class_docstr: A  layer wrapper for random LTD
class_docstr_tok: ["A","layer","wrapper","for","random","LTD"]
code: def get_sbh(self, hidden_stats):
      self.curr_seq, self.curr_micro_batch = (
          hidden_stats.size()[0],
          hidden_stats.size()[1],
      )
  
file_path: DeepSpeed/deepspeed/runtime/data_pipeline/data_routing/basic_layer.py
imports: from deepspeed.utils import logger
  from torch import Tensor
  from torch.nn import Module
  from ..constants import *
  from deepspeed.ops.random_ltd.dropping_utils import gpt_sample_tokens, bert_sample_tokens, GatherTokens, ScatterTokens
label_desc: Use image node_id 4 for calling the RandomLayerTokenDrop obj's underlying member method code with example usage: obj.get_sbh(hidden_stats) without return types