def _get_b(self): common.print_func_name(self._get_b) layer = self.weighted_layers[0] print(self.sess.run(layer.b))
def _init_weight_values(n_inputs, n_outputs, shape): common.print_func_name(Relu._init_weight_values) print(shape) w_values = tf.truncated_normal(shape=shape, stddev=1. / math.sqrt(float(shape[0]))) return w_values