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_headers(self):
      return [
          "ctc.h",
          "numpy_compat.h",
          "gpuarray/ext_cuda.h",
          "gpuarray_helper.h",
          "gpuarray/types.h",
          "gpuarray_api.h",
          "gpuarray/array.h",
          "gpuarray/util.h",
          "gpuarray/extension.h",
      ]
  
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 6 for calling the GpuConnectionistTemporalClassification obj's underlying member method code with example usage: obj.c_headers() and returns: list