class_docstr: Learner for Sequence Taggers.
class_docstr_tok: ["Learner","for","Sequence","Taggers","."]
docstr: a wrapper to model.save
docstr_tok: ["a","wrapper","to","model.save"]
code: def save_model(self, fpath):
      """
      a wrapper to model.save
      """
      self._make_model_folder(fpath)
      if U.is_crf(self.model):
          from .anago.layers import crf_loss
  
          self.model.compile(loss=crf_loss, optimizer=U.DEFAULT_OPT)
      self.model.save(
          os.path.join(fpath, U.MODEL_NAME), save_format="h5"
      )
      return
  
file_path: ktrain/ktrain/text/ner/learner.py
imports: from ...None import utils
  from ...core import GenLearner
  from ...imports import *
  from .None import metrics
label_desc: Use image node_id 5 for calling the NERLearner obj's underlying member method code with example usage: obj.save_model(fpath) without return types