Opts had errors in their return value and implementation of tests

theano/tensor/opt_uncanonicalize.py

@@ -114,10 +114,10 @@ def local_alloc_dimshuffle(node):
             # check if it only adds dimension to the left
             new_order = input_.owner.op.new_order
             expected_new_order = ('x',) * (input_.ndim - input_.owner.inputs[0].ndim) + \
-                    tuple(range(input_.owner.inputs.ndim))
+                    tuple(range(input_.owner.inputs[0].ndim))
             if new_order != expected_new_order:
                 return False
-            return input_.owner.inputs
+            return [T.alloc(input_.owner.inputs[0], *node.inputs[1:])]
     return False
 
 
@@ -128,10 +128,10 @@ def local_reshape_dimshuffle(node):
     If a dimshuffle is inside a reshape and does not change the order
     of dimensions, remove it.
     """
-    if node.op == T.reshape:
+    if isinstance(node.op, T.Reshape):
         input_ = node.inputs[0]
         if input_.owner and isinstance(input_.owner.op, DimShuffle):
-            new_order = input_owner.op.new_order
+            new_order = input_.owner.op.new_order
             offset = 0
             for i, dim in enumerate(new_order):
                 if dim == 'x':
@@ -139,5 +139,5 @@ def local_reshape_dimshuffle(node):
                     continue
                 elif i != dim + offset:
                     return False
-            return input_.owner.inputs
+            return [T.reshape(input_.owner.inputs[0], tuple(node.inputs[1].owner.inputs))]
     return False

theano/tensor/tests/test_opt_uncanonicalize.py

@@ -6,9 +6,15 @@ import numpy
 import theano
 from theano import function, config
 from theano import scalar
+from theano.gof import FunctionGraph
+from theano.tensor.opt import out2in
+from theano.tensor.opt_uncanonicalize import (
+    local_alloc_dimshuffle,
+    local_reshape_dimshuffle
+    )
 import theano.tensor as tensor
 #from theano.tensor import matrix,max_and_argmax,MaaxAndArgmax,neg
-from theano.tensor.elemwise import CAReduce, Elemwise
+from theano.tensor.elemwise import CAReduce, Elemwise, DimShuffle
 from theano.tests import unittest_tools as utt
 
 
@@ -106,3 +112,36 @@ class T_min_max(unittest.TestCase):
             assert len(topo) == 1
             assert isinstance(topo[0].op, CAReduce)  # max
             f(data)
+
+
+def test_local_alloc_dimshuffle():
+
+    alloc_dimshuffle = out2in(local_alloc_dimshuffle)
+
+    x = T.vector('x')
+    m = T.iscalar('m')
+
+    out = x.dimshuffle('x', 0)
+    out = T.alloc(x, m, 1, x.shape[0])
+
+    g = FunctionGraph(out)
+    alloc_dimshuffle(g)
+
+    topo = g.toposort()
+    assert any([not isinstance(x, DimShuffle) for x in topo])
+
+
+def test_local_reshape_dimshuffle():
+
+    reshape_dimshuffle = out2in(local_reshape_dimshuffle)
+
+    x = T.matrix('x')
+
+    y = x.dimshuffle('x', 0, 'x', 1)
+    out = T.reshape(y, (1, x.shape[0] * x.shape[1], 1))
+
+    g = FunctionGraph(out)
+    reshape_dimshuffle(g)
+
+    topo = g.toposort()
+    assert any([not isinstance(x, DimShuffle) for x in topo])