Removing logging bug

src/leaderboard/read_evals.py

@@ -11,10 +11,7 @@ from src.display.formatting import make_clickable_model
 from src.display.utils import AutoEvalColumn, ModelType, Tasks, Precision, WeightType
 from src.submission.check_validity import is_model_on_hub
 
-from src.logging import setup_logger, log_file
-
 logging.basicConfig(level=logging.DEBUG)
-logger = setup_logger(__name__)
 
 
 @dataclass
@@ -75,13 +72,13 @@ class EvalResult:
         results = {}
         for task in Tasks:
             task = task.value
-            logger.info("Task: %s" % task.metric)
-            logger.info(data["results"].items())
+            logging.info("Task: %s" % task.metric)
+            logging.info(data["results"].items())
             # We average all scores of a given metric (not all metrics are present in all files)
             # This looks a bit odd, should just be the one score in the one file. (?)
             scores = np.array([v.get(task.metric, None) for k, v in data["results"].items() if task.benchmark == k])
-            logger.info("scores are:")
-            logger.info(scores)
+            logging.info("scores are:")
+            logging.info(scores)
             if scores.size == 0 or any([score is None for score in scores]):
                 continue
 
@@ -114,7 +111,7 @@ class EvalResult:
             self.num_params = request.get("params", 0)
             self.date = request.get("submitted_time", "")
         except Exception:
-            logger.error(f"Could not find request file for {self.org}/{self.model}") #with precision {self.precision.value.name}")
+            logging.error(f"Could not find request file for {self.org}/{self.model}") #with precision {self.precision.value.name}")
 
     def to_dict(self):
         """Converts the Eval Result to a dict compatible with our dataframe display"""
@@ -166,8 +163,8 @@ def get_request_file_for_model(requests_path, model_name, precision):
 def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResult]:
     """From the path of the results folder root, extract all needed info for results"""
     model_result_filepaths = []
-    logger.debug('looking in results_path: %s' % results_path)
-    logger.debug('looking in requests_path: %s' % requests_path)
+    logging.debug('looking in results_path: %s' % results_path)
+    logging.debug('looking in requests_path: %s' % requests_path)
     for root, _, files in os.walk(results_path):
         # We should only have json files in model results
         if len(files) == 0 or any([not f.endswith(".json") for f in files]):
@@ -184,8 +181,8 @@ def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResu
 
     eval_results = {}
     for model_result_filepath in model_result_filepaths:
-        logger.debug("Examining filepath:")
-        logger.debug(model_result_filepath)
+        logging.debug("Examining filepath:")
+        logging.debug(model_result_filepath)
         # Creation of result
         eval_result = EvalResult.init_from_json_file(model_result_filepath)
         eval_result.update_with_request_file(requests_path)
@@ -196,8 +193,8 @@ def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResu
             eval_results[eval_name].results.update({k: v for k, v in eval_result.results.items() if v is not None})
         else:
             eval_results[eval_name] = eval_result
-    logger.info("eval results is")
-    logger.info(eval_results)
+    logging.info("eval results is")
+    logging.info(eval_results)
 
     results = []
     for v in eval_results.values():