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modify pipeline

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This commit is contained in:
Chong
2023-08-23 13:59:47 +08:00
parent 88c842d3d5
commit b10475b3fa
1 changed files with 18 additions and 8 deletions
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26
src/diffusers/pipelines/t2i_adapter/pipeline_stable_diffusion_xl_adapter.py
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@@ -48,15 +48,26 @@ EXAMPLE_DOC_STRING = """
Examples:
```py
>>> import torch
>>> from diffusers import StableDiffusionXLPipeline
>>> from PIL import Image
>>> from diffusers import T2IAdapter, StableDiffusionXLAdapterPipeline, DDPMScheduler
>>> from pytorch_lightning import seed_everything
>>> from diffusers.models.unet_2d_condition import UNet2DConditionModel
>>> from diffusers.utils import load_image
>>> pipe = StableDiffusionXLPipeline.from_pretrained(
... "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16
... )
>>> pipe = pipe.to("cuda")
>>> sketch_image = load_image('https://huggingface.co/Adapter/t2iadapter/resolve/main/sketch.png').convert('L')
>>> prompt = "a photo of an astronaut riding a horse on mars"
>>> image = pipe(prompt).images[0]
>>> model_id = 'stabilityai/stable-diffusion-xl-base-1.0'
>>> adapter = T2IAdapter.from_pretrained("Adapter/t2iadapter", subfolder='sketch_sdxl_1.0',torch_dtype=torch.float16, adapter_type="full_adapter_xl")
>>> scheduler = DDPMScheduler.from_pretrained(model_id, subfolder="scheduler")
>>> pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
model_id, adapter=adapter, safety_checker=None, torch_dtype=torch.float16, variant="fp16", scheduler=scheduler
)
>>> pipe.to('cuda')
>>> generator = torch.Generator().manual_seed(42)
>>> sketch_image_out = pipe(prompt='a photo of a dog in real world, high quality', negative_prompt='extra digit, fewer digits, cropped, worst quality, low quality', image=sketch_image, generator=generator, guidance_scale=7.5).images[0]
```
"""
@@ -198,7 +209,6 @@ class StableDiffusionXLAdapterPipeline(DiffusionPipeline, FromSingleFileMixin, L
"""
self.vae.disable_tiling()
# Copied from diffusers.pipelines.stable_diffusion_xl.pipeline_stable_diffusion_xl.enable_model_cpu_offload
def enable_model_cpu_offload(self, gpu_id=0):
r"""
Offloads all models to CPU using accelerate, reducing memory usage with a low impact on performance. Compared