Don't use py_ version

theano/sandbox/cuda/rng_curand.py

@@ -159,7 +159,7 @@ class CURAND_Base(GpuOp):
         int odims[%(ndim)s];
         int n_elements = 1;
         int must_alloc_sample = ((NULL == %(o_sample)s)
-                || !CudaNdarray_Check(py_%(o_sample)s)
+                || !CudaNdarray_Check((PyObject*)%(o_sample)s)
                 || (CudaNdarray_NDIM(%(o_sample)s) != %(ndim)s));
 
         if (PyArray_NDIM(%(size)s) != 1)
@@ -246,7 +246,7 @@ class CURAND_Base(GpuOp):
         return code
 
     def c_code_cache_version(self):
-        return (3,)
+        return (4,)
 
 
 class CURAND_Normal(CURAND_Base):

theano/sandbox/multinomial.py

@@ -53,13 +53,13 @@ class MultinomialFromUniform(Op):
         return [T.zeros_like(x) for x in ins]
 
     def c_code_cache_version(self):
-        return (5,)
+        return (6,)
 
     def c_code(self, node, name, ins, outs, sub):
         (pvals, unis) = ins
         (z,) = outs
         if self.odtype == 'auto':
-            t = "PyArray_TYPE((PyArrayObject*) py_%(pvals)s)" % locals()
+            t = "PyArray_TYPE(%(pvals)s)" % locals()
         else:
             t = theano.scalar.Scalar(self.odtype).dtype_specs()[1]
             if t.startswith('theano_complex'):

theano/sandbox/rng_mrg.py

@@ -445,7 +445,9 @@ class mrg_uniform(mrg_uniform_base):
             }
         }
         Py_XDECREF(%(o_rstate)s);
-        %(o_rstate)s = (PyArrayObject*)PyArray_FromAny(py_%(rstate)s, NULL, 0, 0, %(o_rstate_requirement)s,NULL);
+        %(o_rstate)s = (PyArrayObject*)PyArray_FromAny(
+            (PyObject*)%(rstate)s,
+            NULL, 0, 0, %(o_rstate_requirement)s,NULL);
 
         if (PyArray_NDIM(%(o_rstate)s) != 2)
         {
@@ -526,7 +528,7 @@ class mrg_uniform(mrg_uniform_base):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (2,)
+        return (3,)
 
 
 class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
@@ -655,7 +657,7 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
         int n_elements = 1;
         int n_streams, n_streams_used_in_this_call;
         int must_alloc_sample = ((NULL == %(o_sample)s)
-                || !CudaNdarray_Check(py_%(o_sample)s)
+                || !CudaNdarray_Check((PyObject*)%(o_sample)s)
                 || !CudaNdarray_is_c_contiguous(%(o_sample)s)
                 || (CudaNdarray_NDIM(%(o_sample)s) != %(ndim)s));
 
@@ -691,7 +693,7 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
                 %(fail)s;
             }
         }
-        if (!CudaNdarray_Check(py_%(rstate)s))
+        if (!CudaNdarray_Check((PyObject*)%(rstate)s))
         {
             PyErr_Format(PyExc_ValueError, "rstate must be cudandarray");
             %(fail)s;
@@ -764,7 +766,7 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (9,)
+        return (10,)
 
 
 class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
@@ -913,7 +915,7 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
         unsigned int n_elements = 1;
         unsigned int n_streams;
         int must_alloc_sample = ((NULL == %(o_sample)s)
-                || !pygpu_GpuArray_Check(py_%(o_sample)s)
+                || !pygpu_GpuArray_Check((PyObject*)%(o_sample)s)
                 || !(%(o_sample)s->ga.flags & GA_C_CONTIGUOUS)
                 || (PyGpuArray_NDIM(%(o_sample)s) != %(ndim)s));
 
@@ -950,7 +952,7 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
                 %(fail)s;
             }
         }
-        if (!pygpu_GpuArray_Check(py_%(rstate)s))
+        if (!pygpu_GpuArray_Check((PyObject*)%(rstate)s))
         {
             PyErr_Format(PyExc_ValueError, "rstate must be gpuarray");
             %(fail)s;