Completed TODO in as_tensor_variable which said to strip off leading broadcastable dimensions.

theano/tensor/basic.py

@@ -164,10 +164,10 @@ def as_tensor_variable(x, name=None, ndim=None):
             return x
         else:
             if (x.type.ndim > ndim):
-                # TODO: strip off leading broadcastable dimensions
-                raise ValueError(
-                    'TensorType could not be cast to have %i dimensions' %
-                    ndim, x.type)
+                # strip off leading broadcastable dimensions
+                first_non_broadcastable = [idx for idx in range(x.ndim)
+                                           if x.broadcastable[idx] == False][0]
+                return x.dimshuffle(range(x.ndim)[first_non_broadcastable:])
             elif (x.type.ndim < ndim):
                 return shape_padleft(x, n_ones=(ndim - x.type.ndim))
             else:

theano/tensor/tests/test_basic.py

@@ -1919,6 +1919,12 @@ Allocb4GradTester = makeBroadcastTester(
 )
 
 
+def test_as_tensor_variable():
+    x = tensor.TensorType(config.floatX, (True, False))()
+    x = as_tensor_variable(x, ndim=1)
+    assert(x.ndim == 1)
+
+
 class TestAlloc(unittest.TestCase):
     dtype = config.floatX
     mode = mode_opt