docstr: Return a data structure that stores the batch axis of the internal states
   of the inference model.
  
  Returns
  -------
  enc_out_batch_axis
  src_valid_length_batch_axis
  position_batch_axis
  dec_layer_batch_axis
docstr_tok: ["Return","a","data","structure","that","stores","the","batch","axis","of","the","internal","states","of","the","inference","model",".","Returns","--","--","--","-","enc_out_batch_axis","src_valid_length_batch_axis","position_batch_axis","dec_layer_batch_axis"]
code: def state_batch_axis(self) -> Tuple[int, int, int, List]:
      """Return a data structure that stores the batch axis of the internal states
       of the inference model.
  
      Returns
      -------
      enc_out_batch_axis
      src_valid_length_batch_axis
      position_batch_axis
      dec_layer_batch_axis
      """
      if self.model.layout == "NT":
          return 0, 0, 0, self.model.decoder.state_batch_axis
      else:
          return 1, 0, 0, self.model.decoder.state_batch_axis
  
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 3 for calling the TransformerInference obj's underlying member method code with example usage: obj.state_batch_axis() and returns: int,  int,  int,  self, int,  int,  int,  self