Merge pull request #3767 from lamblin/gpuarray_py3

theano/sandbox/gpuarray/basic_ops.py

@@ -12,7 +12,7 @@ from theano.gof.utils import MethodNotDefined
 
 from collections import deque
 
-from six import string_types
+from six import string_types, iterbytes
 from six.moves import xrange
 
 try:
@@ -195,7 +195,7 @@ class GpuKernelBase(object):
         gk = gpuarray.GpuKernel(k.code, k.name, k.params, context=ctx,
                                 **k.flags)
         bin = gk._binary
-        bcode = ','.join(hex(ord(c)) for c in bin)
+        bcode = ','.join(hex(c) for c in iterbytes(bin))
         return ("""static const char %(bname)s[] = { %(bcode)s };""" %
                 dict(bname=k.binvar, bcode=bcode))
 
@@ -943,6 +943,13 @@ class GpuJoin(HideC, Join):
     def c_code_cache_version(self):
         return (2,)
 
+    def c_support_code(self):
+        return """
+#if PY_MAJOR_VERSION >= 3
+#define PyInt_AsLong PyLong_AsLong
+#endif
+"""
+
     def c_code(self, node, name, inputs, out_, sub):
         copy_to_list = []
         restype = pygpu.gpuarray.dtype_to_typecode(node.outputs[0].dtype)

theano/sandbox/gpuarray/dnn.py

@@ -119,7 +119,7 @@ def dnn_available(context_name):
 
     # This is a hack because bin_id is in the from of
     # "<something>_<major><minor>" for cuda devices.
-    if ctx.bin_id[:-2] < '30':
+    if ctx.bin_id[-2:] < b'30':
         dnn_available.msg = "Device not supported by cuDNN"
         return False
 

theano/sandbox/gpuarray/subtensor.py

@@ -632,7 +632,7 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
         if (self.set_instead_of_inc or
                 node.inputs[0].ndim != node.inputs[1].ndim or
                 node.inputs[0].ndim != 2 or
-                ctx.bin_id[-2] < '2'):
+                ctx.bin_id[-2] < b'2'):
             raise NotImplementedError("This case does not have C code yet.")
 
         x = inputs[0]