For example:
layer.printer(input=[x, y], format="x=%s y=%s")

Also remove active_type argument for many layers in config_parser.py because it is automatically
handled by LayerBase.

No longer need to specify target_inlinks or is_seq.

No longer need to use SubsequenceInput. The framework will detect.

print_layer is used to print the values of a layer when evaluating the model for debugging purpose. No layer depends on print_layer. It should be added to the topology if it is used to print some layer already in the topology.

* Compose GRU step naive layer in trainer config helpers.
  * It is uses mixed_layer for gate.
  * It supports ERROR_CLIPPING, DROPOUT
* Add error clipping in MT demo.
* Fix #1143
* Fix #1891