Add one more assert and test the 2 fixes with those assert by modifing

theano/scan_module/scan_op.py

@@ -1582,12 +1582,23 @@ class Scan(PureOp):
                 outer_inp_seqs.append(x[::-1])
 
         if hasattr(inputs[0].tag, 'test_value'):
+            # Here we tests that the new scan input sequence all have
+            # the same shape[0]. This is a properties that the scan()
+            # fct add and we want to keep it for all Scan op.  This is
+            # used in T_Scan.test_grad_multiple_outs_taps to test
+            # that.
             for x in self.outer_mitsot_outs(outs):
                 if hasattr(x[::-1][:inputs[0]].tag, 'test_value'):
-                    assert x[::-1][:inputs[0]].tag.test_value.shape[0] == inputs[0].tag.test_value
+                    assert (x[::-1][:inputs[0]].tag.test_value.shape[0] ==
+                            inputs[0].tag.test_value)
             for x in self.outer_sitsot_outs(outs):
                 if hasattr(x[::-1][:-1].tag, 'test_value'):
-                    assert x[::-1][:-1].tag.test_value.shape[0] == inputs[0].tag.test_value
+                    assert (x[::-1][:-1].tag.test_value.shape[0] ==
+                            inputs[0].tag.test_value)
+            for x in self.outer_nitsot_outs(outs):
+                if hasattr(x[::-1].tag, 'test_value'):
+                    assert (x[::-1].tag.test_value.shape[0] ==
+                            inputs[0].tag.test_value)
         outer_inp_seqs += [x[::-1][:inputs[0]]
                            for x in self.outer_mitsot_outs(outs)]
         outer_inp_seqs += [x[::-1][:-1] for x in self.outer_sitsot_outs(outs)]

theano/scan_module/tests/test_scan.py

@@ -1545,6 +1545,12 @@ class T_Scan(unittest.TestCase):
         x0 = theano.tensor.vector('x0')
         y0 = theano.tensor.vector('y0')
 
+        W_in1.tag.test_value = vW_in1
+        u1.tag.test_value = v_u1
+        u2.tag.test_value = v_u2
+        x0.tag.test_value = v_x0
+        y0.tag.test_value = v_y0
+
         def f_rnn_cmpl(u1_t,
                        u2_tm1,
                        u2_t,
@@ -1553,33 +1559,46 @@ class T_Scan(unittest.TestCase):
                        y_tm1,
                        y_tm3,
                        W_in1):
-            return [theano.dot(u1_t, W_in1) + \
-                      (u2_t + u2_tm1 * u2_tp1) * W_in2 + \
-                      theano.dot(x_tm1, W),
+            return [theano.dot(u1_t, W_in1) +
+                    (u2_t + u2_tm1 * u2_tp1) * W_in2 +
+                    theano.dot(x_tm1, W),
                     (y_tm1 + y_tm3) * theano.dot(x_tm1, W_out),
                     theano.dot(u1_t, W_in1)]
-        cost, updates = scan_project_sum(
-            f_rnn_cmpl,
-            [u1, dict(input=u2, taps=[-1, 0, 1])],
-            [x0, dict(initial=y0, taps=[-1, -3]), None],
-            W_in1,
-            n_steps=None,
-            truncate_gradient=-1,
-            go_backwards=False)
-        vparams = [v_u1, v_u2, v_x0, v_y0, vW_in1]
-        params = [u1, u2, x0, y0, W_in1]
-        gparams = theano.tensor.grad(cost, params)
-        grad_fn = theano.function([u1, u2, x0, y0, W_in1],
-                                  gparams,
-                                  updates=updates,
-                                  no_default_updates=True,
-                                  allow_input_downcast=True)
 
-        cost_fn = theano.function([u1, u2, x0, y0, W_in1],
-                                  cost,
-                                  updates=updates,
-                                  no_default_updates=True,
-                                  allow_input_downcast=True)
+        # We change the compute_test_value[_opt] flag to run the
+        # assert in Scan.grad() of the new scan input sequence related
+        # to outer_mitsot_outs, outer_sitsot_outs and
+        # outer_nitsot_outs. This allow to test an old Scan bug.
+        old1 = theano.config.compute_test_value
+        old2 = theano.config.compute_test_value_opt
+        theano.config.compute_test_value = 'raise'
+        theano.config.compute_test_value_opt = 'raise'
+        try:
+            cost, updates = scan_project_sum(
+                f_rnn_cmpl,
+                [u1, dict(input=u2, taps=[-1, 0, 1])],
+                [x0, dict(initial=y0, taps=[-1, -3]), None],
+                W_in1,
+                n_steps=None,
+                truncate_gradient=-1,
+                go_backwards=False)
+            vparams = [v_u1, v_u2, v_x0, v_y0, vW_in1]
+            params = [u1, u2, x0, y0, W_in1]
+            gparams = theano.tensor.grad(cost, params)
+            grad_fn = theano.function([u1, u2, x0, y0, W_in1],
+                                      gparams,
+                                      updates=updates,
+                                      no_default_updates=True,
+                                      allow_input_downcast=True)
+
+            cost_fn = theano.function([u1, u2, x0, y0, W_in1],
+                                      cost,
+                                      updates=updates,
+                                      no_default_updates=True,
+                                      allow_input_downcast=True)
+        finally:
+            theano.config.compute_test_value = old1
+            theano.config.compute_test_value_opt = old2
 
         num_grad = multiple_outputs_numeric_grad(cost_fn,
                                                  [v_u1,