apolinario commited on
Commit
3e1c79c
1 Parent(s): e7d3f7e

Performance upgrades

Browse files
Files changed (2) hide show
  1. app.py +8 -8
  2. requirements.txt +1 -1
app.py CHANGED
@@ -13,6 +13,8 @@ device = "cuda"
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  #If you are running this code locally, you need to either do a 'huggingface-cli login` or paste your User Access Token from here https://huggingface.co/settings/tokens into the use_auth_token field below.
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  pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True, revision="fp16", torch_dtype=torch.float16)
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  pipe = pipe.to(device)
 
 
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  #When running locally, you won`t have access to this, so you can remove this part
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  word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
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  word_list = word_list_dataset["train"]['text']
@@ -25,14 +27,12 @@ def infer(prompt, samples, steps, scale, seed):
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  generator = torch.Generator(device=device).manual_seed(seed)
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- #If you are running locally with CPU, you can remove the `with autocast("cuda")`
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- with autocast("cuda"):
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- images_list = pipe(
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- [prompt] * samples,
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- num_inference_steps=steps,
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- guidance_scale=scale,
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- generator=generator,
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- )
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  images = []
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  safe_image = Image.open(r"unsafe.png")
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  for i, image in enumerate(images_list["sample"]):
 
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  #If you are running this code locally, you need to either do a 'huggingface-cli login` or paste your User Access Token from here https://huggingface.co/settings/tokens into the use_auth_token field below.
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  pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True, revision="fp16", torch_dtype=torch.float16)
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  pipe = pipe.to(device)
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+ torch.backends.cudnn.benchmark = True
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+
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  #When running locally, you won`t have access to this, so you can remove this part
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  word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
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  word_list = word_list_dataset["train"]['text']
 
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  generator = torch.Generator(device=device).manual_seed(seed)
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+ images_list = pipe(
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+ [prompt] * samples,
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+ num_inference_steps=steps,
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+ guidance_scale=scale,
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+ generator=generator,
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+ )
 
 
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  images = []
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  safe_image = Image.open(r"unsafe.png")
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  for i, image in enumerate(images_list["sample"]):
requirements.txt CHANGED
@@ -1,4 +1,4 @@
1
- diffusers
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  transformers
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  nvidia-ml-py3
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  ftfy
 
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+ -e git+https://github.com/Narsil/diffusers.git@6a4d2ef1e514a25ff5b511cafa1f06b039f0909b#egg=diffusers
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  transformers
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  nvidia-ml-py3
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  ftfy