokens_count: Optional[int] = 0  # How many tokens truncated
+    padded_tokens_count: Optional[int] = 0  # How many tokens of padding
 
     def get_result_for_eval(self):
         raise NotImplementedError()