init

local_coh_ppl.py

@@ -215,16 +215,13 @@ class LocalCohPPL(evaluate.Measurement):
             for pred in batch_sents:
                 ss = pred.split("\n")
                 sslens = [len(tokenizer(y,add_special_tokens=False,padding=False).input_ids) for y in ss]
-                offset = 0
+                offset = int(add_start_token)
                 sspos = [offset]
                 for sslen in sslens:
                     offset = min(offset + sslen,511)
                     sspos.append(offset)
                 sent_tok_lens.append(sspos)
 
-            print("[compute ppl] check ...")
-            pdb.set_trace()
-
             labels = encoded_texts
 
             with torch.no_grad():
@@ -232,7 +229,7 @@ class LocalCohPPL(evaluate.Measurement):
 
             shift_logits = out_logits[..., :-1, :].contiguous()
             shift_labels = labels[..., 1:].contiguous()
-            shift_attention_mask_batch = attn_mask[..., 1:].contiguous()
+            shift_attention_mask_batch = attn_masks[..., 1:].contiguous()
 
             loss_out = loss_fct(shift_logits.transpose(1, 2), shift_labels) * shift_attention_mask_batch
             perplexity_all = torch.exp(