class_docstr: CTC loss function wrapper.
  
  Notes
  -----
  Using the wrapper requires that Baidu's warp-ctc library is installed.
  If the warp-ctc library is not on your compiler's default library path,
  you must set the configuration variable ``config.ctc.root`` appropriately.
  
  Parameters
  ----------
  compute_grad
      If set to True, enables the computation of gradients of the CTC loss function.
class_docstr_tok: ["CTC","loss","function","wrapper",".","Notes","--","--","-","Using","the","wrapper","requires","that","Baidu","'s","warp-ctc","library","is","installed",".","If","the","warp-ctc","library","is","not","on","your","compiler","'s","default","library","path",",","you","must","set","the","configuration","variable","``","config.ctc.root","``","appropriately",".","Parameters","--","--","--","--","--","compute_grad","If","set","to","True",",","enables","the","computation","of","gradients","of","the","CTC","loss","function","."]
code: def c_libraries(self):
      return ["warpctc"]
  
imports: from __future__ import division, absolute_import, print_function
  import os
  import sys
  import theano.tensor
  from theano import config
  from theano import gof
  from theano.gof import local_optimizer
  from theano.gof.cmodule import GCC_compiler
  from theano.tensor.opt import register_canonicalize
  from theano.tensor.extra_ops import cpu_contiguous
  from theano.gradient import grad_undefined
label_desc: Use image node_id 4 for calling the ConnectionistTemporalClassification obj's underlying member method code with example usage: obj.c_libraries() and returns: list