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expose max_cache_size to invokeai-configure interface

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This commit is contained in:
Lincoln Stein 2023-07-05 20:59:14 -04:00
parent bf25818d76
commit 0a6dccd607
2 changed files with 9 additions and 22 deletions
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17
invokeai/backend/install/invokeai_configure.py
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@ -430,13 +430,13 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
max_height=len(PRECISION_CHOICES) + 1, max_height=len(PRECISION_CHOICES) + 1,
scroll_exit=True, scroll_exit=True,
) )
self.max_loaded_models = self.add_widget_intelligent( self.max_cache_size = self.add_widget_intelligent(
IntTitleSlider, IntTitleSlider,
name="Number of models to cache in CPU memory (each will use 2-4 GB!)", name="Size of the RAM cache used for fast model switching (GB)",
value=old_opts.max_loaded_models, value=old_opts.max_cache_size,
out_of=10, out_of=20,
lowest=1, lowest=3,
begin_entry_at=4, begin_entry_at=6,
scroll_exit=True, scroll_exit=True,
) )
self.nextrely += 1 self.nextrely += 1
@ -539,7 +539,7 @@ https://huggingface.co/spaces/CompVis/stable-diffusion-license
"outdir", "outdir",
"nsfw_checker", "nsfw_checker",
"free_gpu_mem", "free_gpu_mem",
"max_loaded_models", "max_cache_size",
"xformers_enabled", "xformers_enabled",
"always_use_cpu", "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.license_acceptance = self.license_acceptance.value
new_opts.precision = PRECISION_CHOICES[self.precision.value[0]] 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 return new_opts

14
invokeai/backend/model_management/model_cache.py
View File

@ -8,7 +8,7 @@ The cache returns context manager generators designed to load the
model into the GPU within the context, and unload outside the model into the GPU within the context, and unload outside the
context. Use like this: context. Use like this:
cache = ModelCache(max_models_cached=6) cache = ModelCache(max_cache_size=7.5)
with cache.get_model('runwayml/stable-diffusion-1-5') as SD1, with cache.get_model('runwayml/stable-diffusion-1-5') as SD1,
cache.get_model('stabilityai/stable-diffusion-2') as SD2: cache.get_model('stabilityai/stable-diffusion-2') as SD2:
do_something_in_GPU(SD1,SD2) do_something_in_GPU(SD1,SD2)
@ -91,7 +91,7 @@ class ModelCache(object):
logger: types.ModuleType = logger logger: types.ModuleType = logger
): ):
''' '''
:param max_models: Maximum number of models to cache in CPU RAM [4] :param max_cache_size: Maximum size of the RAM cache [6.0 GB]
:param execution_device: Torch device to load active model into [torch.device('cuda')] :param execution_device: Torch device to load active model into [torch.device('cuda')]
:param storage_device: Torch device to save inactive model in [torch.device('cpu')] :param storage_device: Torch device to save inactive model in [torch.device('cpu')]
:param precision: Precision for loaded models [torch.float16] :param precision: Precision for loaded models [torch.float16]
@ -126,16 +126,6 @@ class ModelCache(object):
key += f":{submodel_type}" key += f":{submodel_type}"
return key return key
#def get_model(
# self,
# repo_id_or_path: Union[str, Path],
# model_type: ModelType = ModelType.Diffusers,
# subfolder: Path = None,
# submodel: ModelType = None,
# revision: str = None,
# attach_model_part: Tuple[ModelType, str] = (None, None),
# gpu_load: bool = True,
#) -> ModelLocker: # ?? what does it return
def _get_model_info( def _get_model_info(
self, self,
model_path: str, model_path: str,