context kind is now a bytes.

theano/gpuarray/dnn.py

@@ -125,7 +125,7 @@ def dnn_available(context_name):
 
     ctx = get_context(context_name)
 
-    if not ctx.kind == 'cuda':
+    if not ctx.kind == b'cuda':
         dnn_available.msg = "Not on a CUDA device."
         return False
 

theano/gpuarray/elemwise.py

@@ -554,7 +554,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
 
     def make_node(self, x):
         x = as_gpuarray_variable(x, infer_context_name(x))
-        if x.type.context.kind != 'cuda':
+        if x.type.context.kind != b'cuda':
             raise TypeError("GpuCAReduceCuda doesn't work for non-cuda devices")
         ret = super(GpuCAReduceCuda, self).make_node(x)
         self = copy.copy(self)

theano/gpuarray/extra_ops.py

@@ -218,7 +218,7 @@ class GpuCumsum(GpuKernelBase, Op):
         return kernels
 
     def c_code(self, node, nodename, inp, out, sub):
-        if node.inputs[0].type.context.kind != 'cuda':
+        if node.inputs[0].type.context.kind != b'cuda':
             raise NotImplementedError("cuda only")
         x, = inp
         z, = out

theano/gpuarray/neighbours.py

@@ -243,7 +243,7 @@ class GpuImages2Neibs(GpuKernelBase, Images2Neibs, Op):
         return kernels
 
     def c_code(self, node, name, inp, out, sub):
-        if node.inputs[0].type.context.kind != 'cuda':
+        if node.inputs[0].type.context.kind != b'cuda':
             raise NotImplementedError("cuda only")
         dtype_ten4 = node.inputs[0].dtype
         dtype_neib_shape = node.inputs[1].dtype

theano/gpuarray/nnet.py

@@ -189,7 +189,7 @@ class GpuCrossentropySoftmaxArgmax1HotWithBias(GpuKernelBase, Op):
                        flags=flags, objvar=k_var)]
 
     def c_code(self, node, nodename, inp, out, sub):
-        if node.inputs[0].type.context.kind != 'cuda':
+        if node.inputs[0].type.context.kind != b'cuda':
             raise NotImplementedError('cuda only')
         typecode_x = pygpu.gpuarray.dtype_to_typecode(node.inputs[0].dtype)
         typecode_b = pygpu.gpuarray.dtype_to_typecode(node.inputs[1].dtype)
@@ -375,7 +375,7 @@ class GpuCrossentropySoftmax1HotWithBiasDx(GpuKernelBase, Op):
         return ['<numpy_compat.h>', '<gpuarray/types.h>']
 
     def c_code(self, node, nodename, inp, out, sub):
-        if node.inputs[0].type.context.kind != 'cuda':
+        if node.inputs[0].type.context.kind != b'cuda':
             raise NotImplementedError("cuda only")
         typecode_dx = pygpu.gpuarray.dtype_to_typecode(node.outputs[0].dtype)
         itemsize_dnll = numpy.dtype(node.inputs[0].dtype).itemsize
@@ -584,7 +584,7 @@ class GpuSoftmax(GpuKernelBase, Op):
         return ['<numpy_compat.h>', '<gpuarray/types.h>']
 
     def c_code(self, node, nodename, inp, out, sub):
-        if node.inputs[0].type.context.kind != 'cuda':
+        if node.inputs[0].type.context.kind != b'cuda':
             raise NotImplementedError("cuda only")
         dtype_x = node.inputs[0].dtype
         work_x = work_dtype(dtype_x)
@@ -783,7 +783,7 @@ class GpuSoftmaxWithBias(GpuKernelBase, Op):
         return ['<numpy_compat.h>', '<gpuarray/types.h>']
 
     def c_code(self, node, nodename, inp, out, sub):
-        if node.inputs[0].type.context.kind != 'cuda':
+        if node.inputs[0].type.context.kind != b'cuda':
             raise NotImplementedError('cuda only')
         dtype_x = node.inputs[0].dtype
         dtype_b = node.inputs[1].dtype

theano/gpuarray/opt.py

@@ -145,7 +145,7 @@ def op_lifter(OP, cuda_only=False):
                 # Check if we should replace
                 if (not replace or
                     (cuda_only and
-                     get_context(context_name).kind != 'cuda')):
+                     get_context(context_name).kind != b'cuda')):
                     return False
 
                 # tag the inputs with the context in case
@@ -642,7 +642,7 @@ def local_gpua_advanced_subtensor(node, context_name):
 def local_gpua_advanced_incsubtensor(node, context_name):
     context = get_context(context_name)
     # This is disabled on non-cuda contexts
-    if context.kind != 'cuda':
+    if context.kind != b'cuda':
         return None
 
     x, y, ilist = node.inputs
@@ -673,12 +673,12 @@ def local_gpua_careduce(node, context_name):
     if isinstance(node.op.scalar_op, (scalar.Add, scalar.Mul,
                                       scalar.Maximum, scalar.Minimum)):
         ctx = get_context(context_name)
-        if ctx.kind == 'opencl':
+        if ctx.kind == b'opencl':
             op = GpuCAReduceCPY
             if node.op.scalar_op not in [scalar.add, scalar.mul]:
                 # We don't support yet all reduction with cpy code.
                 return
-        elif ctx.kind == 'cuda':
+        elif ctx.kind == b'cuda':
             op = GpuCAReduceCuda
         else:
             return False

theano/gpuarray/subtensor.py

@@ -599,7 +599,7 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
 
     def c_code(self, node, name, inputs, outputs, sub):
         ctx = self.get_params(node)
-        if ctx.kind != 'cuda':
+        if ctx.kind != b'cuda':
             raise NotImplementedError("cuda only")
         if (self.set_instead_of_inc or
                 node.inputs[0].ndim != node.inputs[1].ndim or

theano/gpuarray/tests/test_elemwise.py

@@ -197,7 +197,7 @@ class test_GpuCAReduceCuda(test_GpuCAReduceCPY):
 
     def setUp(self):
         super(test_GpuCAReduceCuda, self).setUp()
-        if get_context(test_ctx_name).kind != 'cuda':
+        if get_context(test_ctx_name).kind != b'cuda':
             raise SkipTest("Cuda specific tests")
 
 
@@ -212,7 +212,7 @@ class T_gpureduce_dtype(test_elemwise.T_reduce_dtype):
               'float32', 'float64']
 
     def setUp(self):
-        if get_context(test_ctx_name).kind != 'cuda':
+        if get_context(test_ctx_name).kind != b'cuda':
             raise SkipTest("Cuda specific tests")
 
 

theano/gpuarray/tests/test_extra_ops.py

@@ -24,7 +24,7 @@ class TestGpuCumsum(theano.tensor.tests.test_extra_ops.TestCumsumOp):
     def setUp(self):
         super(TestGpuCumsum, self).setUp()
         test_ctx = get_context(test_ctx_name)
-        if test_ctx.kind != 'cuda':
+        if test_ctx.kind != b'cuda':
             raise SkipTest("Cuda specific tests")
         self.max_threads_dim0 = test_ctx.maxlsize0
         self.max_grid_size1 = test_ctx.maxgsize2

theano/gpuarray/tests/test_opt.py

@@ -124,7 +124,7 @@ def test_reduce():
         topo = f.maker.fgraph.toposort()
         ops = [type(node.op) for node in topo]
 
-        if kind == 'opencl' and method in ["max", "min"]:
+        if kind == b'opencl' and method in ["max", "min"]:
             assert not(GpuCAReduceCuda in ops or GpuCAReduceCPY in ops)
         else:
             assert GpuCAReduceCuda in ops or GpuCAReduceCPY in ops