Make advsub1 work with type context.

theano/sandbox/gpuarray/subtensor.py

 from __future__ import print_function
 
 import copy
-import os
 
 import numpy
 
 import theano
-from theano import tensor, gof, config
-from theano.gof.utils import MethodNotDefined
+from theano import tensor, gof
 from six.moves import StringIO
 from theano.tensor.subtensor import IncSubtensor, Subtensor, get_idx_list
 import theano.tensor.inplace
@@ -19,7 +17,8 @@ except ImportError:
     pass
 
 from .type import GpuArrayType
-from .basic_ops import (as_gpuarray_variable, HideC, GpuKernelBase, Kernel)
+from .basic_ops import (as_gpuarray_variable, HideC, GpuKernelBase, Kernel,
+                        infer_context_name)
 from .elemwise import GpuElemwise
 
 
@@ -321,7 +320,7 @@ class GpuIncSubtensor(GpuKernelBase, IncSubtensor):
                                   %(view_ndim)s,
                                   dims,
                                   xview_strides,
-                                  pygpu_default_context(),
+                                  %(x)s->ctx,
                                   1,
                                   (PyObject *)%(x)s,
                                   (PyObject *)&PyGpuArrayType);
@@ -567,16 +566,16 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
     only avail on compute capability 2.0 and more recent.
 
     """
-
     _f16_ok = True
 
     def make_node(self, x, y, ilist):
         """It defer from GpuAdvancedIncSubtensor1 in that it make sure
         the index are of type long.
         """
-        x_ = as_gpuarray_variable(x)
-        y_ = as_gpuarray_variable(y)
-        ilist_ = as_gpuarray_variable(ilist)
+        ctx_name = infer_context_name(x, y, ilist)
+        x_ = as_gpuarray_variable(x, ctx_name)
+        y_ = as_gpuarray_variable(y, ctx_name)
+        ilist_ = as_gpuarray_variable(ilist, ctx_name)
 
         assert x_.type.dtype == y_.type.dtype
         assert x_.type.ndim >= y_.type.ndim
@@ -599,32 +598,24 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
 
         return gof.Apply(self, [x_, y_, ilist_], [x_.type()])
 
+    def get_context(self, node):
+        return self.node.outputs[0].type.context
+
     def c_code_cache_version(self):
         return (6,)
 
     def c_headers(self):
-        if pygpu.get_default_context().kind == 'opencl':
-            raise MethodNotDefined('cuda only')
-        return ['cuda.h', '<numpy_compat.h>', '<gpuarray_helper.h>',
+        return ['<numpy_compat.h>', '<gpuarray_helper.h>',
                 '<gpuarray/types.h>']
 
-    def c_header_dirs(self):
-        if pygpu.get_default_context().kind == 'opencl':
-            raise MethodNotDefined('cuda only')
-        cuda_root = config.cuda.root
-        res = [os.path.dirname(__file__)]
-        if cuda_root:
-            res.append(os.path.join(cuda_root, 'include'))
-        return res
-
     def c_code(self, node, name, inputs, outputs, sub):
-        active_device_no = theano.sandbox.cuda.active_device_number()
-        device_properties = theano.sandbox.cuda.device_properties
-        compute_capability = device_properties(active_device_no)['major']
-        if ((self.set_instead_of_inc) or
-                (node.inputs[0].ndim != node.inputs[1].ndim) or
-                (node.inputs[0].ndim != 2) or
-                (compute_capability < 2)):
+        ctx = self.get_context(node)
+        if ctx.kind != 'cuda':
+            raise NotImplementedError("cuda only")
+        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'):
             raise NotImplementedError("This case does not have C code yet.")
 
         x = inputs[0]