Fix DebugMode to accept numpy.memmap.

doc/library/tensor/basic.txt

@@ -300,7 +300,8 @@ TensorType and TensorVariable
 .. class:: TensorType(Type)
 
     The Type class used to mark Variables that stand for `numpy.ndarray`
-    values.  Recalling to the tutorial, the purple box in
+    values (`numpy.memmap`, which is a subclass of `numpy.ndarray`, is also allowed).
+    Recalling to the tutorial, the purple box in
     :ref:`the tutorial's graph-structure figure <tutorial-graphfigure>` is an instance of this class.
 
     .. attribute:: broadcastable

theano/compile/debugmode.py

@@ -870,17 +870,18 @@ def _lessbroken_deepcopy(a):
     """
     :param a: any object
 
-    Returns a copy of `a` that shares no internal storage with the original.  A deep copy.
-    This function handles numpy arrays specially to avoid some bug I had one time... (possibly
-    about copying 0-d arrays?)
+    Returns a copy of `a` that shares no internal storage with the original.
+    A deep copy.
+    This function handles numpy arrays specially, because copy.deepcopy()
+    called on a 0-d array will return a numpy scalar, not an array.
     """
-    # this exists because numpy copies are broken
-    if type(a) is numpy.ndarray:
-        rval = numpy.array(a, copy=True, dtype=a.dtype)
+    # this exists because copy.deepcopy on numpy arrays is broken
+    if type(a) in (numpy.ndarray, numpy.memmap):
+        rval = a.copy()
     else:
         rval = copy.deepcopy(a)
 
-    assert type(rval) == type(a)
+    assert type(rval) == type(a), (type(rval), type(a))
     if isinstance(rval, numpy.ndarray):
         assert rval.dtype == a.dtype
     return rval
@@ -1992,7 +1993,7 @@ class _Linker(gof.link.LocalLinker):
                     if r.owner is None:
                         assert r in fgraph.inputs
                         #HACK TO LOOK LIKE A REAL DESTRUCTIVE ACTION TOOK PLACE
-                        if type(dr_vals[r][0]) is numpy.ndarray \
+                        if type(dr_vals[r][0]) in (numpy.ndarray, numpy.memmap) \
                                 and dr_vals[r][0].dtype == storage_map[r][0].dtype \
                                 and dr_vals[r][0].shape == storage_map[r][0].shape:
                             if len(dr_vals[r][0].shape):

theano/tensor/elemwise.py

@@ -218,7 +218,7 @@ class DimShuffle(Op):
         storage, = out
         # drop
         res = input
-        if type(res) != numpy.ndarray:
+        if type(res) != numpy.ndarray and type(res) != numpy.memmap:
             raise TypeError(res)
         shape = list(res.shape)
         for drop in reversed(self.drop):