33 lines
1.2 KiB
Python
33 lines
1.2 KiB
Python
"""Run the direct H3 core against one matched ComfyUI capture."""
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import time
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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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capture_dir = "/artifacts/capture"
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inputs = torch.load(f"{capture_dir}/input.pt", map_location="cuda", weights_only=False)
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expected = torch.load(f"{capture_dir}/output.pt", map_location="cuda", weights_only=False)
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checkpoint = H3Checkpoint("/models/minimax_h3_ref2va_pruned_nvfp4.safetensors")
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start = time.perf_counter()
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model = H3PackedDenoiser.from_checkpoint(checkpoint).eval()
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with torch.inference_mode():
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video, audio = model(
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inputs["hidden"],
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inputs["timesteps"],
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inputs["position_ids"],
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inputs["segments"],
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expected["video_segment"],
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expected["audio_segment"],
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)
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torch.cuda.synchronize()
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for name, actual, reference in (("video", video, expected["video"]), ("audio", audio, expected["audio"])):
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reference = reference.reshape_as(actual)
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delta = (actual.float() - reference.float()).abs()
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print(f"{name} shape={tuple(actual.shape)} max_abs={delta.max().item():.6g} mean_abs={delta.mean().item():.6g}")
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print(f"elapsed_s={time.perf_counter() - start:.3f}")
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