class_docstr: Intent Extraction model base class (using tf.keras)
class_docstr_tok: ["Intent","Extraction","model","base","class","(","using","tf.keras",")"]
docstr: Train a model given input samples and target labels.
  
  Args:
      x: input samples
      y: input sample labels
      epochs (:obj:`int`, optional): number of epochs to train
      batch_size (:obj:`int`, optional): batch size
      callbacks(:obj:`Callback`, optional): Keras compatible callbacks
      validation(:obj:`list` of :obj:`numpy.ndarray`, optional): optional validation data
          to be evaluated when training
docstr_tok: ["Train","a","model","given","input","samples","and","target","labels",".","Args",":","x",":","input","samples","y",":","input","sample","labels","epochs","(",":","obj",":","`","int","`",",","optional",")",":","number","of","epochs","to","train","batch_size","(",":","obj",":","`","int","`",",","optional",")",":","batch","size","callbacks","(",":","obj",":","`","Callback","`",",","optional",")",":","Keras","compatible","callbacks","validation","(",":","obj",":","`","list","`","of",":","obj",":","`","numpy.ndarray","`",",","optional",")",":","optional","validation","data","to","be","evaluated","when","training"]
code: def fit(
      self,
      x,
      y,
      epochs=1,
      batch_size=1,
      callbacks=None,
      validation=None,
  ):
      """
      Train a model given input samples and target labels.
  
      Args:
          x: input samples
          y: input sample labels
          epochs (:obj:`int`, optional): number of epochs to train
          batch_size (:obj:`int`, optional): batch size
          callbacks(:obj:`Callback`, optional): Keras compatible callbacks
          validation(:obj:`list` of :obj:`numpy.ndarray`, optional): optional validation data
              to be evaluated when training
      """
      assert self.model, "Model was not initialized"
      self.model.fit(
          x,
          y,
          epochs=epochs,
          batch_size=batch_size,
          shuffle=True,
          validation_data=validation,
          callbacks=callbacks,
      )
  
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 2 for calling the IntentExtractionModel obj's underlying member method code with example usage: obj.fit(x, y, epochs, batch_size, callbacks, validation) without return types