docstr: Parameters
  ----------
  model
docstr_tok: ["Parameters","--","--","--","--","--","model"]
code: def __init__(self, model):
      """
  
      Parameters
      ----------
      model
      """
      super().__init__()
      self.model = model
  
imports: import numpy
  import mxnet
  from mxnet import np, npx
  from mxnet import use_np
  from mxnet.gluon import nn, HybridBlock
  from typing import Optional, Tuple, List
  from ..utils.registry import Registry
  from ..attention_cell import MultiHeadAttentionCell, gen_self_attn_mask, gen_mem_attn_mask
  from ..layers import PositionalEmbedding, PositionwiseFFN, InitializerType
  from ..utils.config import CfgNode
  from ..sequence_sampler import BaseStepDecoder
label_desc: Use image node_id 1 to create a new TransformerInference object from inherited base classes: HybridBlock, BaseStepDecoder with example: obj = TransformerInference(model)