class_docstr: Bi-LSTM NER model with CRF classification layer (tf.keras model)
  
  Args:
      use_cudnn (bool, optional): use cudnn LSTM cells
code: def __init__(self, use_cudnn=False):
      self.model = None
      self.word_length = None
      self.target_label_dims = None
      self.word_vocab_size = None
      self.char_vocab_size = None
      self.word_embedding_dims = None
      self.char_embedding_dims = None
      self.tagger_lstm_dims = None
      self.dropout = None
      self.use_cudnn = use_cudnn
  
file_path: nlp-architect/nlp_architect/models/ner_crf.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import tensorflow
  from nlp_architect.nn.tensorflow.python.keras.layers.crf import CRF
  from nlp_architect.nn.tensorflow.python.keras.utils import load_model, save_model
label_desc: Use image node_id 1 to create a new NERCRF object from inherited base classes: object with example: obj = NERCRF(use_cudnn)