add support for transformers==4.25.1

add fallback for when quick model creation fails

1 files changed, 36 insertions, 6 deletions

diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py
index 9942bd7e..088ac24b 100644
--- a/modules/sd_disable_initialization.py
+++ b/modules/sd_disable_initialization.py
@@ -30,30 +30,53 @@ 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):

+        def transformers_modeling_utils_load_pretrained_model(*args, **kwargs):

+            args = args[0:3] + ('/', ) + args[4:]  # resolved_archive_file; must set it to something to prevent what seems to be a bug

+            return self.transformers_modeling_utils_load_pretrained_model(*args, **kwargs)

+

+        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

 

             try:

-                return self.transformers_utils_hub_get_from_cache(url, *args, local_files_only=True, **kwargs)

+                return original(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)

+                return original(url, *args, local_files_only=False, **kwargs)

+

+        def transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs):

+            return transformers_utils_hub_get_file_from_cache(self.transformers_utils_hub_get_from_cache, url, *args, **kwargs)

+

+        def transformers_tokenization_utils_base_cached_file(url, *args, local_files_only=False, **kwargs):

+            return transformers_utils_hub_get_file_from_cache(self.transformers_tokenization_utils_base_cached_file, url, *args, **kwargs)

+

+        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_utils_hub_get_from_cache = transformers.utils.hub.get_from_cache

+        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

-        transformers.utils.hub.get_from_cache = transformers_utils_hub_get_from_cache

+        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

 

     def __exit__(self, exc_type, exc_val, exc_tb):

         torch.nn.init.kaiming_uniform_ = self.init_kaiming_uniform

@@ -61,5 +84,12 @@ class DisableInitialization:
         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

+        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