def dense(x, size, name, weight_init=None, bias_init=0, weight_loss_dict=None, reuse=None): with tf.variable_scope(name, reuse=reuse): assert (len(U.scope_name().split('/')) == 2) w = tf.get_variable("w", [x.get_shape()[1], size], initializer=weight_init) b = tf.get_variable("b", [size], initializer=tf.constant_initializer(bias_init)) weight_decay_fc = 3e-4 if weight_loss_dict is not None: weight_decay = tf.multiply(tf.nn.l2_loss(w), weight_decay_fc, name='weight_decay_loss') if weight_loss_dict is not None: weight_loss_dict[w] = weight_decay_fc weight_loss_dict[b] = 0.0 tf.add_to_collection(U.scope_name().split('/')[0] + '_' + 'losses', weight_decay) return tf.nn.bias_add(tf.matmul(x, w), b)