fix doc

egs/audioset/AT/zipformer/train.py

@@ -40,7 +40,6 @@ from pathlib import Path
 from shutil import copyfile
 from typing import Any, Dict, List, Optional, Tuple, Union
 
-import k2
 import optim
 import sentencepiece as spm
 import torch
@@ -659,15 +658,12 @@ def compute_loss(
     warm_step = params.warm_step
 
     with torch.set_grad_enabled(is_training):
-        audio_tagging_loss = model(
+        loss = model(
             x=feature,
             x_lens=feature_lens,
             target=labels,
         )
 
-        loss = 0.0
-        loss += audio_tagging_loss
-
     assert loss.requires_grad == is_training
 
     info = MetricsTracker()
@@ -677,14 +673,13 @@ def compute_loss(
 
     # Note: We use reduction=sum while computing the loss.
     info["loss"] = loss.detach().cpu().item()
-    info["audio_tagging_loss"] = audio_tagging_loss.detach().cpu().item()
 
     return loss, info
 
 
 def str2multihot(events: List[str], n_classes=527, id_mapping=None):
     # Convert strings separated by semi-colon to multi-hot class labels
-    # input: ["1;2", "2;3"]
+    # input: ["0;1", "1;2"]
     # output: torch.tensor([[1,1,0], [0,1,1]])
     labels = [list(map(int, event.split(";"))) for event in events]
     batch_size = len(labels)