fix mutual info normalization

lm_eval/api/task.py

@@ -52,7 +52,6 @@ class TaskConfig(dict):
 
     task: str = None
     group: Union[str, list] = None
-    reference: str = None
 
     dataset_path: str = None
     dataset_name: str = None
@@ -67,6 +66,8 @@ class TaskConfig(dict):
     doc_to_target: Union[Callable, str] = None
     use_prompt: str = None
     description: str = ""
+    target_delimiter: str = " "
+    fewshot_delimiter: str = "\n\n"
 
     num_fewshot: int = 0
     batch_size: int = 1
@@ -76,8 +77,6 @@ class TaskConfig(dict):
     gold_alias: Union[Callable, str] = None
     output_type: str = "greedy_until"
     generation_kwargs: dict = None
-    target_delimiter: str = " "
-    fewshot_delimiter: str = "\n\n"
     filter_list: Union[str, list] = None
     should_decontaminate: bool = False
     doc_to_decontamination_query: str = None
@@ -343,7 +342,7 @@ class Task(abc.ABC):
             fewshot_ctx = self.fewshot_context(
                 doc, self._config.num_fewshot, rnd=random.Random()
             )
-            # TODO: hardcoded for now: # of runs on each input to be 2. # TODO: we should override this if doing greedy gen so users don't waste time+compute
+            # TODO: we should override this if doing greedy gen so users don't waste time+compute
             inst = self.construct_requests(
                 doc=doc,
                 ctx=fewshot_ctx,
@@ -773,7 +772,7 @@ class ConfigurableTask(Task):
                         Instance(
                             request_type="loglikelihood",
                             doc=doc,
-                            arguments=("", "{}".format(choice)),
+                            arguments=("", " {}".format(choice)),
                             idx=i,
                             **kwargs,
                         )