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add more stuff to ignore when creating model from config

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prevent .vae.safetensors files from being listed as stable diffusion models
This commit is contained in:
AUTOMATIC
2023-01-10 16:51:04 +03:00
parent 0c3feb202c
commit ce3f639ec8
3 changed files with 56 additions and 9 deletions
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29
modules/sd_disable_initialization.py
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@@ -1,15 +1,19 @@
import ldm.modules.encoders.modules
import open_clip
import torch
import transformers.utils.hub
class DisableInitialization:
"""
When an object of this class enters a `with` block, it starts preventing torch's layer initialization
functions from working, and changes CLIP and OpenCLIP to not download model weights. When it leaves,
reverts everything to how it was.
When an object of this class enters a `with` block, it starts:
- preventing torch's layer initialization functions from working
- changes CLIP and OpenCLIP to not download model weights
- changes CLIP to not make requests to check if there is a new version of a file you already have
Use like this:
When it leaves the block, it reverts everything to how it was before.
Use it like this:
```
with DisableInitialization():
do_things()
@@ -26,19 +30,36 @@ class DisableInitialization:
def CLIPTextModel_from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs):
return self.CLIPTextModel_from_pretrained(None, *model_args, config=pretrained_model_name_or_path, state_dict={}, **kwargs)
def transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs):
# this file is always 404, prevent making request
if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json':
raise transformers.utils.hub.EntryNotFoundError
try:
return self.transformers_utils_hub_get_from_cache(url, *args, local_files_only=True, **kwargs)
except Exception as e:
return self.transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs)
self.init_kaiming_uniform = torch.nn.init.kaiming_uniform_
self.init_no_grad_normal = torch.nn.init._no_grad_normal_
self.init_no_grad_uniform_ = torch.nn.init._no_grad_uniform_
self.create_model_and_transforms = open_clip.create_model_and_transforms
self.CLIPTextModel_from_pretrained = ldm.modules.encoders.modules.CLIPTextModel.from_pretrained
self.transformers_utils_hub_get_from_cache = transformers.utils.hub.get_from_cache
torch.nn.init.kaiming_uniform_ = do_nothing
torch.nn.init._no_grad_normal_ = do_nothing
torch.nn.init._no_grad_uniform_ = do_nothing
open_clip.create_model_and_transforms = create_model_and_transforms_without_pretrained
ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = CLIPTextModel_from_pretrained
transformers.utils.hub.get_from_cache = transformers_utils_hub_get_from_cache
def __exit__(self, exc_type, exc_val, exc_tb):
torch.nn.init.kaiming_uniform_ = self.init_kaiming_uniform
torch.nn.init._no_grad_normal_ = self.init_no_grad_normal
torch.nn.init._no_grad_uniform_ = self.init_no_grad_uniform_
open_clip.create_model_and_transforms = self.create_model_and_transforms
ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = self.CLIPTextModel_from_pretrained
transformers.utils.hub.get_from_cache = self.transformers_utils_hub_get_from_cache