support sovits v2Pro v2ProPlus
support sovits v2Pro v2ProPlus
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@@ -22,7 +22,7 @@ logger = logging
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def load_checkpoint(checkpoint_path, model, optimizer=None, skip_optimizer=False):
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assert os.path.isfile(checkpoint_path)
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checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
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checkpoint_dict = torch.load(checkpoint_path, map_location="cpu", weights_only=False)
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iteration = checkpoint_dict["iteration"]
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learning_rate = checkpoint_dict["learning_rate"]
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if optimizer is not None and not skip_optimizer and checkpoint_dict["optimizer"] is not None:
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