class_docstr: Beam search 
class_docstr_tok: ["Beam","search"]
docstr: Get the decoded sequence for the current timestep.
docstr_tok: ["Get","the","decoded","sequence","for","the","current","timestep","."]
code: def get_tentative_hypothesis(self):
      "Get the decoded sequence for the current timestep."
      if len(self.next_ys) == 1:
          dec_seq = self.next_ys[0].unsqueeze(1)
      else:
          _, keys = self.sort_scores()
          hyps = [self.get_hypothesis(k) for k in keys]
          hyps = [[2] + h for h in hyps]
          dec_seq = paddle.to_tensor(hyps, dtype="int64")
      return dec_seq
  
imports: import math
  import paddle
  from paddle import nn
  import paddle.nn.functional
  from paddle.nn import LayerList
  from paddle.nn import Dropout, Linear, LayerNorm
  import numpy
  from ppocr.modeling.backbones.rec_svtrnet import Mlp, zeros_, ones_
  from paddle.nn.initializer import XavierNormal
label_desc: Use image node_id 8 for calling the Beam obj's underlying member method code with example usage: obj.get_tentative_hypothesis() and returns: dec_seq