Refactor app/stable_diffusion_xl.py.
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parent
c84646dcd3
commit
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11
app/setup.py
11
app/setup.py
@ -1,5 +1,6 @@
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import os
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import os
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from abc import ABC, abstractmethod
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from abc import ABC, abstractmethod
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from pathlib import Path
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import diffusers
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import diffusers
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from huggingface_hub import login
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from huggingface_hub import login
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@ -36,7 +37,7 @@ class StableDiffusionCLISetupSDXL(StableDiffusionCLISetupInterface):
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self.__token: str = token
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self.__token: str = token
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def download_model(self) -> None:
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def download_model(self) -> None:
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cache_path = os.path.join(BASE_CACHE_PATH, self.__model_name)
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cache_path = Path(BASE_CACHE_PATH) / self.__model_name
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pipe = diffusers.StableDiffusionXLPipeline.from_single_file(
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pipe = diffusers.StableDiffusionXLPipeline.from_single_file(
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pretrained_model_link_or_path=self.__model_url,
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pretrained_model_link_or_path=self.__model_url,
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use_auth_token=self.__token,
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use_auth_token=self.__token,
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@ -63,7 +64,7 @@ class StableDiffusionCLISetupSD15(StableDiffusionCLISetupInterface):
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self.__token: str = token
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self.__token: str = token
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def download_model(self) -> None:
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def download_model(self) -> None:
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cache_path = os.path.join(BASE_CACHE_PATH, self.__model_name)
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cache_path = Path(BASE_CACHE_PATH) / self.__model_name
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pipe = diffusers.StableDiffusionPipeline.from_single_file(
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pipe = diffusers.StableDiffusionPipeline.from_single_file(
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pretrained_model_link_or_path=self.__model_url,
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pretrained_model_link_or_path=self.__model_url,
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token=self.__token,
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token=self.__token,
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@ -117,7 +118,7 @@ class CommonSetup:
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)
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)
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def __download_vae(self, name: str, model_url: str, token: str) -> None:
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def __download_vae(self, name: str, model_url: str, token: str) -> None:
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cache_path = os.path.join(BASE_CACHE_PATH, name)
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cache_path = Path(BASE_CACHE_PATH, name)
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vae = diffusers.AutoencoderKL.from_single_file(
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vae = diffusers.AutoencoderKL.from_single_file(
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pretrained_model_link_or_path=model_url,
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pretrained_model_link_or_path=model_url,
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use_auth_token=token,
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use_auth_token=token,
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@ -126,7 +127,7 @@ class CommonSetup:
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vae.save_pretrained(cache_path, safe_serialization=True)
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vae.save_pretrained(cache_path, safe_serialization=True)
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def __download_controlnet(self, name: str, repo_id: str, token: str) -> None:
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def __download_controlnet(self, name: str, repo_id: str, token: str) -> None:
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cache_path = os.path.join(BASE_CACHE_PATH_CONTROLNET, name)
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cache_path = Path(BASE_CACHE_PATH_CONTROLNET) / name
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controlnet = diffusers.ControlNetModel.from_pretrained(
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controlnet = diffusers.ControlNetModel.from_pretrained(
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repo_id,
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repo_id,
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use_auth_token=token,
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use_auth_token=token,
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@ -142,7 +143,7 @@ class CommonSetup:
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req = Request(url, headers={"User-Agent": "Mozilla/5.0"})
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req = Request(url, headers={"User-Agent": "Mozilla/5.0"})
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downloaded = urlopen(req).read()
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downloaded = urlopen(req).read()
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dir_names = os.path.join(file_path, file_name)
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dir_names = Path(file_path) / file_name
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os.makedirs(os.path.dirname(dir_names), exist_ok=True)
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os.makedirs(os.path.dirname(dir_names), exist_ok=True)
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with open(dir_names, mode="wb") as f:
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with open(dir_names, mode="wb") as f:
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f.write(downloaded)
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f.write(downloaded)
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@ -1,7 +1,7 @@
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from __future__ import annotations
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from __future__ import annotations
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import io
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import io
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import os
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from pathlib import Path
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import PIL.Image
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import PIL.Image
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from modal import Secret, enter, method
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from modal import Secret, enter, method
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@ -24,13 +24,12 @@ class SDXLTxt2Img:
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import yaml
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import yaml
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config = {}
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config = {}
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with open("/config.yml") as file:
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with Path("/config.yml").open() as file:
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config = yaml.safe_load(file)
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config = yaml.safe_load(file)
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self.__cache_path = os.path.join(BASE_CACHE_PATH, config["model"]["name"])
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self.__cache_path = Path(BASE_CACHE_PATH) / config["model"]["name"]
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if os.path.exists(self.__cache_path):
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if not Path.exists(self.__cache_path):
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print(f"The directory '{self.__cache_path}' exists.")
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msg = f"The directory '{self.__cache_path}' does not exist."
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else:
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raise ValueError(msg)
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print(f"The directory '{self.__cache_path}' does not exist.")
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self.__pipe = diffusers.StableDiffusionXLPipeline.from_pretrained(
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self.__pipe = diffusers.StableDiffusionXLPipeline.from_pretrained(
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self.__cache_path,
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self.__cache_path,
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