Add config flag experimental.unpickle_gpu_on_cpu.

theano/configdefaults.py

@@ -266,6 +266,19 @@ AddConfigVar('experimental.mrg',
              "Another random number generator that work on the gpu",
              BoolParam(False))
 
+AddConfigVar('experimental.unpickle_gpu_on_cpu',
+             "Allow unpickling of pickled CudaNdarrays as numpy.ndarrays."
+             "This is useful, if you want to open a CudaNdarray without "
+             "having cuda installed."
+             "If you have cuda installed, this will force unpickling to"
+             "be done on the cpu to numpy.ndarray."
+             "Please be aware that this may get you access to the data,"
+             "however, trying to unpicke gpu functions will not succeed."
+             "This flag is experimental and may be removed any time, when"
+             "gpu<>cpu transparency is solved.",
+             BoolParam(default=False),
+             in_c_key=False)
+
 AddConfigVar('numpy.seterr_all',
              ("Sets numpy's behaviour for floating-point errors, ",
               "see numpy.seterr. "

theano/sandbox/cuda/tests/test_type.py

 import cPickle
+from nose.tools import assert_raises
 import numpy
 import os.path
+from theano import config
 from theano.sandbox.cuda import cuda_available
 
-
 if cuda_available:
     from theano.sandbox.cuda import CudaNdarray
 
-def test_unpickle_cudandarray_as_numpy_ndarray():
-    # testfile created on cuda enabled machine using
-    # >>> with open('CudaNdarray.pkl', 'wb') as fp:
-    # >>> cPickle.dump(theano.sandbox.cuda.CudaNdarray(np.array([-42.0], dtype=np.float32)), fp)
+# testfile created on cuda enabled machine using
+# >>> with open('CudaNdarray.pkl', 'wb') as fp:
+# >>> cPickle.dump(theano.sandbox.cuda.CudaNdarray(np.array([-42.0], dtype=np.float32)), fp)
+
+def test_unpickle_flag_is_false_by_default():
+    assert not config.experimental.unpickle_gpu_on_cpu
+
+def test_unpickle_cudandarray_as_numpy_ndarray_flag0():
+    oldflag = config.experimental.unpickle_gpu_on_cpu
+    config.experimental.unpickle_gpu_on_cpu = False
 
     testfile_dir = os.path.dirname(os.path.realpath(__file__))
     with open(os.path.join(testfile_dir, 'CudaNdarray.pkl')) as fp:
-        mat = cPickle.load(fp)
-
         if cuda_available:
-            assert isinstance(mat, CudaNdarray)
+            mat = cPickle.load(fp)
         else:
-            assert isinstance(mat, numpy.ndarray)
+            assert_raises(ImportError, cPickle.load, fp)
+
+    if cuda_available:
+        assert isinstance(mat, CudaNdarray)
+        assert mat[0] == -42.0
+
+    config.experimental.unpickle_gpu_on_cpu = oldflag
+
+
+def test_unpickle_cudandarray_as_numpy_ndarray_flag1():
+    oldflag = config.experimental.unpickle_gpu_on_cpu
+    config.experimental.unpickle_gpu_on_cpu = True
+
+    testfile_dir = os.path.dirname(os.path.realpath(__file__))
+
+    with open(os.path.join(testfile_dir, 'CudaNdarray.pkl')) as fp:
+        mat = cPickle.load(fp)
+
+    assert isinstance(mat, numpy.ndarray)
+    assert mat[0] == -42.0
 
-        assert mat[0] == -42.0
\ No newline at end of file
+    config.experimental.unpickle_gpu_on_cpu = oldflag

theano/sandbox/cuda/type.py

@@ -7,6 +7,7 @@ import warnings
 import numpy
 
 import theano
+from theano import config
 from theano import Type, Variable
 from theano import tensor, config
 from theano import scalar as scal
@@ -488,12 +489,15 @@ theano.compile.register_deep_copy_op_c_code(
 # equal the pickled version, and the cmodule cache is not happy with
 # the situation.
 def CudaNdarray_unpickler(npa):
-    if cuda:
-        return cuda.CudaNdarray(npa)
-    else:
+
+    if config.experimental.unpickle_gpu_on_cpu:
         # directly return numpy array
-        warnings.warn("CUDA not found. Unpickling CudaNdarray as numpy.ndarray")
+        warnings.warn("config.experimental.unpickle_gpu_on_cpu is set to True. Unpickling CudaNdarray as numpy.ndarray")
         return npa
+    elif cuda:
+        return cuda.CudaNdarray(npa)
+    else:
+        raise ImportError("Cuda not found. Cannot unpickle CudaNdarray")
 
 copy_reg.constructor(CudaNdarray_unpickler)