From 88643f3978c79dc794c641c4a939f7899b60df39 Mon Sep 17 00:00:00 2001 From: ozbayb <17261091+ozbayb@users.noreply.github.com> Date: Tue, 7 Apr 2026 14:11:19 -0600 Subject: [PATCH] Fix logging of guide frame number --- comfy/context_windows.py | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/comfy/context_windows.py b/comfy/context_windows.py index 2723c77ff..964f7dd33 100644 --- a/comfy/context_windows.py +++ b/comfy/context_windows.py @@ -485,8 +485,6 @@ class IndexListContextHandler(ContextHandlerABC): is_multimodal = window_data.latent_shapes is not None and len(window_data.latent_shapes) > 1 primary_frames = window_data.tensor - num_guide_frames = window_data.guide_frames.size(self.dim) if window_data.guide_frames is not None else 0 - context_windows = self.get_context_windows(model, primary_frames, model_options) enumerated_context_windows = list(enumerate(context_windows)) total_windows = len(enumerated_context_windows) @@ -508,9 +506,6 @@ class IndexListContextHandler(ContextHandlerABC): for window_idx, window in enumerated_context_windows: comfy.model_management.throw_exception_if_processing_interrupted() - logging.info(f"Context window {window_idx + 1}/{total_windows}: frames {window.index_list[0]}-{window.index_list[-1]} of {primary_frames.shape[self.dim]}" - + (f" (+{num_guide_frames} guide frames)" if num_guide_frames > 0 else "") - + (f" [{len(latents)} modalities]" if is_multimodal else "")) # Per-modality window indices if is_multimodal: @@ -547,6 +542,9 @@ class IndexListContextHandler(ContextHandlerABC): sliced_primary, num_guide_frames = inject_guide_frames_into_window(sliced_video, window, window_data, self.dim) else: sliced_primary, num_guide_frames = sliced_video, 0 + logging.info(f"Context window {window_idx + 1}/{total_windows}: frames {window.index_list[0]}-{window.index_list[-1]} of {primary_frames.shape[self.dim]}" + + (f" (+{num_guide_frames} guide frames)" if num_guide_frames > 0 else "") + + (f" [{len(latents)} modalities]" if is_multimodal else "")) sliced = [sliced_primary] + [per_modality_windows_list[mi].get_tensor(latents[mi]) for mi in range(1, len(latents))] sub_x, sub_shapes = self._pack(sliced)