游雁
2024-02-21 cab0af88d8d671d7a358dbdd1c9645cc4cbafd1d
funasr/train_utils/trainer.py
@@ -109,12 +109,8 @@
        
        print(f'Checkpoint saved to {filename}')
        latest = Path(os.path.join(self.output_dir, f'model.pt'))
        try:
            latest.unlink()
        except:
            pass
        torch.save(state, latest)
        latest.symlink_to(filename)
    
    def _resume_checkpoint(self, resume_path):
        """
@@ -128,7 +124,20 @@
        if os.path.isfile(ckpt):
            checkpoint = torch.load(ckpt)
            self.start_epoch = checkpoint['epoch'] + 1
            self.model.load_state_dict(checkpoint['state_dict'])
            # self.model.load_state_dict(checkpoint['state_dict'])
            src_state = checkpoint['state_dict']
            dst_state = self.model.state_dict()
            for k in dst_state.keys():
                if not k.startswith("module.") and "module."+k in src_state.keys():
                    k_ddp = "module."+k
                else:
                    k_ddp = k
                if k_ddp in src_state.keys():
                    dst_state[k] = src_state[k_ddp]
                else:
                    print(f"Miss key in ckpt: model: {k}, ckpt: {k_ddp}")
            self.model.load_state_dict(dst_state)
            self.optim.load_state_dict(checkpoint['optimizer'])
            self.scheduler.load_state_dict(checkpoint['scheduler'])
            print(f"Checkpoint loaded successfully from '{ckpt}'")