Merge pull request #4129 from nouiz/cleanup

theano/gof/fg.py

@@ -172,8 +172,6 @@ class FunctionGraph(utils.object2):
         for i, output in enumerate(outputs):
             output.clients.append(('output', i))
 
-        self.node_locks = {}
-        self.variable_locks = {}
         self.profile = None
         self.update_mapping = update_mapping
 
@@ -232,6 +230,8 @@ class FunctionGraph(utils.object2):
         them back to what they were originally.
 
         """
+        for f in self._features:
+            self.remove_feature(f)
         for apply_node in self.apply_nodes:
             del apply_node.fgraph
             del apply_node.deps
@@ -242,6 +242,8 @@ class FunctionGraph(utils.object2):
         self.variables = set()
         self.inputs = None
         self.outputs = None
+        self.profile = None
+        self.update_mapping = None
 
     # clients #
     def clients(self, r):

theano/scan_module/scan_op.py

@@ -1603,24 +1603,31 @@ class Scan(PureOp):
         # of iterations.
         # sequences
         seqs_shape = [x[1:] for x in input_shapes[1:1 + self.n_seqs]]
-        # inner_seqs = self.inputs[:self.n_seqs]
-        # outer_seqs = node.inputs[1:1 + self.n_seqs]
-        # for in_s, out_s in izip(inner_seqs, outer_seqs):
-        #     out_equivalent[in_s] = out_s[0]
-
-        # mit_mot, mit_sot, sit_sot
-        # outer_inp_idx = 1 + self.n_seqs
-        # inner_inp_idx = self.n_seqs
+        # We disable extra infer_shape for now. See gh-3765.
+        extra_infer_shape = False
+
+        if extra_infer_shape:
+            inner_seqs = self.inputs[:self.n_seqs]
+            outer_seqs = node.inputs[1:1 + self.n_seqs]
+            for in_s, out_s in izip(inner_seqs, outer_seqs):
+                out_equivalent[in_s] = out_s[0]
+
+            # mit_mot, mit_sot, sit_sot
+            outer_inp_idx = 1 + self.n_seqs
+            inner_inp_idx = self.n_seqs
+        else:
+            outer_inp_idx = 0
         n_outs = self.n_mit_mot + self.n_mit_sot + self.n_sit_sot
         outs_shape = []
         for idx in xrange(n_outs):
-            # mintap = abs(min(self.tap_array[idx]))
+            mintap = abs(min(self.tap_array[idx]))
             for k in self.tap_array[idx]:
                 outs_shape += [input_shapes[idx + self.n_seqs + 1][1:]]
-                # corresponding_tap = node.inputs[outer_inp_idx][mintap + k]
-                # out_equivalent[self.inputs[inner_inp_idx]] = corresponding_tap
-                # inner_inp_idx += 1
-            # outer_inp_idx += 1
+                if extra_infer_shape:
+                    corresponding_tap = node.inputs[outer_inp_idx][mintap + k]
+                    out_equivalent[self.inputs[inner_inp_idx]] = corresponding_tap
+                    inner_inp_idx += 1
+            outer_inp_idx += 1
 
         # shared_outs
         offset = 1 + self.n_seqs + n_outs