From f6080f7cee42d08d8ce18c8d127ef5505c645ec2 Mon Sep 17 00:00:00 2001 From: RandNMR73 Date: Wed, 24 Dec 2025 22:59:02 +0000 Subject: [PATCH] add sageattn3 inference example --- .../inference/sageattn_inference_example.py | 49 +++++++++++++++++++ 1 file changed, 49 insertions(+) create mode 100644 examples/inference/sageattn_inference_example.py diff --git a/examples/inference/sageattn_inference_example.py b/examples/inference/sageattn_inference_example.py new file mode 100644 index 000000000..dceb6a3c2 --- /dev/null +++ b/examples/inference/sageattn_inference_example.py @@ -0,0 +1,49 @@ +from fastvideo import VideoGenerator +import os +# from fastvideo.configs.sample import SamplingParam + +OUTPUT_PATH = "video_samples" +os.environ["FASTVIDEO_ATTENTION_BACKEND"] = "SAGE_ATTN_THREE" + +def main(): + # FastVideo will automatically use the optimal default arguments for the + # model. + # If a local path is provided, FastVideo will make a best effort + # attempt to identify the optimal arguments. + generator = VideoGenerator.from_pretrained( + "Wan-AI/Wan2.1-T2V-1.3B-Diffusers", + # FastVideo will automatically handle distributed setup + num_gpus=1, + use_fsdp_inference=True, + dit_cpu_offload=False, + vae_cpu_offload=False, + text_encoder_cpu_offload=True, + pin_cpu_memory=False, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument" + # image_encoder_cpu_offload=False, + ) + + # sampling_param = SamplingParam.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B-Diffusers") + # sampling_param.num_frames = 45 + # sampling_param.image_path = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg" + # Generate videos with the same simple API, regardless of GPU count + 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, save_video=True) + # video = generator.generate_video(prompt, sampling_param=sampling_param, output_path="wan_t2v_videos/") + + # Generate another video with a different prompt, without reloading the + # model! + prompt2 = ( + "A majestic lion strides across the golden savanna, its powerful frame " + "glistening under the warm afternoon sun. The tall grass ripples gently in " + "the breeze, enhancing the lion's commanding presence. The tone is vibrant, " + "embodying the raw energy of the wild. Low angle, steady tracking shot, " + "cinematic.") + video2 = generator.generate_video(prompt2, output_path=OUTPUT_PATH, save_video=True) + + +if __name__ == "__main__": + main()