original_docstring:  Dump all data of the neural model.
  
          This method is used in the serialization and copying of object.
  
          :return: dictionary with names and saved values of all parameters, specified in the constructor and received as
          result of training.
          
docstring: Dump all data of the neural model.
  This method is used in the serialization and copying of object.
docstring_tokens: Dump all data of the neural model . This method is used in the serialization and copying of object .
code: def dump_all(self):
          """ Dump all data of the neural model.
  
          This method is used in the serialization and copying of object.
  
          :return: dictionary with names and saved values of all parameters, specified in the constructor and received as
          result of training.
          """
          try:
              check_is_fitted(self, ['input_token_index_', 'target_token_index_', 'reverse_target_char_index_',
                                     'max_encoder_seq_length_', 'max_decoder_seq_length_',
                                     'encoder_model_', 'decoder_model_'])
              is_trained = True
          except:
              is_trained = False
          params = self.get_params(True)
          if is_trained:
              params['weights'] = self.dump_weights()
              params['input_token_index_'] = copy.deepcopy(self.input_token_index_)
              params['target_token_index_'] = copy.deepcopy(self.target_token_index_)
              params['reverse_target_char_index_'] = copy.deepcopy(self.reverse_target_char_index_)
              params['max_encoder_seq_length_'] = self.max_encoder_seq_length_
              params['max_decoder_seq_length_'] = self.max_decoder_seq_length_
          return params
code_tokens: def dump_all ( self ) : try : check_is_fitted ( self , [ 'input_token_index_' , 'target_token_index_' , 'reverse_target_char_index_' , 'max_encoder_seq_length_' , 'max_decoder_seq_length_' , 'encoder_model_' , 'decoder_model_' ] ) is_trained = True except : is_trained = False params = self . get_params ( True ) if is_trained : params [ 'weights' ] = self . dump_weights ( ) params [ 'input_token_index_' ] = copy . deepcopy ( self . input_token_index_ ) params [ 'target_token_index_' ] = copy . deepcopy ( self . target_token_index_ ) params [ 'reverse_target_char_index_' ] = copy . deepcopy ( self . reverse_target_char_index_ ) params [ 'max_encoder_seq_length_' ] = self . max_encoder_seq_length_ params [ 'max_decoder_seq_length_' ] = self . max_decoder_seq_length_ return params
short_docstring: Dump all data of the neural model.
short_docstring_tokens: Dump all data of the neural model .
comment: """ Dump all data of the neural model.
  
          This method is used in the serialization and copying of object.
  
          :return: dictionary with names and saved values of all parameters, specified in the constructor and received as
          result of training.
          """