| self._num_iter = number_of_iterations | |
| self._visible_biases = tf.Variable(tf.random_uniform([1, visible_dim], 0, 1, name = "visible_biases")) | |
| self._hidden_biases = tf.Variable(tf.random_uniform([1, hidden_dim], 0, 1, name = "hidden_biases")) | |
| self._hidden_states = tf.Variable(tf.zeros([1, hidden_dim], tf.float32, name = "hidden_biases")) | |
| self._visible_cdstates = tf.Variable(tf.zeros([1, visible_dim], tf.float32, name = "visible_biases")) | |
| self._hidden_cdstates = tf.Variable(tf.zeros([1, hidden_dim], tf.float32, name = "hidden_biases")) | |
| self._weights = tf.Variable(tf.random_normal([visible_dim, hidden_dim], 0.01), name="weights") | |
| self._leraning_rate = tf.Variable(tf.fill([visible_dim, hidden_dim], learning_rate), name = "learning_rate") | |
| self._input_sample = tf.placeholder(tf.float32, [visible_dim], name = "input_sample") |
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