def _build_shared_graph(self):
with tf.variable_scope(self._scope, reuse=self._reuse):
_encoder = MultiLayerFC(l2_reg=self._l2_reg,
in_tensor=self._in_tensor,
dims=self._dims[1:],
scope='encoder',
dropout_in=self._dropout,
dropout_mid=self._dropout,
reuse=self._reuse)
_decoder = MultiLayerFC(l2_reg=self._l2_reg,
in_tensor=_encoder.get_outputs()[0],
dims=self._dims[::-1][1:],
scope='decoder',
relu_in=True,
dropout_in=self._dropout,
relu_mid=True,
dropout_mid=self._dropout,
relu_out=True,
dropout_out=self._dropout,
reuse=self._reuse)
self._outputs += _encoder.get_outputs()
self._loss = _encoder.get_loss() + _decoder.get_loss()
self._loss += self._l2_reconst * tf.nn.l2_loss(
_decoder.get_outputs()[0] - self._in_tensor)
def _build_shared_graph(self):
with tf.variable_scope(self._scope, reuse=self._reuse):
self._embedding = tf.get_variable('embedding',
dtype=tf.float32,
shape=self._shape,
trainable=False,
initializer=self._initializer)
self._flag = tf.get_variable('flag',
dtype=tf.bool,
shape=[self._shape[0]],
trainable=False,
initializer=tf.constant_initializer(
value=False, dtype=tf.bool))
unique_ids, _ = tf.unique(self._ids)
with tf.control_dependencies([
tf.scatter_update(self._flag, unique_ids,
tf.ones_like(unique_ids, dtype=tf.bool))
]):
trans_embedding = MultiLayerFC(
in_tensor=tf.nn.embedding_lookup(self._embedding,
self._ids),
dims=self._mlp_dims,
batch_norm=True,
scope=self._scope + '/MLP',
train=self._train,
reuse=self._reuse,
l2_reg=self._l2_reg,
relu_out=True)
self._outputs += trans_embedding.get_outputs()
self._loss += trans_embedding.get_loss()
update_ids = tf.reshape(tf.where(self._flag), [-1])
update_embedding = MultiLayerFC(in_tensor=tf.nn.embedding_lookup(
self._embedding, update_ids),
dims=self._mlp_dims,
batch_norm=True,
scope=self._scope + '/MLP',
train=False,
reuse=True,
l2_reg=self._l2_reg,
relu_out=True)
self._update_node = tf.scatter_update(
self._embedding, update_ids,
update_embedding.get_outputs()[0])
self._clear_flag = tf.scatter_update(
self._flag, update_ids, tf.zeros_like(update_ids,
dtype=tf.bool))
