Allowing model targets to be in a different space from model outputs

In response to: https://github.com/lisa-lab/pylearn2/issues/1004

When returning data_specs, DefaultDatasetMixin and get_monitoring_data_specs now call get_target_space instead of get_output_space. The base model class's get_target_space defaults to get_output_space unless the model has specified the _target_space attribute.

Softmax now has 2 new inputs: binary_targets and target_dim which allow the user to have a softmax with IndexSpace targets. This saves a lot of computation time not transfering and multiplying one-hot vectors.
I am not sure that you can pass a dtype object to Theano; I think Theano
always wants strings (dunno why this decision was made, but that's the way
it is AFAIK). What happens if you call str(np.intp)?