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chore: flake8

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psychedelicious 2023-09-28 13:49:31 +10:00
parent f6bbcd0589
commit 045d3f6139
1 changed files with 5 additions and 5 deletions
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invokeai/backend/install/model_install_backend.py
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@ -350,17 +350,17 @@ class ModelInstall(object):
for suffix in ["safetensors", "bin"]: for suffix in ["safetensors", "bin"]:
if f"{prefix}pytorch_lora_weights.{suffix}" in files: if f"{prefix}pytorch_lora_weights.{suffix}" in files:
location = self._download_hf_model( location = self._download_hf_model(
repo_id, [f"pytorch_lora_weights.bin"], staging, subfolder=subfolder repo_id, ["pytorch_lora_weights.bin"], staging, subfolder=subfolder
) # LoRA ) # LoRA
break break
elif ( elif (
self.config.precision == "float16" and f"{prefix}diffusion_pytorch_model.fp16.{suffix}" in files self.config.precision == "float16" and f"{prefix}diffusion_pytorch_model.fp16.{suffix}" in files
): # vae, controlnet or some other standalone ): # vae, controlnet or some other standalone
files = [f"config.json", f"diffusion_pytorch_model.fp16.{suffix}"] files = ["config.json", f"diffusion_pytorch_model.fp16.{suffix}"]
location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder) location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
break break
elif f"{prefix}diffusion_pytorch_model.{suffix}" in files: elif f"{prefix}diffusion_pytorch_model.{suffix}" in files:
files = [f"config.json", f"diffusion_pytorch_model.{suffix}"] files = ["config.json", f"diffusion_pytorch_model.{suffix}"]
location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder) location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
break break
elif f"{prefix}learned_embeds.{suffix}" in files: elif f"{prefix}learned_embeds.{suffix}" in files:
@ -371,13 +371,13 @@ class ModelInstall(object):
elif ( elif (
f"{prefix}image_encoder.txt" in files and f"{prefix}ip_adapter.{suffix}" in files f"{prefix}image_encoder.txt" in files and f"{prefix}ip_adapter.{suffix}" in files
): # IP-Adapter ): # IP-Adapter
files = [f"image_encoder.txt", f"ip_adapter.{suffix}"] files = ["image_encoder.txt", f"ip_adapter.{suffix}"]
location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder) location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
break break
elif f"{prefix}model.{suffix}" in files and f"{prefix}config.json" in files: elif f"{prefix}model.{suffix}" in files and f"{prefix}config.json" in files:
# This elif-condition is pretty fragile, but it is intended to handle CLIP Vision models hosted # This elif-condition is pretty fragile, but it is intended to handle CLIP Vision models hosted
# by InvokeAI for use with IP-Adapters. # by InvokeAI for use with IP-Adapters.
files = [f"config.json", f"model.{suffix}"] files = ["config.json", f"model.{suffix}"]
location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder) location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
break break
if not location: if not location: