def _create_placeholders(self, n_features, n_classes):

        """ Create the TensorFlow placeholders for the model.
        :param n_features: number of features of the first layer
        :param n_classes: number of classes
        :return: self
        """

        self.keep_prob = tf.placeholder('float')
        self.hrand = [tf.placeholder('float', [None, self.layers[l+1]]) for l in range(self.n_layers-1)]
        self.vrand = [tf.placeholder('float', [None, self.layers[l]]) for l in range(1-self.n_layers)]

        self.x = tf.placeholder('float', [None, n_features])
        self.y_ = tf.placeholder('float', [None, n_classes])
dataset/ETHPy150Open blackecho/Deep-Learning-TensorFlow/models/rbm_models/dbn.py/DBN._create_placeholders/swapped operands of `-`