fix stride bug

theano/sandbox/gpuarray/multinomial.c

@@ -70,6 +70,8 @@ int APPLY_SPECIFIC(multinomial)(PyGpuArrayObject *pvals,
 
     { // NESTED SCOPE
         int nb_multi = PyGpuArray_DIMS(pvals)[0];
+        printf("multinomail_test\n");
+        printf("%d\n",nb_multi); 
         int nb_outcomes = PyGpuArray_DIMS(pvals)[1];
         //TODO : change this for a beautiful constant
         int max_nb_blocks = 2<<15 - 1;
@@ -102,13 +104,13 @@ int APPLY_SPECIFIC(multinomial)(PyGpuArrayObject *pvals,
             PyGpuArray_DIMS(*out)[1],
             PyGpuArray_DIMS(*out)[0],
             (float*)PyGpuArray_DEV_DATA(pvals),
-            PyGpuArray_STRIDES(pvals)[0],
-            PyGpuArray_STRIDES(pvals)[1],
+            PyGpuArray_STRIDES(pvals)[0]/sizeof(float),
+            PyGpuArray_STRIDES(pvals)[1]/sizeof(float),
             (float*)PyGpuArray_DEV_DATA(unis),
-            PyGpuArray_STRIDES(unis)[0],
+            PyGpuArray_STRIDES(unis)[0]/sizeof(float),
             (float*)PyGpuArray_DEV_DATA(*out),
-            PyGpuArray_STRIDES(*out)[0],
-            PyGpuArray_STRIDES(*out)[1]
+            PyGpuArray_STRIDES(*out)[0]/sizeof(float),
+            PyGpuArray_STRIDES(*out)[1]/sizeof(float)
         );
 
 	//TODO

theano/sandbox/gpuarray/multinomial.py

@@ -60,8 +60,9 @@ class GPUAMultinomialFromUniform(COp):
 
         return Apply(self, [pvals, unis], [out])
 
-    def c_code_cache_version(self):
-        return (8,)
+ #   def c_code_cache_version(self):
+ #       return
+ #       return (8,)
 
 
 @register_opt()

theano/sandbox/gpuarray/tests/test_multinomial.py

@@ -43,8 +43,9 @@ def test_multinomial0():
     f = theano.function([p, u], m, mode=mode_with_gpu)
     theano.printing.debugprint(f)
     ret = f(numpy.array([[0.1, 0.2, 0.3, 0.4],
+                         [0.1, 0.2, 0.3, 0.4],
                          [0.1, 0.2, 0.3, 0.4]], dtype='float32'),
-            numpy.array([0.05, 0.05], dtype='float32'))
+            numpy.array([0.05, 0.05, 0.05], dtype='float32'))
     print(numpy.asarray(ret))
 
 
@@ -66,6 +67,7 @@ def test_multinomial_0():
                         for node in f.maker.fgraph.toposort()])
 
         # test that both first and second samples can be drawn
+        print(f([[1, 0], [0, 1]], [.1, .1]))
         utt.assert_allclose(f([[1, 0], [0, 1]], [.1, .1]),
                             [[2, 0], [0, 2]])