class_docstr: GPU wrapper for Baidu CTC loss function.
  
  Parameters
  ----------
  compute_grad
      If set to True, enables the computation of gradients of the CTC loss function.
class_docstr_tok: ["GPU","wrapper","for","Baidu","CTC","loss","function",".","Parameters","--","--","--","--","--","compute_grad","If","set","to","True",",","enables","the","computation","of","gradients","of","the","CTC","loss","function","."]
code: def c_header_dirs(self):
      dirs = [
          gpuarray_helper_inc_dir(),
          pygpu.get_include(),
          config.cuda.include_path,
      ]
      if config.ctc.root != "":
          dirs.append(os.path.join(config.ctc.root, "include"))
      return dirs
  
imports: from __future__ import absolute_import, print_function, division
  import theano
  from theano import config, gof
  import theano.tensor
  from .basic_ops import gpu_contiguous, as_gpuarray_variable, infer_context_name, gpuarray_helper_inc_dir
  import theano.tensor.nnet.ctc
  from .type import GpuArrayType, gpu_context_type
  from .elemwise import GpuDimShuffle
  from theano.gradient import grad_undefined
  from theano.gof import local_optimizer
  from theano.tensor.opt import register_canonicalize
  from theano.tensor.nnet.ctc import ctc_available
  import os
  import sys
  from .None import pygpu
label_desc: Use image node_id 5 for calling the GpuConnectionistTemporalClassification obj's underlying member method code with example usage: obj.c_header_dirs() and returns: dirs