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hao-ai-lab-FastVideo/examples/inference/basic/v2_basic_self_forcing_causal.py
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SolitaryThinker 3541e81d66 [feat] v2 VideoGenerator: convenience API (from_pretrained/generate_video) + porting roadmap
- VideoGenerator gains the convenience surface most basic examples use: from_pretrained(model,
  num_gpus/*_cpu_offload/...) and generate_video(prompt, sampling_param=, **kwargs) -> result, on top
  of the typed from_config/generate. Accepts SamplingParam.
- v2 examples matching the upstream convenience-API examples for the verified models: v2_basic.py
  (Wan2.1) and v2_basic_self_forcing_causal.py (SF-causal).
- V2_PORTING_STATUS.md: honest per-family roadmap. Working: wan21, wan_causal, ltx2-distilled. Each
  further model needs per-model work (FastWan: WanDMD to_gate_compress param mapping; TurboWan: RCM
  consistency sampler; Wan2.2: MoE card; LTX2 base/i2v; new families: new cards/adapters; gated Flux2 /
  local GEN3C / audio StableAudio / interactive MatrixGame blocked in this env).
2026-07-04 17:15:34 +00:00

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Python

"""v2 port of basic_self_forcing_causal.py — SF-causal Wan2.1 (CausalWanTransformer3DModel) through
the v2 VideoGenerator (chunk_rollout loop).
Same convenience API as upstream; only delta is importing VideoGenerator from v2. NOTE: the v2 causal
loop runs per-chunk few-step (not the upstream kv-cache streaming + SF schedule), so output is coherent
but lower-fidelity (a documented gap). num_frames is set by the card's chunk schedule; height/width
drive the latent geometry.
"""
from v2 import VideoGenerator
from fastvideo.api.sampling_param import SamplingParam
OUTPUT_PATH = "v2_video_samples_causal"
def main() -> None:
model_name = "wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers"
generator = VideoGenerator.from_pretrained(
model_name, num_gpus=1, text_encoder_cpu_offload=False, dit_cpu_offload=False)
sampling_param = SamplingParam.from_pretrained(model_name)
prompt = ("A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes wide with "
"interest. The playful yet serene atmosphere is complemented by soft natural light "
"filtering through the petals. Mid-shot, warm and cheerful tones.")
video = generator.generate_video(prompt, output_path=OUTPUT_PATH, output_video_name="causal_raccoon",
save_video=True, sampling_param=sampling_param, height=480, width=832)
print(f"Output: {video.video_path}")
if __name__ == "__main__":
main()