Merge pull request #1341 from pascanur/recent_scan_bugs

theano/scan_module/scan_opt.py

@@ -1159,7 +1159,7 @@ class ScanMerge(gof.Optimizer):
         Questionable, we should also consider profile ?
         """
         rep = set_nodes[0]
-        if not rep.op.as_while and node.op.as_while:
+        if rep.op.as_while != node.op.as_while:
             return False
 
         nsteps = node.inputs[0]

theano/scan_module/scan_utils.py

@@ -48,7 +48,10 @@ def safe_new(x, tag='', dtype=None):
         nw_name = None
     if isinstance(x, theano.Constant):
         if dtype and x.dtype != dtype:
-            return x.clone().astype(dtype)
+            casted_x = x.astype(dtype)
+            nwx = x.__class__(casted_x.type, x.data, x.name)
+            nwx.tag = copy(x.tag)
+            return nwx
         else:
             return x.clone()
     # Note, as_tensor_variable will convert the Scalar into a
@@ -70,6 +73,8 @@ def safe_new(x, tag='', dtype=None):
             # ndarrays
             pass
     nw_x = x.type()
+    if dtype and nw_x.dtype != dtype:
+        nw_x = nw_x.astype(dtype).type()
     nw_x.name = nw_name
     # Preserve test values so that the 'compute_test_value' option can be used.
     # The test value is deep-copied to ensure there can be no interactions
@@ -82,9 +87,6 @@ def safe_new(x, tag='', dtype=None):
             # This means `x` has no test value.
             pass
 
-    if dtype and nw_x.dtype != dtype:
-        nw_x = nw_x.astype(dtype)
-
     return nw_x
 
 

theano/scan_module/tests/test_scan.py

@@ -3452,6 +3452,39 @@ class T_Scan(unittest.TestCase):
         assert numpy.allclose(test(x, tensor.sum((x+1)**2), mention_y=True),
                               1.21000003815)
 
+    def test_grad_find_input(self):
+        w = theano.shared(numpy.array(0, dtype='float32'), name='w')
+        init = tensor.fscalar('init')
+
+        out, _ = theano.scan(
+                fn=lambda prev: w,
+                outputs_info=init,
+                n_steps=2,
+        )
+        tensor.grad(out[-1], w)
+
+    def test_scan_merge_nodes(self):
+        inps = tensor.vector()
+        state = tensor.scalar()
+        y1, _ = theano.scan(lambda x,y: x*y,
+                            sequences = inps,
+                            outputs_info = state,
+                            n_steps = 5)
+
+        y2, _ = theano.scan(lambda x,y : (x+y, theano.scan_module.until(x>0)),
+                            sequences = inps,
+                            outputs_info = state,
+                            n_steps = 5)
+        scan_node1 = y1.owner.inputs[0].owner
+        assert isinstance(scan_node1.op, theano.scan_module.scan_op.Scan)
+        scan_node2 = y2.owner.inputs[0].owner
+        assert isinstance(scan_node2.op, theano.scan_module.scan_op.Scan)
+        opt_obj = theano.scan_module.scan_opt.ScanMerge()
+        # Test the method belongs_to of this class. Specifically see if it
+        # detects the two scan_nodes as not being similar
+        assert not opt_obj.belongs_to_set(scan_node1, [scan_node2])
+        assert not opt_obj.belongs_to_set(scan_node2, [scan_node1])
+
 
 def test_speed():
     #