disable torch weight initialization and CLIP downloading/reading checkpoint to speedup creating sd model from config
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modules/sd_disable_initialization.py
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44
modules/sd_disable_initialization.py
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import ldm.modules.encoders.modules
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import open_clip
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import torch
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class DisableInitialization:
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"""
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When an object of this class enters a `with` block, it starts preventing torch's layer initialization
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functions from working, and changes CLIP and OpenCLIP to not download model weights. When it leaves,
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reverts everything to how it was.
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Use like this:
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```
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with DisableInitialization():
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do_things()
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```
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"""
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def __enter__(self):
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def do_nothing(*args, **kwargs):
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pass
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def create_model_and_transforms_without_pretrained(*args, pretrained=None, **kwargs):
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return self.create_model_and_transforms(*args, pretrained=None, **kwargs)
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def CLIPTextModel_from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs):
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return self.CLIPTextModel_from_pretrained(None, *model_args, config=pretrained_model_name_or_path, state_dict={}, **kwargs)
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self.init_kaiming_uniform = torch.nn.init.kaiming_uniform_
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self.init_no_grad_normal = torch.nn.init._no_grad_normal_
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self.create_model_and_transforms = open_clip.create_model_and_transforms
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self.CLIPTextModel_from_pretrained = ldm.modules.encoders.modules.CLIPTextModel.from_pretrained
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torch.nn.init.kaiming_uniform_ = do_nothing
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torch.nn.init._no_grad_normal_ = do_nothing
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open_clip.create_model_and_transforms = create_model_and_transforms_without_pretrained
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ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = CLIPTextModel_from_pretrained
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def __exit__(self, exc_type, exc_val, exc_tb):
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torch.nn.init.kaiming_uniform_ = self.init_kaiming_uniform
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torch.nn.init._no_grad_normal_ = self.init_no_grad_normal
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open_clip.create_model_and_transforms = self.create_model_and_transforms
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ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = self.CLIPTextModel_from_pretrained
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@ -13,7 +13,7 @@ import ldm.modules.midas as midas
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from ldm.util import instantiate_from_config
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from modules import shared, modelloader, devices, script_callbacks, sd_vae
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from modules import shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization
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from modules.paths import models_path
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from modules.sd_hijack_inpainting import do_inpainting_hijack, should_hijack_inpainting
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@ -319,7 +319,8 @@ def load_model(checkpoint_info=None):
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if shared.cmd_opts.no_half:
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sd_config.model.params.unet_config.params.use_fp16 = False
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sd_model = instantiate_from_config(sd_config.model)
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with sd_disable_initialization.DisableInitialization():
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sd_model = instantiate_from_config(sd_config.model)
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load_model_weights(sd_model, checkpoint_info)
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