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NMZivkovic/gibs_sampling.py

Created October 19, 2018 17:30
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gibs_sampling.py
input_matrix = tf.transpose(tf.stack([self._input_sample for i in range(hidden_dim)]))
_hidden_probabilities = tf.sigmoid(tf.add(tf.multiply(input_matrix, self._weights), tf.stack([self._hidden_biases[0] for i in range(visible_dim)])))
self._hidden_states = self.callculate_state(_hidden_probabilities)
_visible_probabilities = tf.sigmoid(tf.add(tf.multiply(self._hidden_states, self._weights), tf.transpose(tf.stack([self._visible_biases[0] for i in range(hidden_dim)]))))
self._visible_cdstates = self.callculate_state(_visible_probabilities)
self._hidden_cdstates = self.callculate_state(tf.sigmoid(tf.multiply(self._visible_cdstates, self._weights) + self._hidden_biases))
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