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from diffusers import StableDiffusionPipeline, UniPCMultistepScheduler |
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import time |
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import torch |
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import sys |
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path = sys.argv[1] |
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use_device_map = bool(int(sys.argv[2])) |
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start_time = time.time() |
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if use_device_map: |
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print("Load directly on GPU") |
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pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16, device_map="auto") |
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else: |
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print("Load directly on CPU") |
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pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16) |
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pipe = pipe.to("cuda") |
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pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config) |
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prompt = "a highly realistic photo of green turtle" |
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print("Loading Time", time.time() - start_time) |
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generator = torch.Generator(device="cuda").manual_seed(0) |
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image = pipe(prompt, generator=generator, num_inference_steps=15).images[0] |
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print("Time", time.time() - start_time) |
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