Merge pull request #90 from nouiz/force_device_cpu

doc/library/config.txt

@@ -126,8 +126,13 @@ import theano and print the config variable, as in:
 
     Default: ``False``
 
-    If ``True``, we raise an error if we cannot use the specified :attr:`device`.
-    If ``False``, we fall back to the CPU.
+    If ``True`` and ``device=gpu*``, we raise an error if we cannot
+    use the specified :attr:`device`. If ``True`` and ``device=cpu``,
+    we disable the GPU.  If ``False`` and ``device=gpu*``, and if the
+    specified device cannot be used, we warn and fall back to the CPU.
+
+    This is useful to run Theano's tests on a computer with a GPU, but
+    without running the GPU tests.
 
     This flag's value cannot be modified during the program execution.
 

theano/sandbox/cuda/__init__.py

@@ -114,19 +114,6 @@ def try_import():
     return True
 
 
-# Add the theano cache directory's cuda_ndarray subdirectory to the
-# list of places that are hard-coded into compiled modules' runtime
-# library search list.  This works in conjunction with
-# nvcc_compiler.NVCC_compiler.compile_str which adds this folder during
-# compilation with -L and also adds -lcuda_ndarray when compiling
-# modules.
-nvcc_compiler.add_standard_rpath(cuda_ndarray_loc)
-
-compile_cuda_ndarray = True
-
-if not compile_cuda_ndarray:
-    compile_cuda_ndarray = not try_import()
-
 if not nvcc_compiler.is_nvcc_available() or not theano.config.cxx:
     # It can happen that the file cuda_ndarray.so is already compiled
     # but nvcc is not available. In that case we need to disable the CUDA
@@ -134,6 +121,20 @@ if not nvcc_compiler.is_nvcc_available() or not theano.config.cxx:
     # use already compiled GPU op and not the others.
     # Also, if cxx is not available, we need to disable all GPU code.
     set_cuda_disabled()
+elif not config.device.startswith('gpu') and config.force_device:
+    # We where asked to NEVER use the GPU
+    set_cuda_disabled()
+    compile_cuda_ndarray = False
+else:
+    # Add the theano cache directory's cuda_ndarray subdirectory to the
+    # list of places that are hard-coded into compiled modules' runtime
+    # library search list.  This works in conjunction with
+    # nvcc_compiler.NVCC_compiler.compile_str which adds this folder during
+    # compilation with -L and also adds -lcuda_ndarray when compiling
+    # modules.
+    nvcc_compiler.add_standard_rpath(cuda_ndarray_loc)
+    compile_cuda_ndarray = not try_import()
+
 
 if compile_cuda_ndarray and cuda_available:
     get_lock()