support detecting midas model
fix broken api for checkpoint list
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@ -228,7 +228,7 @@ class SDModelItem(BaseModel):
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hash: Optional[str] = Field(title="Short hash")
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sha256: Optional[str] = Field(title="sha256 hash")
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filename: str = Field(title="Filename")
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config: str = Field(title="Config file")
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config: Optional[str] = Field(title="Config file")
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class HypernetworkItem(BaseModel):
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name: str = Field(title="Name")
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@ -439,12 +439,12 @@ def reload_model_weights(sd_model=None, info=None):
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if sd_model.sd_model_checkpoint == checkpoint_info.filename:
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return
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if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
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lowvram.send_everything_to_cpu()
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else:
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sd_model.to(devices.cpu)
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if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
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lowvram.send_everything_to_cpu()
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else:
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sd_model.to(devices.cpu)
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sd_hijack.model_hijack.undo_hijack(sd_model)
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sd_hijack.model_hijack.undo_hijack(sd_model)
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timer = Timer()
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@ -10,6 +10,7 @@ sd_repo_configs_path = os.path.join(paths.paths['Stable Diffusion'], "configs",
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config_default = shared.sd_default_config
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config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml")
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config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
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config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml")
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config_inpainting = os.path.join(sd_configs_path, "v1-inpainting-inference.yaml")
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config_instruct_pix2pix = os.path.join(sd_configs_path, "instruct-pix2pix.yaml")
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config_alt_diffusion = os.path.join(sd_configs_path, "alt-diffusion-inference.yaml")
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@ -22,7 +23,9 @@ def guess_model_config_from_state_dict(sd, filename):
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sd2_cond_proj_weight = sd.get('cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight', None)
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diffusion_model_input = sd.get('model.diffusion_model.input_blocks.0.0.weight', None)
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roberta_weight = sd.get('cond_stage_model.roberta.embeddings.word_embeddings.weight', None)
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if sd.get('depth_model.model.pretrained.act_postprocess3.0.project.0.bias', None) is not None:
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return config_depth_model
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if sd2_cond_proj_weight is not None and sd2_cond_proj_weight.shape[1] == 1024:
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if re.search(re_parametrization_v, fn) or "v2-1_768" in fn:
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@ -36,7 +39,7 @@ def guess_model_config_from_state_dict(sd, filename):
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if diffusion_model_input.shape[1] == 8:
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return config_instruct_pix2pix
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if roberta_weight is not None:
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if sd.get('cond_stage_model.roberta.embeddings.word_embeddings.weight', None) is not None:
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return config_alt_diffusion
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return config_default
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