class_docstr: A trainer for training models. 
docstr: Predict a list of expansions given words. 
docstr_tok: ["Predict","a","list","of","expansions","given","words","."]
code: def predict_dict(self, words):
      """Predict a list of expansions given words."""
      expansions = []
      for w in words:
          if w in self.expansion_dict:
              expansions += [self.expansion_dict[w]]
          elif w.lower() in self.expansion_dict:
              expansions += [self.expansion_dict[w.lower()]]
          else:
              expansions += [w]
      return expansions
  
imports: import sys
  import numpy
  from collections import Counter
  import logging
  import torch
  from torch import nn
  import torch.nn.init
  import stanza.models.common.seq2seq_constant
  from stanza.models.common.trainer import Trainer
  from stanza.models.common.seq2seq_model import Seq2SeqModel
  from stanza.models.common import utils, loss
  from stanza.models.mwt.vocab import Vocab
label_desc: Use image node_id 5 for calling the Trainer obj's underlying member method code with example usage: obj.predict_dict(words) and returns: expansions