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Add safetensors support to LDSR
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@ -1,3 +1,4 @@
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import os
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import gc
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import gc
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import time
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import time
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import warnings
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import warnings
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@ -8,6 +9,7 @@ import torchvision
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from PIL import Image
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from PIL import Image
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from einops import rearrange, repeat
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from einops import rearrange, repeat
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from omegaconf import OmegaConf
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from omegaconf import OmegaConf
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import safetensors.torch
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from ldm.models.diffusion.ddim import DDIMSampler
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from ldm.models.diffusion.ddim import DDIMSampler
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from ldm.util import instantiate_from_config, ismap
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from ldm.util import instantiate_from_config, ismap
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@ -28,8 +30,12 @@ class LDSR:
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model: torch.nn.Module = cached_ldsr_model
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model: torch.nn.Module = cached_ldsr_model
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else:
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else:
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print(f"Loading model from {self.modelPath}")
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print(f"Loading model from {self.modelPath}")
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pl_sd = torch.load(self.modelPath, map_location="cpu")
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_, extension = os.path.splitext(self.modelPath)
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sd = pl_sd["state_dict"]
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if extension.lower() == ".safetensors":
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pl_sd = safetensors.torch.load_file(self.modelPath, device="cpu")
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else:
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pl_sd = torch.load(self.modelPath, map_location="cpu")
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sd = pl_sd["state_dict"] if "state_dict" in pl_sd else pl_sd
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config = OmegaConf.load(self.yamlPath)
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config = OmegaConf.load(self.yamlPath)
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config.model.target = "ldm.models.diffusion.ddpm.LatentDiffusionV1"
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config.model.target = "ldm.models.diffusion.ddpm.LatentDiffusionV1"
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model: torch.nn.Module = instantiate_from_config(config.model)
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model: torch.nn.Module = instantiate_from_config(config.model)
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@ -25,6 +25,7 @@ class UpscalerLDSR(Upscaler):
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yaml_path = os.path.join(self.model_path, "project.yaml")
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yaml_path = os.path.join(self.model_path, "project.yaml")
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old_model_path = os.path.join(self.model_path, "model.pth")
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old_model_path = os.path.join(self.model_path, "model.pth")
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new_model_path = os.path.join(self.model_path, "model.ckpt")
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new_model_path = os.path.join(self.model_path, "model.ckpt")
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safetensors_model_path = os.path.join(self.model_path, "model.safetensors")
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if os.path.exists(yaml_path):
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if os.path.exists(yaml_path):
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statinfo = os.stat(yaml_path)
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statinfo = os.stat(yaml_path)
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if statinfo.st_size >= 10485760:
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if statinfo.st_size >= 10485760:
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@ -33,8 +34,11 @@ class UpscalerLDSR(Upscaler):
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if os.path.exists(old_model_path):
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if os.path.exists(old_model_path):
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print("Renaming model from model.pth to model.ckpt")
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print("Renaming model from model.pth to model.ckpt")
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os.rename(old_model_path, new_model_path)
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os.rename(old_model_path, new_model_path)
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model = load_file_from_url(url=self.model_url, model_dir=self.model_path,
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if os.path.exists(safetensors_model_path):
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file_name="model.ckpt", progress=True)
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model = safetensors_model_path
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else:
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model = load_file_from_url(url=self.model_url, model_dir=self.model_path,
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file_name="model.ckpt", progress=True)
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yaml = load_file_from_url(url=self.yaml_url, model_dir=self.model_path,
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yaml = load_file_from_url(url=self.yaml_url, model_dir=self.model_path,
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file_name="project.yaml", progress=True)
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file_name="project.yaml", progress=True)
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