From 416a7d9697b7e378ab10870825249ad202075671 Mon Sep 17 00:00:00 2001 From: Daniel Maddern Date: Thu, 13 Aug 2026 14:58:04 +0700 Subject: [PATCH] Compare H3 sampler pre-step states --- tools/compare_fl2va_steps.py | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/tools/compare_fl2va_steps.py b/tools/compare_fl2va_steps.py index 56dee76..f70ff60 100644 --- a/tools/compare_fl2va_steps.py +++ b/tools/compare_fl2va_steps.py @@ -21,15 +21,15 @@ text = H3TokenRefiner(checkpoint)(Qwen3VLPromptConditioner("/text-encoders/qwen3 model = H3PackedDenoiser.from_checkpoint(checkpoint, attention_backend="sage2").eval() packer = H3PromptPacker(checkpoint) -packed_initial = initial["initial_x"].to("cuda").reshape(-1) video_shape = (1, 24, 7, 12, 20) audio_shape = (1, 32, 2, 37) video_count = torch.tensor(video_shape).prod().item() -video = packed_initial[:video_count].reshape(video_shape) -audio_carried = packed_initial[video_count:].reshape(audio_shape) old_video = old_audio = old_sigma = None for index, reference in enumerate(steps): sigma, sigma_down = sigmas[index], sigmas[index + 1] + packed_state = reference["x"].to("cuda").reshape(-1) + video = packed_state[:video_count].reshape(video_shape) + audio_carried = packed_state[video_count:].reshape(audio_shape) native_audio = audio_carried * (_audio_sigma(sigma) / sigma) hidden, times, segments, positions, video_segment, audio_segment = packer(text, video, native_audio, float(sigma)) raw_video, raw_audio = model(hidden, times, positions, segments, video_segment, audio_segment) @@ -44,7 +44,11 @@ for index, reference in enumerate(steps): previous_sigma = sigmas[index - 1] if index else None video = res_multistep_update(video, denoised[0], sigma, sigma_down, old_video, old_sigma, previous_sigma) audio_carried = res_multistep_update(audio_carried, denoised[1], sigma, sigma_down, old_audio, old_sigma, previous_sigma) - reference_latent = reference["x"].to("cuda").reshape(-1)[:video_count].reshape(video_shape) - latent_delta = (video.float() - reference_latent.float()).abs() - print(f"step={index:02d} x0_video_mean={denoised_delta.mean().item():.6g} x0_video_max={denoised_delta.max().item():.6g} latent_video_mean={latent_delta.mean().item():.6g} latent_video_max={latent_delta.max().item():.6g}") + if index + 1 < len(steps): + reference_latent = steps[index + 1]["x"].to("cuda").reshape(-1)[:video_count].reshape(video_shape) + latent_delta = (video.float() - reference_latent.float()).abs() + latent_text = f"latent_video_mean={latent_delta.mean().item():.6g} latent_video_max={latent_delta.max().item():.6g}" + else: + latent_text = "latent_video_mean=final-unobserved latent_video_max=final-unobserved" + print(f"step={index:02d} x0_video_mean={denoised_delta.mean().item():.6g} x0_video_max={denoised_delta.max().item():.6g} {latent_text}") old_video, old_audio, old_sigma = denoised[0], denoised[1], sigma_down