Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' into lstein/model-manager-router-api

Browse Source
This commit is contained in:
Lincoln Stein
2023-07-06 13:20:36 -04:00
committed by GitHub
parent 90c66aab3d d5f90b1a02
commit 581be42c75
24 changed files with 474 additions and 114 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
invokeai/backend/install/invokeai_configure.py
View File

@ -430,13 +430,13 @@ to allow InvokeAI to download restricted styles & subjects from the "Concept Lib
max_height=len(PRECISION_CHOICES) + 1,
scroll_exit=True,
)
self.max_loaded_models = self.add_widget_intelligent(
self.max_cache_size = self.add_widget_intelligent(
IntTitleSlider,
name="Number of models to cache in CPU memory (each will use 2-4 GB!)",
value=old_opts.max_loaded_models,
out_of=10,
lowest=1,
begin_entry_at=4,
name="Size of the RAM cache used for fast model switching (GB)",
value=old_opts.max_cache_size,
out_of=20,
lowest=3,
begin_entry_at=6,
scroll_exit=True,
)
self.nextrely += 1
@ -539,7 +539,7 @@ https://huggingface.co/spaces/CompVis/stable-diffusion-license
"outdir",
"nsfw_checker",
"free_gpu_mem",
"max_loaded_models",
"max_cache_size",
"xformers_enabled",
"always_use_cpu",
]:
@ -555,9 +555,6 @@ https://huggingface.co/spaces/CompVis/stable-diffusion-license
new_opts.license_acceptance = self.license_acceptance.value
new_opts.precision = PRECISION_CHOICES[self.precision.value[0]]
# widget library workaround to make max_loaded_models an int rather than a float
new_opts.max_loaded_models = int(new_opts.max_loaded_models)
return new_opts

7
invokeai/backend/install/model_install_backend.py
View File

@ -196,8 +196,11 @@ class ModelInstall(object):
models_installed.update({str(path):self._install_path(path)})
# folders style or similar
elif path.is_dir() and any([(path/x).exists() for x in {'config.json','model_index.json','learned_embeds.bin'}]):
models_installed.update({str(path): self._install_path(path)})
elif path.is_dir() and any([(path/x).exists() for x in \
{'config.json','model_index.json','learned_embeds.bin','pytorch_lora_weights.bin'}
]
):
models_installed.update(self._install_path(path))
# recursive scan
elif path.is_dir():