Merge branch 'k2-fsa:master' into dev/k2ssl

egs/librispeech/ASR/zipformer/model.py

@@ -22,10 +22,10 @@
 import torch
 import torch.nn as nn
 from encoder_interface import EncoderInterface
+from lhotse.dataset import SpecAugment
 from scaling import ScaledLinear
 
 from icefall.utils import add_sos, make_pad_mask, time_warp
-from lhotse.dataset import SpecAugment
 
 
 class AsrModel(nn.Module):

egs/speech_llm/ASR_LLM/whisper_llm_zh/label_smoothing.py

@@ -0,0 +1 @@
+../../../librispeech/ASR/conformer_ctc/label_smoothing.py

icefall/utils.py

@@ -2282,13 +2282,12 @@ def time_warp(
     time_warp_factor: Optional[int] = 80,
     supervision_segments: Optional[torch.Tensor] = None,
 ):
-    """Apply time warping on a batch of features
-    """
+    """Apply time warping on a batch of features"""
     if time_warp_factor is None or time_warp_factor < 1:
         return features
-    assert len(features.shape) == 3, (
-        "SpecAugment only supports batches of single-channel feature matrices."
-    )
+    assert (
+        len(features.shape) == 3
+    ), f"SpecAugment only supports batches of single-channel feature matrices. {features.shape}"
     features = features.clone()
     if supervision_segments is None:
         # No supervisions - apply spec augment to full feature matrices.