(self, input_shape)
initializing nn weights
initializing nn weights
initializing nn weights
def initialize_nn(self, input_shape):

        """
        initializing nn weights
        """

        loss = "keep_predict_loss"
        self.nn_builder = get_nn_builder(config_type=self.config_type)
        self.nn: NNModel = self.nn_builder(loss=loss, nn_define=self.nn_define, optimizer=self.optimizer, metrics=None,
                                           input_shape=input_shape)

        LOGGER.debug('printing nn layers structure')
        for layer in self.nn._model.layers:
            LOGGER.debug('input shape {}, output shape {}'.format(layer.input_shape, layer.output_shape))
def initialize_nn ( self , input_shape ) : loss = "keep_predict_loss" self . nn_builder = get_nn_builder ( config_type = self . config_type ) self . nn : NNModel = self . nn_builder ( loss = loss , nn_define = self . nn_define , optimizer = self . optimizer , metrics = None , input_shape = input_shape ) LOGGER . debug ( 'printing nn layers structure' ) for layer in self . nn . _model . layers : LOGGER . debug ( 'input shape {}, output shape {}' . format ( layer . input_shape , layer . output_shape ) )