Fix the GPUA version of MRG to use the same rstate shape as the CPU one.

theano/sandbox/rng_mrg.py

@@ -952,17 +952,25 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
             }
         }
 
-        if (PyGpuArray_NDIM(%(o_rstate)s) != 1)
+        if (PyGpuArray_NDIM(%(o_rstate)s) != 2)
         {
-            PyErr_SetString(PyExc_ValueError, "rstate must be vector");
-            %(fail)s;
+            PyErr_SetString(PyExc_ValueError, "rstate must be a matrix");
+            %(fail)s
         }
-        if (PyGpuArray_DIMS(%(o_rstate)s)[0] %% 6)
+        if (PyGpuArray_DIMS(%(o_rstate)s)[1] != 6)
         {
-            PyErr_Format(PyExc_ValueError, "rstate len must be multiple of 6");
-            %(fail)s;
+            PyErr_Format(PyExc_ValueError, "rstate must have 6 columns");
+            %(fail)s
+        }
+        if (%(o_rstate)s->ga.typecode != GA_INT) {
+            PyErr_Format(PyExc_ValueError, "rstate must be int32");
+            %(fail)s
+        }
+        if (!GpuArray_CHKFLAGS(&%(o_rstate)s->ga, GA_C_CONTIGUOUS)) {
+            PyErr_Format(PyExc_ValueError, "rstate must be C contiguous");
+            %(fail)s
         }
-        n_streams = PyGpuArray_DIMS(%(o_rstate)s)[0]/6;
+        n_streams = PyGpuArray_DIMS(%(o_rstate)s)[0];
         if (n_streams > n_elements)
           n_streams = n_elements;
 

theano/sandbox/test_rng_mrg.py

@@ -325,7 +325,8 @@ def test_consistency_GPUA_serial():
     for i in range(n_streams):
         stream_rstate = curr_rstate.copy()
         for j in range(n_substreams):
-            substream_rstate = numpy.array(stream_rstate.copy(), dtype='int32')
+            substream_rstate = numpy.array([stream_rstate.copy()],
+                                           dtype='int32')
             # Transfer to device
             rstate = gpuarray_shared_constructor(substream_rstate)
 
@@ -380,7 +381,7 @@ def test_consistency_GPUA_parallel():
         rstate = [curr_rstate.copy()]
         for j in range(1, n_substreams):
             rstate.append(rng_mrg.ff_2p72(rstate[-1]))
-        rstate = numpy.asarray(rstate).flatten()
+        rstate = numpy.asarray(rstate)
         rstate = gpuarray_shared_constructor(rstate)
 
         new_rstate, sample = rng_mrg.GPUA_mrg_uniform.new(rstate, ndim=None,