!12663 [auto-monad] Fix backend control flow bug found by igamma test

From: @hwhewei
Reviewed-by: @zh_qh,@ginfung
Signed-off-by: @zh_qh

mindspore/ccsrc/backend/session/ascend_auto_monad.cc

@@ -305,6 +305,9 @@ class AscendAutoMonadConverter {
       }
       if (return_label_ != kNoLabel) {
         (void)LabelGoto(return_label_);
+      } else {
+        // Clear end goto if return label not set.
+        kernel_graph_->set_end_goto(nullptr);
       }
     }
   }

mindspore/ccsrc/backend/session/kernel_graph.cc

@@ -274,6 +274,25 @@ std::vector<CNodePtr> KernelGraph::SortStartLabelAndEndGoto() {
       continue;
     }
 
+    //
+    // Re-order:
+    //   u = LabelGoto(...)
+    //   x = Mul(...)
+    //   LabelSet(u)
+    // To:
+    //   u = LabelGoto(...)
+    //   LabelSet(u)
+    //   x = Mul(...)
+    // This prevent Mul be skipped.
+    //
+    if (IsPrimitiveCNode(node, prim::kPrimLabelSet) && (re_order.back() != node->input(1))) {
+      auto iter = std::find(re_order.rbegin() + 1, re_order.rend(), node->input(1));
+      if (iter != re_order.rend()) {
+        re_order.insert(iter.base(), node);
+        continue;
+      }
+    }
+
     re_order.push_back(node);
   }
   if (end_goto_ != nullptr) {

tests/st/auto_monad/test_effect_ops.py

@@ -15,6 +15,7 @@
 import os
 import tempfile
 import pytest
+import scipy
 import numpy as np
 import mindspore.nn as nn
 import mindspore.ops.operations as P
@@ -395,3 +396,24 @@ def test_summary():
                 event = summary_writer.read_event()
                 tags = set(value.tag for value in event.summary.value)
                 assert tags == {'tensor', 'histogram', 'scalar', 'image'}
+
+
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+def test_igamma():
+    class IGammaTest(nn.Cell):
+        def __init__(self):
+            super().__init__()
+            self.igamma = nn.IGamma()
+
+        def construct(self, x, a):
+            return self.igamma(a=a, x=x)
+
+    x = 4.22
+    a = 2.29
+    net = IGammaTest()
+    out = net(Tensor(x, mstype.float32), Tensor(a, mstype.float32))
+    expect = scipy.special.gammainc(a, x)
+    assert np.allclose(out.asnumpy(), expect, rtol=1e-5, atol=1e-5, equal_nan=True)