030f2785177566814a69e392337b13f48833a187,train_decaying_keep_prob.py,,keep_prob_decay,#Any#Any#Any#Any#Any#Any#Any#,37

Before Change

                    // update accumulator
                    // if trigger: reset_acculator, else accumulator[position] = va
                    accumulator = tf.cond(
                        tf.equal(trigger, 1), reset_accumulator,
                        lambda: tf.scatter_update(accumulator, position, validation_accuracy)
                    )
                    // update accumulated (for current prob)
                    // if trigger; accumulated = 1, else accumulated +=1
                    accumulated = tf.cond(
                        tf.equal(trigger, 1),

After Change

        // keep only the specified precision of validation_accuracy_
        validation_accuracy = tf.Variable(0.0)
        with tf.control_dependencies([
                tf.assign(validation_accuracy,
                          tf.ceil(validation_accuracy_ / precision) *
                          precision)
        ]):
            // trigger value: 0 (nop) or 1 (trigger)
            mean = tf.ceil(
                tf.reduce_sum(accumulator) /

Instances