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Merge pull request #16144 from akx/bump-spandrel
Bump spandrel to 0.3.4
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commit
a6c384b9f7
@ -36,13 +36,11 @@ class FaceRestorerGFPGAN(face_restoration_utils.CommonFaceRestoration):
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ext_filter=['.pth'],
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):
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if 'GFPGAN' in os.path.basename(model_path):
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model = modelloader.load_spandrel_model(
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return modelloader.load_spandrel_model(
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model_path,
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device=self.get_device(),
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expected_architecture='GFPGAN',
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).model
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model.different_w = True # see https://github.com/chaiNNer-org/spandrel/pull/81
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return model
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raise ValueError("No GFPGAN model found")
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def restore(self, np_image):
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@ -139,6 +139,27 @@ def load_upscalers():
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key=lambda x: x.name.lower() if not isinstance(x.scaler, (UpscalerNone, UpscalerLanczos, UpscalerNearest)) else ""
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)
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# None: not loaded, False: failed to load, True: loaded
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_spandrel_extra_init_state = None
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def _init_spandrel_extra_archs() -> None:
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"""
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Try to initialize `spandrel_extra_archs` (exactly once).
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"""
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global _spandrel_extra_init_state
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if _spandrel_extra_init_state is not None:
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return
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try:
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import spandrel
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import spandrel_extra_arches
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spandrel.MAIN_REGISTRY.add(*spandrel_extra_arches.EXTRA_REGISTRY)
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_spandrel_extra_init_state = True
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except Exception:
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logger.warning("Failed to load spandrel_extra_arches", exc_info=True)
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_spandrel_extra_init_state = False
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def load_spandrel_model(
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path: str | os.PathLike,
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@ -148,11 +169,16 @@ def load_spandrel_model(
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dtype: str | torch.dtype | None = None,
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expected_architecture: str | None = None,
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) -> spandrel.ModelDescriptor:
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global _spandrel_extra_init_state
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import spandrel
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_init_spandrel_extra_archs()
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model_descriptor = spandrel.ModelLoader(device=device).load_from_file(str(path))
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if expected_architecture and model_descriptor.architecture != expected_architecture:
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arch = model_descriptor.architecture
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if expected_architecture and arch.name != expected_architecture:
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logger.warning(
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f"Model {path!r} is not a {expected_architecture!r} model (got {model_descriptor.architecture!r})",
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f"Model {path!r} is not a {expected_architecture!r} model (got {arch.name!r})",
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)
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half = False
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if prefer_half:
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@ -166,6 +192,6 @@ def load_spandrel_model(
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model_descriptor.model.eval()
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logger.debug(
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"Loaded %s from %s (device=%s, half=%s, dtype=%s)",
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model_descriptor, path, device, half, dtype,
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arch, path, device, half, dtype,
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)
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return model_descriptor
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@ -24,7 +24,8 @@ pytorch_lightning==1.9.4
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resize-right==0.0.2
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safetensors==0.4.2
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scikit-image==0.21.0
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spandrel==0.1.6
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spandrel==0.3.4
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spandrel-extra-arches==0.1.1
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tomesd==0.1.3
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torch
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torchdiffeq==0.2.3
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