diff options
Diffstat (limited to 'modules/sd_disable_initialization.py')
| -rw-r--r-- | modules/sd_disable_initialization.py | 29 |
1 files changed, 25 insertions, 4 deletions
diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py index c9a3b5e4..9942bd7e 100644 --- a/modules/sd_disable_initialization.py +++ b/modules/sd_disable_initialization.py @@ -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
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