rollingdepth_src/diffusers/benchmarks/benchmark_text_to_image.py

import argparse
import sys


sys.path.append(".")
from base_classes import TextToImageBenchmark, TurboTextToImageBenchmark  # noqa: E402


ALL_T2I_CKPTS = [
    "runwayml/stable-diffusion-v1-5",
    "segmind/SSD-1B",
    "stabilityai/stable-diffusion-xl-base-1.0",
    "kandinsky-community/kandinsky-2-2-decoder",
    "warp-ai/wuerstchen",
    "stabilityai/sdxl-turbo",
]


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--ckpt",
        type=str,
        default="runwayml/stable-diffusion-v1-5",
        choices=ALL_T2I_CKPTS,
    )
    parser.add_argument("--batch_size", type=int, default=1)
    parser.add_argument("--num_inference_steps", type=int, default=50)
    parser.add_argument("--model_cpu_offload", action="store_true")
    parser.add_argument("--run_compile", action="store_true")
    args = parser.parse_args()

    benchmark_cls = None
    if "turbo" in args.ckpt:
        benchmark_cls = TurboTextToImageBenchmark
    else:
        benchmark_cls = TextToImageBenchmark

    benchmark_pipe = benchmark_cls(args)
    benchmark_pipe.benchmark(args)