code: def sample_n(self, num_words, input, temperature=1.0, hidden=None):
      preds = [None] * num_words
      for i in range(num_words):
          preds[i], hidden = self.sample(input, hidden=hidden)
          input = skorch.utils.to_tensor(
              torch.LongTensor([[preds[i]]]), device=self.device
          )
      return preds, hidden
  
file_path: skorch/examples/word_language_model/net.py
imports: import skorch
  import numpy
  import torch
  from torch.autograd import Variable
  from sklearn.metrics import f1_score
label_desc: Use image node_id 9 for calling the Net obj's underlying member method code with example usage: obj.sample_n(num_words, input, temperature, hidden) and returns: preds,  hidden