From 0232183cbcecb331d736ef3b130fd31341bee2a4 Mon Sep 17 00:00:00 2001 From: RandNMR73 Date: Wed, 8 Apr 2026 23:52:40 +0000 Subject: [PATCH] clean --- examples/inference/sageattn+fp4linear.py | 50 ------------------------ 1 file changed, 50 deletions(-) delete mode 100644 examples/inference/sageattn+fp4linear.py diff --git a/examples/inference/sageattn+fp4linear.py b/examples/inference/sageattn+fp4linear.py deleted file mode 100644 index b37a3477c..000000000 --- a/examples/inference/sageattn+fp4linear.py +++ /dev/null @@ -1,50 +0,0 @@ -from fastvideo import VideoGenerator -import os -# from fastvideo.configs.sample import SamplingParam - -OUTPUT_PATH = "video_samples" -os.environ["FASTVIDEO_ATTENTION_BACKEND"] = "QAT_ATTN" - -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, - transformer_quant="fp4", - 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()