removing tqdm logging

perplexity.py

@@ -20,7 +20,6 @@ from torch.nn import CrossEntropyLoss
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 import evaluate
-from evaluate import logging
 
 
 _CITATION = """\
@@ -161,7 +160,7 @@ class Perplexity(evaluate.Metric):
         ppls = []
         loss_fct = CrossEntropyLoss(reduction="none")
 
-        for start_index in logging.tqdm(range(0, len(encoded_texts), batch_size)):
+        for start_index in range(0, len(encoded_texts), batch_size):
             end_index = min(start_index + batch_size, len(encoded_texts))
             encoded_batch = encoded_texts[start_index:end_index]
             attn_mask = attn_masks[start_index:end_index]