Add a target argument to shared variable constructor to have explicit

theano/sandbox/cuda/var.py

@@ -159,7 +159,8 @@ CudaNdarrayType.SharedVariable = CudaNdarraySharedVariable
 
 
 def cuda_shared_constructor(value, name=None, strict=False,
-        allow_downcast=None, borrow=False, broadcastable=None):
+                            allow_downcast=None, borrow=False,
+                            broadcastable=None):
     """
     SharedVariable Constructor for CudaNdarrayType.
 
@@ -193,12 +194,15 @@ def cuda_shared_constructor(value, name=None, strict=False,
 
 
 def float32_shared_constructor(value, name=None, strict=False,
-        allow_downcast=None, borrow=False, broadcastable=None):
+                               allow_downcast=None, borrow=False,
+                               broadcastable=None, target='gpu'):
     """
     SharedVariable Constructor for CudaNdarrayType from numpy.ndarray or
     CudaNdarray.
 
     """
+    if target != 'gpu':
+        raise TypeError('not for gpu')
     if theano.sandbox.cuda.use.device_number is None:
         theano.sandbox.cuda.use("gpu",
                                 force=True,

theano/sandbox/gpuarray/__init__.py

@@ -24,8 +24,8 @@ except ImportError:
 # This is for documentation not to depend on the availability of pygpu
 from .type import (GpuArrayType, GpuArrayVariable, GpuArrayConstant,
                    GpuArraySharedVariable, gpuarray_shared_constructor,
-                   reg_context)
-from .basic import as_gpuarray_variable
+                   reg_context, get_context, ContextNotDefined)
+from .basic_ops import as_gpuarray_variable
 from . import opt, nerv
 
 def transfer(x, target):

theano/sandbox/gpuarray/type.py

@@ -472,27 +472,29 @@ GpuArrayType.SharedVariable = GpuArraySharedVariable
 
 def gpuarray_shared_constructor(value, name=None, strict=False,
                                 allow_downcast=None, borrow=False,
-                                broadcastable=None,
-                                context_name=None):
+                                broadcastable=None, target=None):
     """
     SharedVariable constructor for GpuArrayType.
 
     """
+    if target == 'gpu' or target == 'cpu':
+        raise TypeError('not for me')
+
     if not isinstance(value, (numpy.ndarray, pygpu.gpuarray.GpuArray)):
         raise TypeError('ndarray or GpuArray required')
 
     try:
-        get_context(context_name)
+        get_context(target)
     except ContextNotDefined:
         # Don't make this a hard error if we attempt to make a shared
         # variable while there is no default context.
-        if context_name is None:
+        if target is None:
             raise TypeError('No default context and no context specified')
         raise
 
     if broadcastable is None:
         broadcastable = (False,) * value.ndim
-    type = GpuArrayType(value.dtype, broadcastable, context_name=context_name)
+    type = GpuArrayType(value.dtype, broadcastable, context_name=target)
     deviceval = pygpu.gpuarray.array(value, copy=(not borrow),
                                      context=type.context)
     return GpuArraySharedVariable(type=type, value=deviceval, name=name,

theano/tensor/sharedvar.py

@@ -24,7 +24,7 @@ class TensorSharedVariable(_tensor_py_operators, SharedVariable):
 
 @shared_constructor
 def tensor_constructor(value, name=None, strict=False, allow_downcast=None,
-                       borrow=False, broadcastable=None):
+                       borrow=False, broadcastable=None, target='cpu'):
     """
     SharedVariable Constructor for TensorType.
 
@@ -36,6 +36,9 @@ def tensor_constructor(value, name=None, strict=False, allow_downcast=None,
     The optional `broadcastable` argument will override this default.
 
     """
+    if target != 'cpu':
+        raise TypeError('not for cpu')
+
     if not isinstance(value, numpy.ndarray):
         raise TypeError()
 
@@ -65,7 +68,7 @@ class ScalarSharedVariable(_tensor_py_operators, SharedVariable):
 
 @shared_constructor
 def scalar_constructor(value, name=None, strict=False, allow_downcast=None,
-                       borrow=False):
+                       borrow=False, target='cpu'):
     """
     SharedVariable constructor for scalar values. Default: int64 or float64.
 
@@ -78,6 +81,9 @@ def scalar_constructor(value, name=None, strict=False, allow_downcast=None,
     borrow, as it is a hint to Theano that we can reuse it.
 
     """
+    if target != 'cpu':
+        raise TypeError('not for cpu')
+
     if not isinstance(value, (numpy.number, float, int, complex)):
         raise TypeError()
     try: