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Add better error handling for a custom ar_video sampler.
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@@ -1817,21 +1817,37 @@ def sample_ar_video(model, x, sigmas, extra_args=None, callback=None, disable=No
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"""
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Autoregressive video sampler: block-by-block denoising with KV cache
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and flow-match re-noising for Causal Forcing / Self-Forcing models.
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Requires a Causal-WAN compatible model (diffusion_model must expose
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init_kv_caches / init_crossattn_caches) and 5-D latents [B,C,T,H,W].
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"""
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extra_args = {} if extra_args is None else extra_args
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model_options = extra_args.get("model_options", {})
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transformer_options = model_options.get("transformer_options", {})
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ar_config = transformer_options.get("ar_config", {})
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if x.ndim != 5:
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raise ValueError(
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f"ar_video sampler requires 5-D video latents [B,C,T,H,W], got {x.ndim}-D tensor with shape {x.shape}. "
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"This sampler is only compatible with autoregressive video models (e.g. Causal-WAN)."
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)
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inner_model = model.inner_model.inner_model
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causal_model = inner_model.diffusion_model
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if not (hasattr(causal_model, "init_kv_caches") and hasattr(causal_model, "init_crossattn_caches")):
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raise TypeError(
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"ar_video sampler requires a Causal-WAN compatible model whose diffusion_model "
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"exposes init_kv_caches() and init_crossattn_caches(). The loaded checkpoint "
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"does not support this interface — choose a different sampler."
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)
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num_frame_per_block = ar_config.get("num_frame_per_block", 1)
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seed = extra_args.get("seed", 0)
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bs, c, lat_t, lat_h, lat_w = x.shape
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frame_seq_len = -(-lat_h // 2) * -(-lat_w // 2) # ceiling division
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num_blocks = -(-lat_t // num_frame_per_block) # ceiling division
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inner_model = model.inner_model.inner_model
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causal_model = inner_model.diffusion_model
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device = x.device
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model_dtype = inner_model.get_dtype()
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