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import importlib |
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import torch |
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import yaml |
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from omegaconf import OmegaConf |
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from taming.models.vqgan import VQModel |
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def load_config(config_path, display=False): |
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config = OmegaConf.load(config_path) |
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if display: |
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print(yaml.dump(OmegaConf.to_container(config))) |
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return config |
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def load_vqgan(device, conf_path=None, ckpt_path=None): |
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if conf_path is None: |
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conf_path = "./model_checkpoints/vqgan_only.yaml" |
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config = load_config(conf_path, display=False) |
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model = VQModel(**config.model.params) |
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if ckpt_path is None: |
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ckpt_path = "./model_checkpoints/vqgan_only.pt" |
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sd = torch.load(ckpt_path, map_location=device) |
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if ".ckpt" in ckpt_path: |
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sd = sd["state_dict"] |
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model.load_state_dict(sd, strict=True) |
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model.to(device) |
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del sd |
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return model |
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def reconstruct_with_vqgan(x, model): |
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z, _, [_, _, indices] = model.encode(x) |
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print(f"VQGAN --- {model.__class__.__name__}: latent shape: {z.shape[2:]}") |
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xrec = model.decode(z) |
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return xrec |
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def get_obj_from_str(string, reload=False): |
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module, cls = string.rsplit(".", 1) |
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if reload: |
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module_imp = importlib.import_module(module) |
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importlib.reload(module_imp) |
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return getattr(importlib.import_module(module, package=None), cls) |
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def instantiate_from_config(config): |
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if "target" not in config: |
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raise KeyError("Expected key `target` to instantiate.") |
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return get_obj_from_str(config["target"])(**config.get("params", {})) |
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def load_model_from_config(config, sd, gpu=True, eval_mode=True): |
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model = instantiate_from_config(config) |
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if sd is not None: |
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model.load_state_dict(sd) |
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if gpu: |
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model.cuda() |
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if eval_mode: |
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model.eval() |
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return {"model": model} |
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def load_model(config, ckpt, gpu, eval_mode): |
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if ckpt: |
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pl_sd = torch.load(ckpt, map_location="cpu") |
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global_step = pl_sd["global_step"] |
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print(f"loaded model from global step {global_step}.") |
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else: |
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pl_sd = {"state_dict": None} |
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global_step = None |
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model = load_model_from_config(config.model, pl_sd["state_dict"], gpu=gpu, eval_mode=eval_mode)["model"] |
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return model, global_step |
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