applying changes to remove Flatten Op

theano/sandbox/cuda/basic_ops.py

@@ -3322,23 +3322,23 @@ class GpuIncSubtensor(tensor.IncSubtensor, GpuOp):
         return ()
 
 
-#class GpuFlatten(gof.HideC, tensor.Reshape, GpuOp):
-#    """
-#    Implement Flatten on the gpu.
-#
-#    """
-#
-#    def make_node(self, x):
-#        warnings.warn(
-#            "GpuFlatten class is deprecated, "
-#            "please use gpu_flatten method instead.",
-#            DeprecationWarning,
-#            stacklevel=4)
-#        assert isinstance(x.type, CudaNdarrayType)
-#        rval = tensor.Reshape.make_node(self, x, [tensor.prod(x.shape)])
-#        host_out_broadcastable = rval.outputs[0].type.broadcastable
-#        out_type = CudaNdarrayType(broadcastable=host_out_broadcastable)
-#        return Apply(self, [x], [out_type()])
+class GpuFlatten(gof.HideC, tensor.Reshape, GpuOp):
+    """
+    Implement Flatten on the gpu.
+
+    """
+
+    def make_node(self, x):
+        warnings.warn(
+            "GpuFlatten class is deprecated, "
+            "please use gpu_flatten method instead.",
+            DeprecationWarning,
+            stacklevel=4)
+        assert isinstance(x.type, CudaNdarrayType)
+        rval = tensor.Reshape.make_node(self, x, [tensor.prod(x.shape)])
+        host_out_broadcastable = rval.outputs[0].type.broadcastable
+        out_type = CudaNdarrayType(broadcastable=host_out_broadcastable)
+        return Apply(self, [x], [out_type()])
 
 
 

theano/tensor/opt.py

@@ -3877,24 +3877,24 @@ def local_useless_split(node):
 ################
 # Flatten Opts #
 ################
-#@register_canonicalize
-#@register_stabilize
-#@gof.local_optimizer([T.Flatten])
-#def local_flatten_lift(node):
-#    ""
-#    Flatten(UnaryElemwise(x)) -> UnaryElemwise(Flatten(x))
-#
-#    This optimization is needed by optimization
-#    nnet/sigm.py:log1msigm_to_softplus to get applied when there is a flatten.
-#
-#    ""
-#    if (isinstance(node.op, T.Flatten) and
-#            node.inputs[0].owner and
-#            isinstance(node.inputs[0].owner.op, T.Elemwise) and
-#            len(node.inputs[0].owner.inputs) == 1):
-#        f = node.op(node.inputs[0].owner.inputs[0])
-#        e = node.inputs[0].owner.op(f)
-#        return [e]
+@register_canonicalize
+@register_stabilize
+@gof.local_optimizer([T.Flatten])
+def local_flatten_lift(node):
+    ""
+    Flatten(UnaryElemwise(x)) -> UnaryElemwise(Flatten(x))
+
+    This optimization is needed by optimization
+    nnet/sigm.py:log1msigm_to_softplus to get applied when there is a flatten.
+
+    ""
+    if (isinstance(node.op, T.Flatten) and
+            node.inputs[0].owner and
+            isinstance(node.inputs[0].owner.op, T.Elemwise) and
+            len(node.inputs[0].owner.inputs) == 1):
+        f = node.op(node.inputs[0].owner.inputs[0])
+        e = node.inputs[0].owner.op(f)
+        return [e]
 
 ##################
 # Reshape opts   #