code: def tile_to_beam_size_after_initial_step(
      self, fn_map_state, log_probs
  ):
      if fn_map_state is not None:
          log_probs = fn_map_state(log_probs, dim=0)
          self.model.decoder.map_state(fn_map_state)
          log_probs = log_probs[:, -1, :]
      return log_probs
  
imports: import torch
  from torch.nn.functional import log_softmax
  from torch.nn.utils.rnn import pad_sequence
  import codecs
  from time import time
  from math import exp
  from itertools import count, zip_longest
  from copy import deepcopy
  import onmt.model_builder
  import onmt.decoders.ensemble
  from onmt.constants import DefaultTokens
  from onmt.translate.beam_search import BeamSearch, BeamSearchLM
  from onmt.translate.greedy_search import GreedySearch, GreedySearchLM
  from onmt.utils.misc import tile, set_random_seed, report_matrix
  from onmt.utils.alignment import extract_alignment, build_align_pharaoh
  from onmt.modules.copy_generator import collapse_copy_scores
  from onmt.constants import ModelTask
  from onmt.transforms import TransformPipe
label_desc: Use image node_id 5 for calling the GeneratorLM obj's underlying member method code with example usage: obj.tile_to_beam_size_after_initial_step(fn_map_state, log_probs) and returns: log_probs