code: def _create_placeholders(self, n_features):
          
          self.input_data = tf.placeholder(tf.float32, [None, n_features],
                                           name='x-input')
          self.hrand = tf.placeholder(tf.float32, [None, self.num_hidden],
                                      name='hrand')
          self.vrand = tf.placeholder(tf.float32, [None, n_features],
                                      name='vrand')
          # not used in this model, created just to comply with
          # unsupervised_model.py
          self.input_labels = tf.placeholder(tf.float32)
          self.keep_prob = tf.placeholder(tf.float32, name='keep-probs')
docs: Create the TensorFlow placeholders for the model.
  
          :param n_features: number of features
          :return: self