Fetch the kernel name from the Kernel object in the c_code and document what Kernel represents.

theano/sandbox/gpuarray/basic_ops.py

@@ -62,6 +62,9 @@ class HideC(object):
 
 
 class Kernel(object):
+    """
+    This class groups together all the attributes of a gpu kernel.
+    """
     def __init__(self, code, params, name, flags,
                  codevar=None, binvar=None, objvar=None):
         self.code = code
@@ -833,7 +836,7 @@ KERNEL void k(GLOBAL_MEM %(ctype)s *a, ga_size n, ga_size m) {
         fail = sub['fail']
         typecode = pygpu.gpuarray.dtype_to_typecode(self.dtype)
         sync = bool(config.gpuarray.sync)
-        kname = 'k_eye_'+name
+        kname = self.gpu_kernels()[0].objvar
         s = """
         size_t dims[2] = {0, 0};
         void *args[3];

theano/sandbox/rng_mrg.py

@@ -867,8 +867,8 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
         return [Kernel(code=code, name="mrg_uniform",
                        params=[gpuarray.GpuArray, gpuarray.GpuArray,
                                'uint32', 'uint32'],
-                       flags=Kernel.get_flags(self.output_type.dtype, 'int32'),
-                       objvar='k_mrg_uniform')]
+                       flags=Kernel.get_flags(self.output_type.dtype, 'int32'))
+                ]
 
     def c_code(self, node, nodename, inp, out, sub):
         rstate, size = inp
@@ -877,7 +877,7 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
         ndim = self.output_type.ndim
         o_type_num = numpy.asarray(0, dtype=self.output_type.dtype).dtype.num
         fail = sub['fail']
-        kname = 'k_mrg_uniform'
+        kname = self.gpu_kernels()[0].objvar
 
         if self.output_type.dtype == 'float32':
             otype = 'float'