Rename GpuCAReduce to GpuCAReduceCPY

theano/sandbox/gpuarray/elemwise.py

@@ -518,7 +518,7 @@ class GpuDimShuffle(HideC, DimShuffle):
         return (3,)
 
 
-class GpuCAReduce(GpuKernelBase, HideC, CAReduceDtype):
+class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
     def __init__(self, scalar_op, axis=None, dtype=None, acc_dtype=None):
         if not hasattr(scalar_op, 'identity'):
             raise ValueError("No identity on scalar op")
@@ -550,7 +550,7 @@ class GpuCAReduce(GpuKernelBase, HideC, CAReduceDtype):
     def make_thunk(self, node, storage_map, compute_map, no_recycling):
         # cache the kernel object
         self.get_kernel_cache(node)
-        return super(GpuCAReduce, self).make_thunk(node, storage_map,
+        return super(GpuCAReduceCPY, self).make_thunk(node, storage_map,
                                                    compute_map, no_recycling)
 
     def get_kernel_cache(self, node):
@@ -732,7 +732,7 @@ class GpuCAReduce(GpuKernelBase, HideC, CAReduceDtype):
         err = GpuKernel_call(&%(k_var)s, 0, %(ls)s, gs, args);
         if (err != GA_NO_ERROR) {
             PyErr_Format(PyExc_RuntimeError,
-                         "compyte error: GpuCAReduce: %%s.",
+                         "compyte error: GpuCAReduceCPY: %%s.",
                          GpuKernel_error(&%(k_var)s, err));
             %(fail)s
         }
@@ -741,7 +741,7 @@ class GpuCAReduce(GpuKernelBase, HideC, CAReduceDtype):
             err = GpuArray_move(&%(output)s->ga, &tmp->ga);
             if (err != GA_NO_ERROR) {
                 PyErr_Format(PyExc_RuntimeError,
-                             "compyte error: GpuCAReduce [cast]: %%s.",
+                             "compyte error: GpuCAReduceCPY [cast]: %%s.",
                              GpuArray_error(&tmp->ga, err));
                 %(fail)s
             }

theano/sandbox/gpuarray/opt.py

@@ -24,7 +24,7 @@ from theano.sandbox.gpuarray.conv import GpuConv
 from theano.sandbox.gpuarray.nnet import (GpuCrossentropySoftmaxArgmax1HotWithBias,
                                           GpuCrossentropySoftmax1HotWithBiasDx)
 from theano.sandbox.gpuarray.elemwise import (GpuElemwise, _is_scalar,
-                                              GpuDimShuffle, GpuCAReduce)
+                                              GpuDimShuffle, GpuCAReduceCPY)
 from theano.sandbox.gpuarray.subtensor import GpuIncSubtensor, GpuSubtensor
 from theano.sandbox.gpuarray.type import GpuArrayConstant
 
@@ -249,7 +249,7 @@ def local_gpua_incsubtensor(node):
 def local_gpua_careduce(node):
     if (isinstance(node.op.scalar_op, scalar.basic.Add) or
         isinstance(node.op.scalar_op, scalar.basic.Mul)):
-        return GpuCAReduce(node.op.scalar_op, axis=node.op.axis,
+        return GpuCAReduceCPY(node.op.scalar_op, axis=node.op.axis,
                            dtype=getattr(node.op, 'dtype', None),
                            acc_dtype=getattr(node.op, 'acc_dtype', None))
 

theano/sandbox/gpuarray/tests/test_elemwise.py

@@ -10,7 +10,7 @@ from theano.tensor.tests.test_elemwise import (test_Broadcast, test_DimShuffle,
 
 from theano.sandbox.gpuarray.tests.test_basic_ops import rand_gpuarray
 from theano.sandbox.gpuarray.elemwise import (GpuElemwise, GpuDimShuffle,
-                                              GpuCAReduce)
+                                              GpuCAReduceCPY)
 from theano.sandbox.gpuarray.type import GpuArrayType
 
 from pygpu.array import gpuarray
@@ -37,10 +37,11 @@ class test_gpu_Broadcast(test_Broadcast):
 class test_GpuDimShuffle(test_DimShuffle):
     op = GpuDimShuffle
 
-class test_GpuCAReduce(test_CAReduce):
+
+class test_GpuCAReduceCPY(test_CAReduce):
     dtypes = ["float32"]
     bin_dtypes = ["uint8", "int8"]
-    op = GpuCAReduce
+    op = GpuCAReduceCPY
     reds = [scalar.add, scalar.mul]
 
     def test_perform(self):

theano/sandbox/gpuarray/tests/test_opt.py

@@ -3,7 +3,7 @@ import numpy
 import theano
 from theano.tests import unittest_tools as utt
 from theano.sandbox.gpuarray.basic_ops import GpuAlloc, GpuReshape, gpu_alloc
-from theano.sandbox.gpuarray.elemwise import GpuCAReduce
+from theano.sandbox.gpuarray.elemwise import GpuCAReduceCPY
 import theano.sandbox.gpuarray
 from theano.tests.unittest_tools import SkipTest
 
@@ -69,7 +69,7 @@ def test_sum_prod():
         res = f(val)
         utt.assert_allclose(res, val.sum())
         assert res.shape == ()
-        assert GpuCAReduce in [type(node.op)
+        assert GpuCAReduceCPY in [type(node.op)
                                for node in f.maker.fgraph.toposort()]