Move Flatten to the new GPU back-end by reusing reshape.

theano/sandbox/gpuarray/opt.py

@@ -62,7 +62,10 @@ def op_lifter(OP):
                     new_op = maker(node)
                     # This is needed as sometimes new_op inherit from OP.
                     if new_op and new_op != node.op:
-                        return [host_from_gpu(new_op(*node.inputs))]
+                        if isinstance(new_op, theano.Op):
+                            return [host_from_gpu(new_op(*node.inputs))]
+                        else:  # suppose it is a variable on the GPU
+                            return [host_from_gpu(new_op)]
             return False
         local_opt.__name__ = maker.__name__
         return local_optimizer([OP])(local_opt)
@@ -128,12 +131,24 @@ def local_gpureshape(node):
     if type(node.op) is not tensor.Reshape:
         return None
     if name:
-        name = 'Gpu'+name
+        name = 'Gpu' + name
     res = GpuReshape(op.ndim, op.name)
-    o = res(*node.inputs)
     return res
 
 
+@register_opt()
+@op_lifter(tensor.Flatten)
+def local_gpuflatten(node):
+    op = node.op
+    if type(node.op) is not tensor.Flatten:
+        return None
+    if op.outdim != 1:
+        return None
+    res = GpuReshape(op.outdim, None)
+    o = res(node.inputs[0], theano.tensor.constant([-1]))
+    return o
+
+
 @register_opt()
 @op_lifter(tensor.Elemwise)
 def local_gpu_elemwise(node):

theano/sandbox/gpuarray/tests/test_opt.py

+import numpy
+
+import theano
+from theano.tests import unittest_tools as utt
+from theano.sandbox.gpuarray.basic_ops import GpuReshape
+import theano.sandbox.gpuarray
+
+if theano.sandbox.gpuarray.pygpu is None:
+    raise SkipTest("pygpu not installed")
+
+import theano.sandbox.cuda as cuda_ndarray
+if cuda_ndarray.cuda_available and not theano.sandbox.gpuarray.pygpu_activated:
+    if not cuda_ndarray.use.device_number:
+        cuda_ndarray.use('gpu')
+    theano.sandbox.gpuarray.init_dev('cuda')
+
+if not theano.sandbox.gpuarray.pygpu_activated:
+    raise SkipTest("pygpu disabled")
+
+if theano.config.mode == 'FAST_COMPILE':
+    mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpuarray').excluding('gpu')
+    mode_without_gpu = theano.compile.mode.get_mode('FAST_RUN').excluding('gpuarray')
+else:
+    mode_with_gpu = theano.compile.mode.get_default_mode().including('gpuarray').excluding('gpu')
+    mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpuarray')
+
+
+def test_flatten():
+    m = theano.tensor.fmatrix()
+    f = theano.function([m], m.flatten(), mode=mode_with_gpu)
+    val = numpy.random.rand(10,11).astype("float32")
+    res = f(val)
+    utt.assert_allclose(res, val.flatten())
+    assert res.shape == val.flatten().shape
+    assert GpuReshape in [type(node.op)
+                          for node in f.maker.fgraph.toposort()]
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