Merge branch 'master' into dr-support-pip-cm

Author: ltdrdata

comfy_api/latest/_ui.py

@@ -9,7 +9,11 @@
 import av
 import numpy as np
 import torch
-import torchaudio
+try:
+    import torchaudio
+    TORCH_AUDIO_AVAILABLE = True
+except ImportError:
+    TORCH_AUDIO_AVAILABLE = False
 from PIL import Image as PILImage
 from PIL.PngImagePlugin import PngInfo
 
@@ -302,6 +306,8 @@ def save_audio(
 
                 # Resample if necessary
                 if sample_rate != audio["sample_rate"]:
+                    if not TORCH_AUDIO_AVAILABLE:
+                        raise Exception("torchaudio is not available; cannot resample audio.")
                     waveform = torchaudio.functional.resample(waveform, audio["sample_rate"], sample_rate)
 
             # Create output with specified format

nodes.py

@@ -1232,12 +1232,12 @@ def repeat(self, samples, amount):
         s = samples.copy()
         s_in = samples["samples"]
 
-        s["samples"] = s_in.repeat((amount, 1,1,1))
+        s["samples"] = s_in.repeat((amount,) + ((1,) * (s_in.ndim - 1)))
         if "noise_mask" in samples and samples["noise_mask"].shape[0] > 1:
             masks = samples["noise_mask"]
             if masks.shape[0] < s_in.shape[0]:
-                masks = masks.repeat(math.ceil(s_in.shape[0] / masks.shape[0]), 1, 1, 1)[:s_in.shape[0]]
-            s["noise_mask"] = samples["noise_mask"].repeat((amount, 1,1,1))
+                masks = masks.repeat((math.ceil(s_in.shape[0] / masks.shape[0]),) + ((1,) * (masks.ndim - 1)))[:s_in.shape[0]]
+            s["noise_mask"] = samples["noise_mask"].repeat((amount,) + ((1,) * (samples["noise_mask"].ndim - 1)))
         if "batch_index" in s:
             offset = max(s["batch_index"]) - min(s["batch_index"]) + 1
             s["batch_index"] = s["batch_index"] + [x + (i * offset) for i in range(1, amount) for x in s["batch_index"]]