def _create_model(self):
# TODO hidden_layers to be fixed
# hidden_layers = self.params[HIDDEN_LAYERS][0]
hidden_layers = self.params[HIDDEN_LAYERS]
mb = ModelBuilder()
# b = a.grab("tensorflow.python.estimator.canned.linear.LinearRegressor", self.feature_columns)
self.params['n_classes'] = len(self.label_unique_values) if self.label_unique_values is not None else 0
self.params['label_vocabulary'] = self.label_unique_values
self.params['config'] = self.runConfig
self.params['hidden_units'] = hidden_layers
self.params['dnn_hidden_units'] = hidden_layers
self.params['dnn_dropout'] = self.params['dropout']
self.params['dnn_optimizer'] = self.params['optimizer']
self.params['linear_optimizer'] = self.params['optimizer']
self.params['activation_fn'] = getattr(tf.nn, self.params['activation_fn'])
self.model = mb.create_from_model_name(self.params['model_name'], self.feature_columns, self.params)
