class_docstr: This is the class to record the infomation of each microbatch, and also do some update operation.
  This clase is the base class of `HeadMicroBatchDescription` and `BodyMicroBatchDescription`, for more
  details, please refer to the doc of these two classes blow.
  
  Args:
      inputs_dict (Dict[str, torch.Tensor]): the inputs of current stage. The key should have `input_ids` and `attention_mask`.
      output_dict (Dict[str, torch.Tensor]): the outputs of previous stage. The key should have `hidden_states` and `past_key_values`.
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docstr: Return the current sequnence length of micro batch
docstr_tok: ["Return","the","current","sequnence","length","of","micro","batch"]
code: def cur_length(self):
      """
      Return the current sequnence length of micro batch
  
      """
  
imports: from enum import Enum
  from typing import Dict
  import torch
  from ..kv_cache import BatchInferState, MemoryManager
label_desc: Use image node_id 4 for calling the MicroBatchDescription obj's underlying member method code with example usage: obj.cur_length() without return types