made the theano flags force_device a bool.

doc/library/config.txt

@@ -105,9 +105,11 @@ Config Attributes
 
 .. attribute:: force_device
 
-    String value: either 'cpu', gpu, 'gpu0', 'gpu1', 'gpu2', or 'gpu3'
+    Bool value: either True or False
+
+    Default False
 
-    As the attribute 'device' except that if we can't use the gpu, we raise an error.
+    If True, we raise an error if we can't use the specified device. If False, we fall back to the cpu.
     Have precedence over the device flag.
 
 .. attribute:: floatX

doc/tutorial/using_gpu.txt

@@ -46,7 +46,7 @@ You can also set the device option in the .theanorc file's ``[global]`` section.
 * You can choose one specific gpu by giving device the one of those values: gpu0, gpu1, gpu2, or gpu3.  
     * If you have more than 4 devices you are very lucky but you'll have to modify theano's *configdefaults.py* file and define more gpu devices to choose from.
 * Using the 'device=gpu*' theano flag make theano fall back to the cpu if their is a problem with the gpu. 
-  You can use the flag 'force_device=gpu*' to have theano raise an error when we can't use the gpu.
+  You can use the flag 'force_device=True' to have theano raise an error when we can't use the gpu.
 
 .. note::
     There is a compatibility issue affecting some Ubuntu 9.10 users, and probably anyone using

theano/__init__.py

@@ -75,7 +75,7 @@ import scalar
 import gradient
 import gof
 
-if config.device.startswith('gpu') or config.force_device.startswith('gpu'):
+if config.device.startswith('gpu'):
     import theano.sandbox.cuda
 
 ## import scalar_opt

theano/configdefaults.py

@@ -16,8 +16,8 @@ AddConfigVar('device',
         )
 
 AddConfigVar('force_device',
-        "Have precedence over device if not equal cpu.",
-        EnumStr('cpu', 'gpu',*['gpu%i'%i for i in range(4)])
+        "Raise an error if we can't use the specified device",
+        BoolParam(False)
         )
 
 AddConfigVar('mode',
@@ -80,6 +80,10 @@ AddConfigVar('traceback.limit',
              "The number of stack to trace. -1 mean all.",
              IntParam(5))
 
+AddConfigVar('experimental.mrg',
+             "Another random number generator that work on the gpu",
+             BoolParam(False))
+
 
 ###
 ### To disable some warning about old bug that are fixed now.

theano/sandbox/cuda/__init__.py

@@ -91,8 +91,6 @@ except Exception, e:
 
 if cuda_available:
     cuda_available=device_available()
-    if not cuda_available:
-        warning('CUDA is installed, but GPU device is not available')
 
 if cuda_available:
     #check if their is an old cuda_ndarray that was loading instead of the one we compiled!
@@ -122,6 +120,12 @@ if cuda_available:
 
 def use(device, force=False):
     global cuda_enabled
+    if force and not cuda_available and device.startswith('gpu'):
+        raise Exception("You force to use a gpu device but cuda is not installed or their is no usable gpu device")
+    if not cuda_available:
+        warning('CUDA is installed, but GPU device is not available')
+        return 
+
     if device == 'gpu':
         pass
     elif device.startswith('gpu'):
@@ -159,6 +163,15 @@ def use(device, force=False):
                    'fast_run',
                    'inplace')
 
+    if force:
+        try:
+            #in case the device if just gpu, we check that the driver init it correctly.
+            cuda_ndarray.cuda_ndarray.CudaNdarray.zeros((5,5))
+        except (Exception, NameError), e:#NameError when no gpu present as cuda_ndarray is not loaded.
+            e.args+=("ERROR: GPU did not work and we told to don't use the cpu. ",)
+            raise
+
+
 use.device_number = None
 
 def handle_shared_float32(tf):
@@ -173,16 +186,5 @@ def handle_shared_float32(tf):
     else:
         raise NotImplementedError('removing our handler')
 
-if cuda_available and config.force_device.startswith('gpu'):
-    use(config.force_device, True)
-elif cuda_available and config.device.startswith('gpu'):
-    use(config.device)
-
-
-if config.force_device.startswith('gpu'):
-        try:
-            #in case the device if just gpu, we check that the driver init it correctly.
-            cuda_ndarray.cuda_ndarray.CudaNdarray.zeros((5,5))
-        except (Exception, NameError), e:#NameError when no gpu present as cuda_ndarray is not loaded.
-            e.args+=("ERROR: GPU did not work and we told to don't use the cpu. ",)
-            raise
+if config.device.startswith('gpu'):
+    use(config.device, config.force_device)