diff --git a/mindspore/ccsrc/pre_activate/ascend/ascend_backend_optimization.cc b/mindspore/ccsrc/pre_activate/ascend/ascend_backend_optimization.cc
index bdefc9bf7c..4a6b5b1e4a 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ascend_backend_optimization.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/ascend_backend_optimization.cc
@@ -104,6 +104,9 @@ void AddAscendBackendOptionalIRFusion(PassManager *ir_fusion_pm) {
   ir_fusion_pm->AddPass(std::make_shared<LambNextMVWithDecayRuleCond2>());
   ir_fusion_pm->AddPass(std::make_shared<LambNextMVWithDecayRuleCond3>());
   ir_fusion_pm->AddPass(std::make_shared<LambNextMVWithDecayRuleCond4>());
+  ir_fusion_pm->AddPass(std::make_shared<LambNextMVRuleCond1>());
+  ir_fusion_pm->AddPass(std::make_shared<LambNextMVRuleCond2>());
+  ir_fusion_pm->AddPass(std::make_shared<LambNextMVRuleCond3>());
   ir_fusion_pm->AddPass(std::make_shared<LambNextMVRuleCond4>());
   ir_fusion_pm->AddPass(std::make_shared<LambNextRightRule>());
   ir_fusion_pm->AddPass(std::make_shared<LambUpdateWithLrV2>());
diff --git a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.cc b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.cc
index 7265f1b60d..5f0b869644 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.cc
+++ b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.cc
@@ -116,9 +116,116 @@ const AnfNodePtr LambNextMVRule::Process(const FuncGraphPtr &func_graph, const A
   return CreateLambNextMVNode(func_graph, old_pattern_outputs, equiv);
 }
 
+const BaseRef LambNextMVRuleCond1::DefinePattern() const {
+  const auto prim_rsqrt = std::make_shared<Primitive>(kRsqrtOpName);
+
+  auto mul0 = VectorRef({prim::kPrimMul, mul0_x_, input4_});
+  auto mul1 = VectorRef({prim::kPrimMul, mul1_sub_, input3_});
+  auto mul2 = VectorRef({prim::kPrimMul, mul2_x_, input1_});
+  auto mul3 = VectorRef({prim::kPrimMul, mul3_sub1_, input0_});
+  auto mul4 = VectorRef({prim::kPrimMul, mul4_x_, input6_});
+  auto add0 = VectorRef({add0_var_, mul0, mul1});
+  auto add1 = VectorRef({add1_var_, mul2, mul3});
+
+  auto real_div0 = VectorRef({real_div0_var_, add0, input5_});
+  auto real_div1 = VectorRef({real_div1_var_, add1, input2_});
+
+  auto add2 = VectorRef({prim::kPrimTensorAdd, add2_y_, real_div1});
+  auto sqrt0 = VectorRef({prim_rsqrt, add2});
+  auto real_div2 = VectorRef({real_div2_var_, sqrt0, real_div0});
+
+  return VectorRef({prim::kPrimTensorAdd, mul4, real_div2});
+}
+
+BaseRef LambNextMVRuleCond1::DefineAnotherPattern() const {
+  const auto prim_sqrt = std::make_shared<Primitive>(kSqrtOpName);
+  const auto prim_real_div = std::make_shared<Primitive>(kRealDivOpName);
+  VarPtr Xs = std::make_shared<SeqVar>();
+  VarPtr Ys = std::make_shared<SeqVar>();
+  // Two patterns share: real_div0, real_div1, add2_y_
+  VectorRef real_div0 = VectorRef({real_div0_var_, Xs});
+  VectorRef real_div1 = VectorRef({real_div1_var_, Ys});
+
+  VectorRef sqrt1 = VectorRef({prim_sqrt, real_div1});
+  VectorRef add4 = VectorRef({prim::kPrimTensorAdd, add2_y_, sqrt1});
+  VectorRef real_div4 = VectorRef({prim_real_div, real_div0, add4});
+  return real_div4;
+}
+
+const BaseRef LambNextMVRuleCond2::DefinePattern() const {
+  const auto prim_rsqrt = std::make_shared<Primitive>(kRsqrtOpName);
+
+  auto mul0 = VectorRef({prim::kPrimMul, input4_, mul0_x_});
+  auto mul1 = VectorRef({prim::kPrimMul, input3_, mul1_sub_});
+  auto mul2 = VectorRef({prim::kPrimMul, input1_, mul2_x_});
+  auto mul3 = VectorRef({prim::kPrimMul, mul3_sub1_, input0_});
+  auto mul4 = VectorRef({prim::kPrimMul, input6_, mul4_x_});
+  auto add0 = VectorRef({add0_var_, mul0, mul1});
+  auto add1 = VectorRef({add1_var_, mul2, mul3});
+
+  auto real_div0 = VectorRef({real_div0_var_, add0, input5_});
+  auto real_div1 = VectorRef({real_div1_var_, add1, input2_});
+
+  auto add2 = VectorRef({prim::kPrimTensorAdd, add2_y_, real_div1});
+  auto sqrt0 = VectorRef({prim_rsqrt, add2});
+  auto real_div2 = VectorRef({real_div2_var_, sqrt0, real_div0});
+
+  return VectorRef({prim::kPrimTensorAdd, mul4, real_div2});
+}
+
+BaseRef LambNextMVRuleCond2::DefineAnotherPattern() const {
+  const auto prim_sqrt = std::make_shared<Primitive>(kSqrtOpName);
+  const auto prim_real_div = std::make_shared<Primitive>(kRealDivOpName);
+  VarPtr Xs = std::make_shared<SeqVar>();
+  VarPtr Ys = std::make_shared<SeqVar>();
+  // Two patterns share: real_div0, real_div1, add2_y_
+  VectorRef real_div0 = VectorRef({real_div0_var_, Xs});
+  VectorRef real_div1 = VectorRef({real_div1_var_, Ys});
+
+  VectorRef sqrt1 = VectorRef({prim_sqrt, real_div1});
+  VectorRef add4 = VectorRef({prim::kPrimTensorAdd, sqrt1, add2_y_});
+  VectorRef real_div4 = VectorRef({prim_real_div, real_div0, add4});
+  return real_div4;
+}
+
+const BaseRef LambNextMVRuleCond3::DefinePattern() const {
+  const auto prim_rsqrt = std::make_shared<Primitive>(kRsqrtOpName);
+
+  auto mul0 = VectorRef({prim::kPrimMul, input4_, mul0_x_});
+  auto mul1 = VectorRef({prim::kPrimMul, input3_, mul1_sub_});
+  auto mul2 = VectorRef({prim::kPrimMul, input1_, mul2_x_});
+  auto mul3 = VectorRef({prim::kPrimMul, input0_, mul3_sub1_});
+  auto mul4 = VectorRef({prim::kPrimMul, input6_, mul4_x_});
+  auto add0 = VectorRef({add0_var_, mul0, mul1});
+  auto add1 = VectorRef({add1_var_, mul2, mul3});
+
+  auto real_div0 = VectorRef({real_div0_var_, add0, input5_});
+  auto real_div1 = VectorRef({real_div1_var_, add1, input2_});
+
+  auto add2 = VectorRef({prim::kPrimTensorAdd, real_div1, add2_y_});
+  auto sqrt0 = VectorRef({prim_rsqrt, add2});
+  auto real_div2 = VectorRef({real_div2_var_, sqrt0, real_div0});
+
+  return VectorRef({prim::kPrimTensorAdd, mul4, real_div2});
+}
+
+BaseRef LambNextMVRuleCond3::DefineAnotherPattern() const {
+  const auto prim_sqrt = std::make_shared<Primitive>(kSqrtOpName);
+  const auto prim_real_div = std::make_shared<Primitive>(kRealDivOpName);
+  VarPtr Xs = std::make_shared<SeqVar>();
+  VarPtr Ys = std::make_shared<SeqVar>();
+  // Two patterns share: real_div0, real_div1, add2_y_
+  VectorRef real_div0 = VectorRef({real_div0_var_, Xs});
+  VectorRef real_div1 = VectorRef({real_div1_var_, Ys});
+
+  VectorRef sqrt1 = VectorRef({prim_sqrt, real_div1});
+  VectorRef add4 = VectorRef({prim::kPrimTensorAdd, sqrt1, add2_y_});
+  VectorRef real_div4 = VectorRef({prim_real_div, real_div0, add4});
+  return real_div4;
+}
+
 const BaseRef LambNextMVRuleCond4::DefinePattern() const {
   const auto prim_rsqrt = std::make_shared<Primitive>(kRsqrtOpName);
-  MS_EXCEPTION_IF_NULL(prim_rsqrt);
 
   auto mul0 = VectorRef({prim::kPrimMul, mul0_x_, input4_});
   auto mul1 = VectorRef({prim::kPrimMul, mul1_sub_, input3_});
@@ -140,13 +247,9 @@ const BaseRef LambNextMVRuleCond4::DefinePattern() const {
 
 BaseRef LambNextMVRuleCond4::DefineAnotherPattern() const {
   const auto prim_sqrt = std::make_shared<Primitive>(kSqrtOpName);
-  MS_EXCEPTION_IF_NULL(prim_sqrt);
   const auto prim_real_div = std::make_shared<Primitive>(kRealDivOpName);
-  MS_EXCEPTION_IF_NULL(prim_real_div);
   VarPtr Xs = std::make_shared<SeqVar>();
   VarPtr Ys = std::make_shared<SeqVar>();
-  MS_EXCEPTION_IF_NULL(Xs);
-  MS_EXCEPTION_IF_NULL(Ys);
   // Two patterns share: real_div0, real_div1, add2_y_
   VectorRef real_div0 = VectorRef({real_div0_var_, Xs});
   VectorRef real_div1 = VectorRef({real_div1_var_, Ys});
diff --git a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.h b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.h
index f28d837dcf..0089c33f87 100644
--- a/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.h
+++ b/mindspore/ccsrc/pre_activate/ascend/ir_fusion/lamb_next_mv_rule.h
@@ -87,6 +87,33 @@ class LambNextMVRule : public MultipleOutputPatternProcessPass {
   VarPtr real_div2_var_;
 };
 
+class LambNextMVRuleCond1 : public LambNextMVRule {
+ public:
+  explicit LambNextMVRuleCond1(bool multigraph = true) : LambNextMVRule("lamb_next_mv_rule_cond1", multigraph) {}
+
+  ~LambNextMVRuleCond1() override = default;
+  const BaseRef DefinePattern() const override;
+  BaseRef DefineAnotherPattern() const override;
+};
+
+class LambNextMVRuleCond2 : public LambNextMVRule {
+ public:
+  explicit LambNextMVRuleCond2(bool multigraph = true) : LambNextMVRule("lamb_next_mv_rule_cond2", multigraph) {}
+
+  ~LambNextMVRuleCond2() override = default;
+  const BaseRef DefinePattern() const override;
+  BaseRef DefineAnotherPattern() const override;
+};
+
+class LambNextMVRuleCond3 : public LambNextMVRule {
+ public:
+  explicit LambNextMVRuleCond3(bool multigraph = true) : LambNextMVRule("lamb_next_mv_rule_cond3", multigraph) {}
+
+  ~LambNextMVRuleCond3() override = default;
+  const BaseRef DefinePattern() const override;
+  BaseRef DefineAnotherPattern() const override;
+};
+
 class LambNextMVRuleCond4 : public LambNextMVRule {
  public:
   explicit LambNextMVRuleCond4(bool multigraph = true) : LambNextMVRule("lamb_next_mv_rule_cond4", multigraph) {}
diff --git a/tests/ut/cpp/pre_activate/ascend/ir_fusion/lamb_next_mv_rule_test.cc b/tests/ut/cpp/pre_activate/ascend/ir_fusion/lamb_next_mv_rule_test.cc
index e5b4c6bc32..6ea622d030 100644
--- a/tests/ut/cpp/pre_activate/ascend/ir_fusion/lamb_next_mv_rule_test.cc
+++ b/tests/ut/cpp/pre_activate/ascend/ir_fusion/lamb_next_mv_rule_test.cc
@@ -244,5 +244,125 @@ TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond4_unmatched_real_div1) {
 
   EXPECT_TRUE(CheckEqualGraph(origin_graph, new_graph));
 }
+
+TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond1_fusion) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond1", "before");
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 13; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto fg = GetKernelGraph(g, args_spec_list);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LambNextMVRuleCond1>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(fg);
+
+  FuncGraphPtr g_after = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond1", "after");
+  EXPECT_TRUE(CheckEqualGraph(g_after, new_graph));
+}
+
+TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond1_unmatched) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond1", "un_match");
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 13; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto fg = GetKernelGraph(g, args_spec_list);
+  auto origin_graph = std::make_shared<session::KernelGraph>(*fg);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LambNextMVRuleCond1>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(fg);
+
+  EXPECT_TRUE(CheckEqualGraph(origin_graph, new_graph));
+}
+
+TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond2_fusion) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond2", "before");
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 13; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto fg = GetKernelGraph(g, args_spec_list);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LambNextMVRuleCond2>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(fg);
+
+  FuncGraphPtr g_after = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond2", "after");
+  EXPECT_TRUE(CheckEqualGraph(g_after, new_graph));
+}
+
+TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond2_unmatched) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond2", "un_match");
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 13; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto fg = GetKernelGraph(g, args_spec_list);
+  auto origin_graph = std::make_shared<session::KernelGraph>(*fg);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LambNextMVRuleCond2>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(fg);
+
+  EXPECT_TRUE(CheckEqualGraph(origin_graph, new_graph));
+}
+
+TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond3_fusion) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond3", "before");
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 13; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto fg = GetKernelGraph(g, args_spec_list);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LambNextMVRuleCond3>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(fg);
+
+  FuncGraphPtr g_after = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond3", "after");
+  EXPECT_TRUE(CheckEqualGraph(g_after, new_graph));
+}
+
+TEST_F(TestHWLambNextMVRule, test_lamb_next_mv_rule_cond3_unmatched) {
+  FuncGraphPtr g = get_py_fun_.CallAndParseRet("test_lamb_next_mv_rule_cond3", "un_match");
+  std::vector<int> shp{2, 32, 224, 224};
+  auto x_abstract = std::make_shared<abstract::AbstractTensor>(kFloat32, shp);
+  AbstractBasePtrList args_spec_list;
+  for (size_t i = 0; i < 13; ++i) {
+    args_spec_list.push_back(x_abstract);
+  }
+  auto fg = GetKernelGraph(g, args_spec_list);
+  auto origin_graph = std::make_shared<session::KernelGraph>(*fg);
+
+  auto optimizer = std::make_shared<opt::GraphOptimizer>();
+  auto pm = std::make_shared<opt::PassManager>();
+  pm->AddPass(std::make_shared<opt::LambNextMVRuleCond3>());
+  optimizer->AddPassManager(pm);
+  FuncGraphPtr new_graph = optimizer->Optimize(fg);
+
+  EXPECT_TRUE(CheckEqualGraph(origin_graph, new_graph));
+}
 }  // namespace opt
 }  // namespace mindspore
diff --git a/tests/ut/cpp/python_input/gtest_input/pre_activate/lamb_next_mv_rule_test.py b/tests/ut/cpp/python_input/gtest_input/pre_activate/lamb_next_mv_rule_test.py
index c93c00cd72..5660771723 100644
--- a/tests/ut/cpp/python_input/gtest_input/pre_activate/lamb_next_mv_rule_test.py
+++ b/tests/ut/cpp/python_input/gtest_input/pre_activate/lamb_next_mv_rule_test.py
@@ -24,7 +24,6 @@ make_tuple = Primitive('make_tuple')
 tuple_getitem = Primitive('tuple_getitem')
 LambNextMV = Primitive('LambNextMV')
 
-
 class FnDict:
     def __init__(self):
         self.fnDict = {}
@@ -35,7 +34,6 @@ class FnDict:
     def __getitem__(self, name):
         return self.fnDict[name]
 
-
 def test_lamb_next_mv_rule_cond4(tag):
     fns = FnDict()
 
@@ -170,3 +168,192 @@ def test_lamb_next_mv_rule_cond4(tag):
         return output
 
     return fns[tag]
+
+def test_lamb_next_mv_rule_cond1(tag):
+    fns = FnDict()
+
+    @fns
+    def before(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+               constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        mul0 = Mul(constant_mul0_x, input4)
+        mul1 = Mul(constant_mul1_sub, input3)
+        add0 = Add(mul0, mul1)
+        mul2 = Mul(constant_mul2_x, input1)
+        mul3 = Mul(constant_mul3_sub1, input0)
+        add1 = Add(mul2, mul3)
+        real_div1 = RealDiv(add1, input2)
+        add2 = Add(constant_add2_y, real_div1)
+        sqrt0 = Rsqrt(add2)
+        sqrt1 = Sqrt(real_div1)
+        add4 = Add(constant_add2_y, sqrt1)
+        real_div0 = RealDiv(add0, input5)
+        real_div4 = RealDiv(real_div0, add4)
+        real_div2 = Mul(sqrt0, real_div0)
+        mul4 = Mul(constant_mul4_x, input6)
+        add3 = Add(mul4, real_div2)
+        outputs = make_tuple(add3, add0, add1, real_div4)
+        output = tuple_getitem(outputs, 0)
+        return output
+
+    @fns
+    def after(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+              constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        lamb_next_mv = LambNextMV(input0, input1, input2, input3, input4, input5, input6,
+                                  constant_mul0_x, constant_mul1_sub, constant_mul2_x, constant_mul3_sub1,
+                                  constant_mul4_x, constant_add2_y)
+        outputs = make_tuple(tuple_getitem(lamb_next_mv, 0), tuple_getitem(lamb_next_mv, 1),
+                             tuple_getitem(lamb_next_mv, 2), tuple_getitem(lamb_next_mv, 3))
+        output = tuple_getitem(outputs, 0)
+        return make_tuple(output)
+
+    @fns
+    def un_match(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+                 constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        mul0 = Mul(constant_mul0_x, input4)
+        mul1 = Mul(constant_mul1_sub, input3)
+        add0 = Add(mul0, mul1)
+        mul2 = Mul(constant_mul2_x, input1)
+        mul3 = Mul(constant_mul3_sub1, input0)
+        add1 = Add(mul2, mul3)
+        real_div1 = RealDiv(add1, input2)
+        add2 = Add(constant_add2_y, real_div1)
+        sqrt0 = Rsqrt(add2)
+        sqrt1 = Sqrt(real_div1)
+        # un match
+        add4 = Add(sqrt1, constant_add2_y)
+        real_div0 = RealDiv(add0, input5)
+        real_div4 = RealDiv(real_div0, add4)
+        real_div2 = Mul(sqrt0, real_div0)
+        mul4 = Mul(constant_mul4_x, input6)
+        add3 = Add(mul4, real_div2)
+        outputs = make_tuple(add3, add0, add1, real_div4)
+        output = tuple_getitem(outputs, 0)
+        return output
+
+    return fns[tag]
+
+def test_lamb_next_mv_rule_cond2(tag):
+    fns = FnDict()
+
+    @fns
+    def before(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+               constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        mul0 = Mul(input4, constant_mul0_x)
+        mul1 = Mul(input3, constant_mul1_sub)
+        add0 = Add(mul0, mul1)
+        mul2 = Mul(input1, constant_mul2_x)
+        mul3 = Mul(constant_mul3_sub1, input0)
+        add1 = Add(mul2, mul3)
+        real_div1 = RealDiv(add1, input2)
+        add2 = Add(constant_add2_y, real_div1)
+        sqrt0 = Rsqrt(add2)
+        sqrt1 = Sqrt(real_div1)
+        add4 = Add(sqrt1, constant_add2_y)
+        real_div0 = RealDiv(add0, input5)
+        real_div4 = RealDiv(real_div0, add4)
+        real_div2 = Mul(sqrt0, real_div0)
+        mul4 = Mul(input6, constant_mul4_x)
+        add3 = Add(mul4, real_div2)
+        outputs = make_tuple(add3, add0, add1, real_div4)
+        output = tuple_getitem(outputs, 0)
+        return output
+
+    @fns
+    def after(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+              constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        lamb_next_mv = LambNextMV(input0, input1, input2, input3, input4, input5, input6,
+                                  constant_mul0_x, constant_mul1_sub, constant_mul2_x, constant_mul3_sub1,
+                                  constant_mul4_x, constant_add2_y)
+        outputs = make_tuple(tuple_getitem(lamb_next_mv, 0), tuple_getitem(lamb_next_mv, 1),
+                             tuple_getitem(lamb_next_mv, 2), tuple_getitem(lamb_next_mv, 3))
+        output = tuple_getitem(outputs, 0)
+        return make_tuple(output)
+
+    @fns
+    def un_match(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+                 constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        mul0 = Mul(input4, constant_mul0_x)
+        mul1 = Mul(input3, constant_mul1_sub)
+        add0 = Add(mul0, mul1)
+        mul2 = Mul(input1, constant_mul2_x)
+        mul3 = Mul(constant_mul3_sub1, input0)
+        add1 = Add(mul2, mul3)
+        real_div1 = RealDiv(add1, input2)
+        add2 = Add(constant_add2_y, real_div1)
+        sqrt0 = Rsqrt(add2)
+        sqrt1 = Sqrt(real_div1)
+        # un match
+        add4 = Add(constant_add2_y, sqrt1)
+        real_div0 = RealDiv(add0, input5)
+        real_div4 = RealDiv(real_div0, add4)
+        real_div2 = Mul(sqrt0, real_div0)
+        mul4 = Mul(input6, constant_mul4_x)
+        add3 = Add(mul4, real_div2)
+        outputs = make_tuple(add3, add0, add1, real_div4)
+        output = tuple_getitem(outputs, 0)
+        return output
+
+    return fns[tag]
+
+def test_lamb_next_mv_rule_cond3(tag):
+    fns = FnDict()
+
+    @fns
+    def before(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+               constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        mul0 = Mul(input4, constant_mul0_x)
+        mul1 = Mul(input3, constant_mul1_sub)
+        add0 = Add(mul0, mul1)
+        mul2 = Mul(input1, constant_mul2_x)
+        mul3 = Mul(input0, constant_mul3_sub1)
+        add1 = Add(mul2, mul3)
+        real_div1 = RealDiv(add1, input2)
+        add2 = Add(real_div1, constant_add2_y)
+        sqrt0 = Rsqrt(add2)
+        sqrt1 = Sqrt(real_div1)
+        add4 = Add(sqrt1, constant_add2_y)
+        real_div0 = RealDiv(add0, input5)
+        real_div4 = RealDiv(real_div0, add4)
+        real_div2 = Mul(sqrt0, real_div0)
+        mul4 = Mul(input6, constant_mul4_x)
+        add3 = Add(mul4, real_div2)
+        outputs = make_tuple(add3, add0, add1, real_div4)
+        output = tuple_getitem(outputs, 0)
+        return output
+
+    @fns
+    def after(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+              constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        lamb_next_mv = LambNextMV(input0, input1, input2, input3, input4, input5, input6,
+                                  constant_mul0_x, constant_mul1_sub, constant_mul2_x, constant_mul3_sub1,
+                                  constant_mul4_x, constant_add2_y)
+        outputs = make_tuple(tuple_getitem(lamb_next_mv, 0), tuple_getitem(lamb_next_mv, 1),
+                             tuple_getitem(lamb_next_mv, 2), tuple_getitem(lamb_next_mv, 3))
+        output = tuple_getitem(outputs, 0)
+        return make_tuple(output)
+
+    @fns
+    def un_match(input0, input1, input2, input3, input4, input5, input6, constant_mul0_x, constant_mul1_sub,
+                 constant_mul2_x, constant_mul3_sub1, constant_mul4_x, constant_add2_y):
+        mul0 = Mul(input4, constant_mul0_x)
+        mul1 = Mul(input3, constant_mul1_sub)
+        add0 = Add(mul0, mul1)
+        mul2 = Mul(input1, constant_mul2_x)
+        mul3 = Mul(input0, constant_mul3_sub1)
+        add1 = Add(mul2, mul3)
+        real_div1 = RealDiv(add1, input2)
+        add2 = Add(real_div1, constant_add2_y)
+        sqrt0 = Rsqrt(add2)
+        sqrt1 = Sqrt(real_div1)
+        # un match
+        add4 = Add(constant_add2_y, sqrt1)
+        real_div0 = RealDiv(add0, input5)
+        real_div4 = RealDiv(real_div0, add4)
+        real_div2 = Mul(sqrt0, real_div0)
+        mul4 = Mul(input6, constant_mul4_x)
+        add3 = Add(mul4, real_div2)
+        outputs = make_tuple(add3, add0, add1, real_div4)
+        output = tuple_getitem(outputs, 0)
+        return output
+
+    return fns[tag]