Merge pull request #952 from EleutherAI/fixup-logging

[Refactor] Logging fixes

lm_eval/evaluator.py

@@ -2,7 +2,6 @@ import random
 import itertools
 import json
 import collections
-import logging
 import sys
 
 import torch
@@ -25,10 +24,6 @@ from lm_eval.utils import (
 
 from lm_eval.logger import eval_logger
 
-logger = logging.getLogger(__name__)
-logger.setLevel(logging.INFO)
-logger.addHandler(logging.StreamHandler(sys.stdout))
-
 
 @positional_deprecated
 def simple_evaluate(

lm_eval/models/huggingface.py

@@ -675,7 +675,8 @@ class HFLM(LM):
             else None,
         )
 
-        for chunk in tqdm(chunks, disable=(disable_tqdm or (self.rank != 0))):
+        pbar = tqdm(total=len(requests), disable=(disable_tqdm or (self.rank != 0)))
+        for chunk in chunks:
             inps = []
             cont_toks_list = []
             inplens = []
@@ -812,6 +813,9 @@ class HFLM(LM):
                 res.append(answer)
 
                 self.cache_hook.add_partial("loglikelihood", cache_key, answer)
+                pbar.update(1)
+
+        pbar.close()
 
         return re_ord.get_original(res)
 
@@ -857,7 +861,7 @@ class HFLM(LM):
                 if self.batch_size == "auto" and not adaptive_batch_size
                 else None,
             )
-            for chunk in tqdm(chunks, disable=self.rank != 0):
+            for chunk in chunks:
                 contexts, all_gen_kwargs = zip(*chunk)
                 # we assume all gen kwargs in the batch are the same
                 # this is safe to assume because the `grouper` object ensures it.