else:
x_input = self.X_ph
// two dense hidden layers with 15 nodes each
net = tf.layers.dense(x_input, 15, activation=tf.nn.relu)
net = tf.layers.dense(net, 15, activation=tf.nn.relu)
self.estimator = net
// locations and scales of the mixture components
After Change
self.estimator = net
// locations and scales of the mixture components
self.locs = Dense(self.n_centers * self.ndim_y)(net)
//self.locs = tf.layers.dense(net, self.n_centers * self.ndim_y, activation=None)
self.locs = locs = tf.reshape(self.locs, (-1, self.n_centers, self.ndim_y))
self.scales = Dense(self.n_centers * self.ndim_y, activation="softplus")(net)
