update comments in evaluate.py

egs/audioset/AT/zipformer/evaluate.py

@@ -17,13 +17,11 @@
 """
 Usage:
 
-export CUDA_VISIBLE_DEVICES="0,1,2,3"
-
+export CUDA_VISIBLE_DEVICES="0"
 
 ./zipformer/evaluate.py \
-  --num-epochs 50 \
-  --start-epoch 10 \
-  --use-fp16 1 \
+  --epoch 50 \
+  --avg 10 \
   --exp-dir zipformer/exp \
   --max-duration 1000
 
@@ -47,7 +45,11 @@ import torch.nn as nn
 import torch.nn.functional as F
 from at_datamodule import AudioSetATDatamodule
 from lhotse import load_manifest
-from sklearn.metrics import average_precision_score
+
+try:
+    from sklearn.metrics import average_precision_score
+except Exception as ex:
+    raise RuntimeError(f"{ex}\nPlease run\n" "pip3 install -U scikit-learn")
 from train import add_model_arguments, get_model, get_params, str2multihot
 
 from icefall.checkpoint import (
@@ -130,7 +132,7 @@ def inference_one_batch(
 ):
     device = next(model.parameters()).device
     feature = batch["inputs"]
-    assert feature.ndim == 3
+    assert feature.ndim == 3, feature.shape
 
     feature = feature.to(device)
     # at entry, feature is (N, T, C)
@@ -138,7 +140,7 @@ def inference_one_batch(
     supervisions = batch["supervisions"]
     audio_event = supervisions["audio_event"]
 
-    label, orig_labels = str2multihot(audio_event)
+    label, _ = str2multihot(audio_event)
     label = label.detach().cpu()
 
     feature_lens = supervisions["num_frames"].to(device)