diff options
Diffstat (limited to 'modules/sd_disable_initialization.py')
| -rw-r--r-- | modules/sd_disable_initialization.py | 71 |
1 files changed, 32 insertions, 39 deletions
diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py index 088ac24b..c72d8efc 100644 --- a/modules/sd_disable_initialization.py +++ b/modules/sd_disable_initialization.py @@ -20,6 +20,19 @@ class DisableInitialization: ```
"""
+ def __init__(self):
+ self.replaced = []
+
+ def replace(self, obj, field, func):
+ original = getattr(obj, field, None)
+ if original is None:
+ return None
+
+ self.replaced.append((obj, field, original))
+ setattr(obj, field, func)
+
+ return original
+
def __enter__(self):
def do_nothing(*args, **kwargs):
pass
@@ -37,11 +50,14 @@ class DisableInitialization: def transformers_utils_hub_get_file_from_cache(original, url, *args, **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
+ if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json':
+ return None
try:
- return original(url, *args, local_files_only=True, **kwargs)
+ res = original(url, *args, local_files_only=True, **kwargs)
+ if res is None:
+ res = original(url, *args, local_files_only=False, **kwargs)
+ return res
except Exception as e:
return original(url, *args, local_files_only=False, **kwargs)
@@ -54,42 +70,19 @@ class DisableInitialization: def transformers_configuration_utils_cached_file(url, *args, local_files_only=False, **kwargs):
return transformers_utils_hub_get_file_from_cache(self.transformers_configuration_utils_cached_file, url, *args, **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_modeling_utils_load_pretrained_model = getattr(transformers.modeling_utils.PreTrainedModel, '_load_pretrained_model', None)
- self.transformers_tokenization_utils_base_cached_file = getattr(transformers.tokenization_utils_base, 'cached_file', None)
- self.transformers_configuration_utils_cached_file = getattr(transformers.configuration_utils, 'cached_file', None)
- self.transformers_utils_hub_get_from_cache = getattr(transformers.utils.hub, 'get_from_cache', None)
-
- 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
- if self.transformers_modeling_utils_load_pretrained_model is not None:
- transformers.modeling_utils.PreTrainedModel._load_pretrained_model = transformers_modeling_utils_load_pretrained_model
- if self.transformers_tokenization_utils_base_cached_file is not None:
- transformers.tokenization_utils_base.cached_file = transformers_tokenization_utils_base_cached_file
- if self.transformers_configuration_utils_cached_file is not None:
- transformers.configuration_utils.cached_file = transformers_configuration_utils_cached_file
- if self.transformers_utils_hub_get_from_cache is not None:
- transformers.utils.hub.get_from_cache = transformers_utils_hub_get_from_cache
+ self.replace(torch.nn.init, 'kaiming_uniform_', do_nothing)
+ self.replace(torch.nn.init, '_no_grad_normal_', do_nothing)
+ self.replace(torch.nn.init, '_no_grad_uniform_', do_nothing)
+ self.create_model_and_transforms = self.replace(open_clip, 'create_model_and_transforms', create_model_and_transforms_without_pretrained)
+ self.CLIPTextModel_from_pretrained = self.replace(ldm.modules.encoders.modules.CLIPTextModel, 'from_pretrained', CLIPTextModel_from_pretrained)
+ self.transformers_modeling_utils_load_pretrained_model = self.replace(transformers.modeling_utils.PreTrainedModel, '_load_pretrained_model', transformers_modeling_utils_load_pretrained_model)
+ self.transformers_tokenization_utils_base_cached_file = self.replace(transformers.tokenization_utils_base, 'cached_file', transformers_tokenization_utils_base_cached_file)
+ self.transformers_configuration_utils_cached_file = self.replace(transformers.configuration_utils, 'cached_file', transformers_configuration_utils_cached_file)
+ self.transformers_utils_hub_get_from_cache = self.replace(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
- if self.transformers_modeling_utils_load_pretrained_model is not None:
- transformers.modeling_utils.PreTrainedModel._load_pretrained_model = self.transformers_modeling_utils_load_pretrained_model
- if self.transformers_tokenization_utils_base_cached_file is not None:
- transformers.utils.hub.cached_file = self.transformers_tokenization_utils_base_cached_file
- if self.transformers_configuration_utils_cached_file is not None:
- transformers.utils.hub.cached_file = self.transformers_configuration_utils_cached_file
- if self.transformers_utils_hub_get_from_cache is not None:
- transformers.utils.hub.get_from_cache = self.transformers_utils_hub_get_from_cache
+ for obj, field, original in self.replaced:
+ setattr(obj, field, original)
+
+ self.replaced.clear()
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