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hao-ai-lab-FastVideo/examples/inference/basic/basic_self_forcing_causal.py
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2025-08-27 02:12:43 -07:00

67 lines
2.7 KiB
Python

import os
import time
from fastvideo import VideoGenerator, SamplingParam
OUTPUT_PATH = "video_samples_causal"
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.
load_start_time = time.perf_counter()
model_name = "wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers"
generator = VideoGenerator.from_pretrained(
model_name,
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=True,
text_encoder_cpu_offload=False,
dit_cpu_offload=False,
)
load_end_time = time.perf_counter()
load_time = load_end_time - load_start_time
sampling_param = SamplingParam.from_pretrained(model_name)
start_time = time.perf_counter()
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, sampling_param=sampling_param)
end_time = time.perf_counter()
gen_time1 = end_time - start_time
e2e_gen_time = end_time - load_start_time
# Generate another video with a different prompt, without reloading the
# model!
gen_time_list = []
for i in range(10):
start_time = time.perf_counter()
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, sampling_param=sampling_param)
end_time = time.perf_counter()
gen_time2 = end_time - start_time
gen_time_list.append(gen_time2)
# print(f"Time taken for video {i}: {gen_time2} seconds")
print(f"Time taken for first video: {gen_time1} seconds")
print(f"Average time taken for 10 videos: {sum(gen_time_list) / len(gen_time_list)} seconds")
for i, gen_time in enumerate(gen_time_list):
print(f"Time taken for video {i}: {gen_time} seconds")
# print(f"Time taken for second video: {gen_time2} seconds")
print(f"Time taken to load model: {load_time} seconds")
print(f"Time taken for first e2e generation: {e2e_gen_time} seconds")
if __name__ == "__main__":
main()