Small modif follow code review

doc/acknowledgement.txt

@@ -24,4 +24,4 @@ Acknowledgements
     P. L'Ecuyer and R. Touzin, `Fast Combined Multiple Recursive Generators with Multipliers of the form a = +/- 2^d +/- 2^e <http://www.informs-sim.org/wsc00papers/090.PDF>`_, Proceedings of the 2000 Winter Simulation Conference, Dec. 2000, 683--689.
 
   We were authorized by Pierre L'Ecuyer to copy/modify his Java implementation in the `SSJ <http://www.iro.umontreal.ca/~simardr/ssj/>`_ software and to relicense it under BSD 3-Clauses in Theano.
-* A better GPU memory allocator :attr:`CNMeM <config.lib.cnmem>` is included in Theano. It have the same license.
+* A better GPU memory allocator :attr:`CNMeM <config.lib.cnmem>` is included in Theano. It has the same license.

doc/library/config.txt

@@ -380,8 +380,9 @@ import theano and print the config variable, as in:
 
     That library is included in Theano, you do not need to install it.
 
-    The value represent the start size (in MB or % of
-    total GPU memory) of the memory pool:
+    The value represents the start size (in MB or % of total GPU
+    memory) of the memory pool. If more memory are needed, it will
+    try to get more, but this can cause more memory fragmentation:
 
         * 0: not enabled.
         * 0 < N <= 1: % of the total GPU memory (clipped to .985 for driver memory)
@@ -392,9 +393,9 @@ import theano and print the config variable, as in:
 
     .. note::
 
-        This could cause memory fragmentation. So if you have an
+        This could cause memory fragmentation. So if you have a
         memory error while using cnmem, try to allocate more memory at
-        the start or without it. If you try this, report your result
+        the start or disable it. If you try this, report your result
         on :ref`theano-dev`.
 
 .. attribute:: linker

theano/sandbox/cuda/cuda_ndarray.cu

@@ -3143,7 +3143,8 @@ CudaNdarray_gpu_init(PyObject* _unused, PyObject* args)
     int card_number_provided = 1;
     float cnmem = 0; // Theano flag lib.cnmem
     // if we're given something wildly invalid, this will throw a TypeError
-    PyArg_ParseTuple(args, "|if", &card_nb, &cnmem);
+    if(!PyArg_ParseTuple(args, "|if", &card_nb, &cnmem))
+        return NULL;
     if(cnmem)
         g_use_cnmem = true;