24 lines
1.3 KiB
Python
24 lines
1.3 KiB
Python
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"""Run one direct FL2VA H3 denoiser call from raw prompt conditioning."""
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import torch
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from h3_blackwell_runtime.checkpoint import H3Checkpoint
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from h3_blackwell_runtime.denoiser import H3PackedDenoiser
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from h3_blackwell_runtime.packing import H3PromptPacker
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from h3_blackwell_runtime.qwen3vl_text import Qwen3VLPromptConditioner
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from h3_blackwell_runtime.t2v import empty_av_latents
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prompt = "A brass-and-paper dragon flies above a rain-washed old city at blue hour."
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text_encoder = Qwen3VLPromptConditioner("/text-encoders/qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors", "/opt/h3-blackwell-runtime/qwen25_tokenizer")
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checkpoint = H3Checkpoint("/models/minimax_h3_fl2va_pruned_nvfp4.safetensors")
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video, audio, _ = empty_av_latents(960, 544, 124)
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video.normal_()
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text = text_encoder(prompt)
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hidden, timesteps, segments, positions, video_segment, audio_segment = H3PromptPacker(checkpoint)(text, video, audio, 1.0)
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model = H3PackedDenoiser.from_checkpoint(checkpoint).eval()
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with torch.inference_mode():
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velocity_video, velocity_audio = model(hidden, timesteps, positions, segments, video_segment, audio_segment)
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torch.cuda.synchronize()
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print({"video": tuple(velocity_video.shape), "audio": tuple(velocity_audio.shape), "finite": torch.isfinite(velocity_video).all().item() and torch.isfinite(velocity_audio).all().item()})
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