Implemented infer_shape for subtensor ( which was not complete before )

theano/tensor/basic.py

@@ -2852,7 +2852,8 @@ class Subtensor(Op):
         xshp = shapes[0]
         assert len(xshp) == node.inputs[0].ndim
         outshp = []
-        padded = self.idx_list + [slice(None, None, None)] * (len(xshp) - len(self.idx_list))
+        actual_idx_list = list(get_idx_list(node.inputs, self.idx_list))
+        padded = actual_idx_list + [slice(None, None, None)] * (len(xshp) - len(self.idx_list))
         i = 0
         shape_i = node.env.shape_feature.shape_i
         for idx, xl in zip(padded, xshp):
@@ -2861,11 +2862,23 @@ class Subtensor(Op):
                 # the shape will be xl
                 if (idx.start is None or idx.start == 0)\
                     and (idx.stop is None or idx.stop == sys.maxint)\
-                    and (idx.step is None or idx.step == 1):
+                    and (idx.step is None or abs(idx.step) == 1):
                     outshp.append(xl)
                 else:
-                    # Not implemented yet
-                    outshp.append(shape_i(i)(node.outputs[0]))
+                    cnf = get_canonical_form_slice(idx, xl)
+                    if cnf[0].stop not in [None, sys.maxint]:
+                        length = cnf[0].stop
+                    else:
+                        length = xl
+                    if cnf[0].start not in [None,0]:
+                        length = length - cnf[0].start
+                        length = switch(lt(length,0), 0, length)
+                    if cnf[0].step not in [None, 1]:
+                        # any more elegant way of doing this??
+                        length = cast(
+                            ceil(length / cast(cnf[0].step,'float32')),'int64')
+
+                    outshp.append(length)
                 i += 1
             else:
                 # That dimension is dropped