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[refactor]: move examples to generate(request) and from_config

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Every example calls VideoGenerator.generate with a nested request instead
of generate_video keywords, and passes settings outside the from_pretrained
convenience keywords through VideoGenerator.from_config at their typed
paths. Each request and generator config equals what the keyword call built.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
This commit is contained in:
Davids048
2026-10-03 02:14:36 +00:00
co-authored by Claude Opus 5.5
parent 96b7c0d223
commit f571621ae7
66 changed files with 1514 additions and 1130 deletions
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examples/inference/basic/basic_flux_dev.py
+32 -31
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@@ -83,24 +83,23 @@ def main() -> None:
os.makedirs(args.out_dir, exist_ok=True)
init_kwargs = {
"num_gpus": args.num_gpus,
"workload_type": "t2i",
"sp_size": 1,
"tp_size": 1,
"dit_cpu_offload": False,
"dit_layerwise_offload": False,
"text_encoder_cpu_offload": False,
"vae_cpu_offload": False,
"image_encoder_cpu_offload": False,
"pin_cpu_memory": False,
"use_fsdp_inference": False,
}
generator = VideoGenerator.from_pretrained(
model_path=args.model_path,
**init_kwargs,
)
generator = VideoGenerator.from_config({
"model_path": args.model_path,
"engine": {
"num_gpus": args.num_gpus,
"parallelism": {"sp_size": 1, "tp_size": 1},
"offload": {
"dit": False,
"dit_layerwise": False,
"text_encoder": False,
"vae": False,
"image_encoder": False,
"pin_cpu_memory": False,
},
"use_fsdp_inference": False,
},
"pipeline": {"workload_type": "t2i"},
})
try:
for i, prompt in enumerate(prompts):
seed = args.seed + i
@@ -109,21 +108,23 @@ def main() -> None:
output_path = os.path.join(args.out_dir, f"{filename_base}.png")
print(f"[flux] prompt_idx={i} seed={seed} output_path={output_path}")
generation_kwargs = {
"output_path": output_path,
"height": args.height,
"width": args.width,
"num_frames": 1,
"fps": 1,
"num_inference_steps": args.steps,
"guidance_scale": args.guidance,
"use_embedded_guidance": True,
"true_cfg_scale": 1.0,
"seed": seed,
"save_video": True,
request = {
"prompt": prompt,
"sampling": {
"height": args.height,
"width": args.width,
"num_frames": 1,
"fps": 1,
"num_inference_steps": args.steps,
"guidance_scale": args.guidance,
"use_embedded_guidance": True,
"true_cfg_scale": 1.0,
"seed": seed,
},
"output": {"output_path": output_path, "save_video": True},
}
generator.generate_video(prompt, **generation_kwargs)
generator.generate(request)
print(f"[flux] done. outputs written to: {args.out_dir}")
finally: