code: def move_dimension_to_the_front(tensor, dim_index):
      all_dims = list(range(tensor.ndim))
      return tensor.permute(
          *(
              [dim_index]
              + all_dims[:dim_index]
              + all_dims[dim_index + 1 :]
          )
      )
  
imports: import re
  from abc import abstractmethod
  from dataclasses import dataclass, field, is_dataclass
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from omegaconf import DictConfig, OmegaConf
  from nemo.collections.asr.parts.submodules import ctc_beam_decoding, ctc_greedy_decoding
  from nemo.collections.asr.parts.utils.asr_confidence_utils import ConfidenceConfig, ConfidenceMixin
  from nemo.collections.asr.parts.utils.rnnt_utils import Hypothesis, NBestHypotheses
  from nemo.collections.common.tokenizers.aggregate_tokenizer import DummyTokenizer
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.utils import logging, logging_mode
label_desc: Use image node_id 1 for calling a global function with example usage: move_dimension_to_the_front(tensor, dim_index) and returns: tensor