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Configuration error
Configuration error
| 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 | |
| - 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 | |
| When it leaves the block, it reverts everything to how it was before. | |
| Use it like this: | |
| ``` | |
| with DisableInitialization(): | |
| do_things() | |
| ``` | |
| """ | |
| def __init__(self, disable_clip=True): | |
| self.replaced = [] | |
| self.disable_clip = disable_clip | |
| 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 | |
| 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): | |
| res = self.CLIPTextModel_from_pretrained(None, *model_args, config=pretrained_model_name_or_path, state_dict={}, **kwargs) | |
| res.name_or_path = pretrained_model_name_or_path | |
| return res | |
| 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' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json': | |
| return None | |
| try: | |
| 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: | |
| 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.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) | |
| if self.disable_clip: | |
| 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): | |
| for obj, field, original in self.replaced: | |
| setattr(obj, field, original) | |
| self.replaced.clear() | |