Initializing weights from checkpoint with configs - init_from_ptl_ckpt
**Describe the bug**
Hi! When I tried to initialize weights of the model from checkpoint using configs and excluding some parts of it I get an error that model_path is not defined
I looked a the code at https://github.com/NVIDIA/NeMo/blob/main/nemo/core/classes/modelPT.py and indeed there is  an initialized variable  ckpt_path, but model_path  is initialized for init_from_nemo_model
![image](https://user-images.githubusercontent.com/53433879/186564873-4faebdc0-a4bc-4f65-b9d3-7e0024025780.png)

Could you check if it was just accidental copy-paste and there should be ckpt_path instead of model_path  
                        self.load_part_of_state_dict(
                            ckpt['state_dict'], include, exclude, f'nemo file with path `**{model_path**}`'
                        )

in this snippet of  the code 

        if 'init_from_ptl_ckpt' in cfg and cfg.init_from_ptl_ckpt is not None:
            with open_dict(cfg):
                if isinstance(cfg.init_from_ptl_ckpt, str):
                    # Restore checkpoint
                    ckpt_path = cfg.pop('init_from_ptl_ckpt')
                    ckpt = torch.load(ckpt_path, map_location=map_location)

                    # Restore checkpoint into current model
                    self.load_state_dict(ckpt['state_dict'], strict=False)
                    logging.info(
                        f'Model checkpoint restored from pytorch lightning chackpoint with path : `{ckpt_path}`'
                    )

                    del ckpt
                elif isinstance(cfg.init_from_ptl_ckpt, (DictConfig, dict)):
                    model_load_dict = cfg.init_from_ptl_ckpt
                    for model_load_cfg in model_load_dict.values():
                        ckpt_path = model_load_cfg.path
                        # Restore model
                        ckpt = torch.load(ckpt_path, map_location=map_location)

                        include = model_load_cfg.pop('include', [""])
                        exclude = model_load_cfg.pop('exclude', [])

                        self.load_part_of_state_dict(
                            ckpt['state_dict'], include, exclude, f'nemo file with path `{model_path}`'
                        )
