docstr: Returns the f1-micro score on the given test data and labels.
  
  Args:
      x_test : array-like, shape = (n_samples, sent_length)
      Test samples.
  
      y_test : array-like, shape = (n_samples, sent_length)
      True labels for x.
  
  Returns:
      score : float, f1-micro score.
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code: def score(self, x_test, y_test):
      """Returns the f1-micro score on the given test data and labels.
  
      Args:
          x_test : array-like, shape = (n_samples, sent_length)
          Test samples.
  
          y_test : array-like, shape = (n_samples, sent_length)
          True labels for x.
  
      Returns:
          score : float, f1-micro score.
      """
      if self.model:
          x_test = self.p.transform(x_test)
          lengths = map(len, y_test)
          y_pred = self.model.predict(x_test)
          y_pred = self.p.inverse_transform(y_pred, lengths)
          score = metrics.f1_score(y_test, y_pred)
          return score
      else:
          raise OSError("Could not find a model. Call load(dir_path).")
  
file_path: ktrain/ktrain/text/ner/anago/wrapper.py
imports: from ....imports import *
  from ..None import metrics
  from .models import BiLSTMCRF, load_model, save_model
  from .preprocessing import IndexTransformer
  from .tagger import Tagger
  from .trainer import Trainer
  from .utils import filter_embeddings
label_desc: Use image node_id 3 for calling the Sequence obj's underlying member method code with example usage: obj.score(x_test, y_test) and returns: score