fix bug in ticket #596 related to tensor.concatenate of 1 element on the gpu.

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -584,6 +584,11 @@ def test_hostfromgpu_shape_i():
 import theano.sandbox.cuda as cuda_ndarray
 from theano.sandbox.cuda.basic_ops import gpu_join, GpuDimShuffle
 
+def test_gpujoin_concatenate_one_element():
+    m = T.fmatrix()
+    c = T.concatenate([m])
+    f = theano.function(inputs=[m], outputs=[c], mode=mode_with_gpu)
+
 def test_gpujoin_twomatrices_joincolumns():
     _a = numpy.asarray([[1,2],[3,4]],dtype='float32')
     _b = numpy.asarray([[5,6,7],[8,9,10]],dtype='float32')

theano/tensor/basic.py

@@ -3173,7 +3173,7 @@ class Join(Op):
                 # broadcastable.
                 bcastable = [False] * len(as_tensor_variable_args[0].type.broadcastable)
 
-        inputs = [as_tensor_variable(axis)] + as_tensor_variable_args
+        inputs = [as_tensor_variable(axis)] + list(as_tensor_variable_args)
         if inputs[0].type not in int_types:
             raise TypeError('Axis could not be cast to an integer type', axis, inputs[0].type, int_types)