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import ldm.modules.encoders.modules
import open_clip
import torch
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.
Use like this:
```
with DisableInitialization():
do_things()
```
"""
def __enter__(self):
def do_nothing(*args, **kwargs):
pass
def create_model_and_transforms_without_pretrained(*args, pretrained=None, **kwargs):
return self.create_model_and_transforms(*args, pretrained=None, **kwargs)
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)
self.init_kaiming_uniform = torch.nn.init.kaiming_uniform_
self.init_no_grad_normal = torch.nn.init._no_grad_normal_
self.create_model_and_transforms = open_clip.create_model_and_transforms
self.CLIPTextModel_from_pretrained = ldm.modules.encoders.modules.CLIPTextModel.from_pretrained
torch.nn.init.kaiming_uniform_ = do_nothing
torch.nn.init._no_grad_normal_ = do_nothing
open_clip.create_model_and_transforms = create_model_and_transforms_without_pretrained
ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = CLIPTextModel_from_pretrained
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
open_clip.create_model_and_transforms = self.create_model_and_transforms
ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = self.CLIPTextModel_from_pretrained
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