Add warp-ctc in the optional dependency and indicate clearly that the CPU interface is prefered.

doc/library/gpuarray/ctc.txt

@@ -4,6 +4,13 @@
 :mod:`theano.gpuarray.ctc` -- Connectionist Temporal Classification (CTC) loss
 ================================================================================
 
+
+.. warning::
+
+    This is not the recomanded user interface. Use :ref:`the CPU
+    interface <libdoc_tensor_nnet_ctc>`. It will get moved
+    automatically to the GPU.
+
 .. note::
 
     Usage of connectionist temporal classification (CTC) loss Op, requires that

doc/library/tensor/nnet/ctc.txt

@@ -12,6 +12,11 @@
     the ``config.ctc.root`` configuration option must be appropriately set to the
     directory containing the warp-ctc library files.
 
+.. note::
+
+   This interface is the prefered interface. It will be moved
+   automatically to the GPU.
+
 .. note::
 
     Unfortunately, Windows platforms are not yet supported by the underlying

doc/requirements.inc

@@ -13,6 +13,7 @@ Requirements
 .. _libgpuarray: http://deeplearning.net/software/libgpuarray/installation.html
 .. _pycuda: https://mathema.tician.de/software/pycuda/
 .. _skcuda: http://scikit-cuda.readthedocs.io/en/latest/
+.. _warp-ctc: https://github.com/baidu-research/warp-ctc
 
     Python_ == 2.7* or ( >= 3.4 and < 3.6 )
         |PythonDistRecommended|. Python 2.4 was supported up to and including the
@@ -57,6 +58,12 @@ Requirements
         cusolver: ``pip install pycuda; pip install
         git+https://github.com/lebedov/scikit-cuda.git#egg=scikit-cuda``.
 
+    `warp-ctc`_
+        Required for :ref:`Theano CTC implementation
+        <libdoc_tensor_nnet_ctc>`. It is faster then using an
+        equivalent graph of Theano ops.
+
+
 Requirements installation through Conda (recommended)
 -----------------------------------------------------