From 05df2df489f6b237f63c5f7d42a943ae2be417e9 Mon Sep 17 00:00:00 2001 From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com> Date: Thu, 7 Aug 2025 08:20:40 -0700 Subject: [PATCH 1/2] Fix RepeatLatentBatch not working on multi dim latents. (#9227) --- nodes.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/nodes.py b/nodes.py index 9bedbcaca..9448f9c1b 100644 --- a/nodes.py +++ b/nodes.py @@ -1229,12 +1229,12 @@ class RepeatLatentBatch: 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"]] From 42974a448c39af50c5f72d8c70267f9fe2971cd2 Mon Sep 17 00:00:00 2001 From: Jedrzej Kosinski Date: Thu, 7 Aug 2025 14:54:09 -0700 Subject: [PATCH 2/2] _ui.py import torchaudio safety check (#9234) * Added safety around torchaudio import in _ui.py * Trusted cursor too much, fixed torchaudio bool --- comfy_api/latest/_ui.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/comfy_api/latest/_ui.py b/comfy_api/latest/_ui.py index 6b8a39d58..61597038f 100644 --- a/comfy_api/latest/_ui.py +++ b/comfy_api/latest/_ui.py @@ -9,7 +9,11 @@ from typing import Type 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 @@ class AudioSaveHelper: # 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