added disabled-by-default experimental advanced indexing code

theano/tensor/basic.py

@@ -4,7 +4,7 @@ __docformat__ = "restructuredtext en"
 
 import __builtin__
 import sys # for sys.maxint
-from theano.configparser import config
+from theano.configparser import config, AddConfigVar, BoolParam
 import traceback #for overriding Op.__call__
 if sys.version_info >= (2,5):
   import functools
@@ -943,7 +943,13 @@ class _tensor_py_operators:
                 break
 
         if advanced:
-            return AdvancedSubtensor(args)(self, *args)
+            if config.experimental.advanced_indexing:
+                if len(args) == 1:
+                    return AdvancedSubtensor1()(self, *args)
+                else:
+                    return AdvancedSubtensor(args)(self, *args)
+            else:
+                return AdvancedSubtensor(args)(self, *args)
         else:
             return Subtensor(args)(self, *Subtensor.collapse(args, lambda entry: isinstance(entry, Variable)))
 
@@ -3136,6 +3142,37 @@ def inverse_permutation(perm):
 # Should reproduce numpy's behaviour:
 # http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#advanced-indexing
 
+AddConfigVar('experimental.advanced_indexing',
+        "enable not-well-tested advanced indexing functionality",
+        BoolParam(False))
+
+
+class AdvancedSubtensor1(Op):
+    """Implement x[ilist] where ilist is a vector of integers."""
+
+    def __hash__(self):
+        return hash(type(self))
+    def __eq__(self, other):
+        type(self) == type(other)
+
+    def make_node(self, x, ilist):
+        x_ = as_tensor_variable(x)
+        ilist_ = as_tensor_variable(ilist)
+        if ilist_.type.dtype[:3] not in ('int', 'uin'):
+            raise TypeError('index must be integers')
+        if ilist_.type.broadcastable != (False,):
+            raise TypeError('index must be vector')
+        if x_.type.ndim == 0:
+            raise TypeError('cannot index into a scalar')
+        if x_.type.broadcastable[0]:
+            # the caller should have made a copy of x len(ilist) times
+            raise TypeError('cannot index into a broadcastable dimension')
+
+        return gof.Apply(self, [x_, ilist_], [x_.type()])
+
+    def perform(self, node, (x,i), (out,)):
+        out[0] = x[i]
+
 class AdvancedSubtensor(Op):
     """Return a subtensor copy, using advanced indexing.
     """