code: def score(self, X, y=None):
      ds = self.get_dataset(X)
      target_iterator = self.get_iterator(ds, training=False)
  
      y_true = np.concatenate(
          [skorch.utils.to_numpy(y) for _, y in target_iterator]
      )
      y_pred = self.predict(X)
  
      return f1_score(y_true, y_pred, average="micro")
  
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 10 for calling the Net obj's underlying member method code with example usage: obj.score(X, y) and returns: f1_score