CRF head [WIP] #393
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CRF head [WIP] #393
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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.
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Don't hesitate to ask if you are stuck on a specific thing. |
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Thanks, appreciate it! I'm going to try and pick this up again tonight/tomorrow and will probably have some better questions once I'm done with the forward pass. |
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Haven't forgotten about this, just haven't had as much time to work on this as I thought I would. |
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No problem, I don't have much time myself |
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I'm going to need some help refining this (especially not sure yet how the backward pass will work), but I think that I can add a CRF head for sequence prediction that should work with (for example) the GRU layer.
I've been mostly following your guide #331
TODO: