Want to try and add a new CRF layer for sequence tagging / prediction,
and will implement Viterbi decoding and NLL as the loss value.

There is some logic needed to properly create the transitions matrix, so
add an initializer function using range + xavier uniform, and disallow
Any -> BOS or EOS -> Any transitions.

Following other implementations, will do scores + log partition function
for the forward pass (getting NLL).

Uses array passed in and only reshapes if needed (the new Tensor has a
larger size than the old one).  Needed / think should help when doing
index_select with each subset of the same size.

Example here is selecting batch_size for each time step in CRF
emissions.

Ran 'nimpretty' to clean up formatting / long lines, and passed more
information to the nnp_crf functions.

Implementation of forward pass underway, starting with scores (non
normalized log prob with emission + transition components).

Fix some bugs with CRF non-normalized score calculation (mostly making
sure that not returning matrix when shouldn't when using index_select).

Also fix some out-of-bounds bug due to loop over time steps.