diff --git a/inc/external/ge/ge_api_types.h b/inc/external/ge/ge_api_types.h
index a377c2f7..b77bebfc 100644
--- a/inc/external/ge/ge_api_types.h
+++ b/inc/external/ge/ge_api_types.h
@@ -369,6 +369,8 @@ const std::string PERFORMANCE_MODE = "ge.performance_mode";
 // shape_precise: Shape will not be generalized, use precise shape.
 const std::string SHAPE_GENERALIZED_BUILD_MODE = "ge.shape_generalized_build_mode";
 
+const std::string JIT_COMPILE = "ge.jit_compile";
+
 const std::string MODIFY_MIXLIST = "ge.exec.modify_mixlist";
 
 const std::string OP_PRECISION_MODE = "ge.exec.op_precision_mode";
diff --git a/metadef b/metadef
index 17536092..62c14e1c 160000
--- a/metadef
+++ b/metadef
@@ -1 +1 @@
-Subproject commit 17536092c004f6f9e08116939f4f49e1e11a99d3
+Subproject commit 62c14e1cde161dccf6967f151ece9509f778c416
diff --git a/third_party/fwkacllib/inc/ops/nn_training_ops.h b/third_party/fwkacllib/inc/ops/nn_training_ops.h
index 32da707e..d3775260 100644
--- a/third_party/fwkacllib/inc/ops/nn_training_ops.h
+++ b/third_party/fwkacllib/inc/ops/nn_training_ops.h
@@ -606,6 +606,78 @@ REG_OP(ApplyAdamWithAmsgrad)
     .OP_END_FACTORY_REG(ApplyAdamWithAmsgrad)
 
 
+/**
+*@brief Updates '*var' according to the Adam algorithm..
+*   lr_t := {learning_rate} * sqrt{1 - beta_2^t} / (1 - beta_1^t)
+*   m_t := beta_1 * m_{t-1} + (1 - beta_1) * g
+*   v_t := beta_2 * v_{t-1} + (1 - beta_2) * g * g
+*   vhat_t := max{vhat_{t-1}, v_t}
+*   variable := variable - lr_t * m_t / (sqrt{vhat_t} + epsilon)
+*
+*@par Inputs:
+*Eleven inputs, including:
+*@li var: A mutable tensor. Must be one of the data types defined in
+*    TensorType::NumberType(). Should be from a Variable().
+*@li m: A mutable tensor. Has the same type as "var". Should be from a
+*    Variable().
+*@li v: A mutable tensor. Has the same type as "var". Should be from a
+*    Variable().
+*@li vhat: A mutable tensor. Has the same type as "var". Should be from a
+*    Variable().
+*@li beta1_power: A mutable tensor. Has the same type as "var". Should be from a
+*    Variable().
+*@li beta2_power: A mutable tensor. Has the same type as "var". Should be from a
+*    Variable().
+*@li lr: A tensor for the learning rate. Has the same type as "var". Should be
+*    from a Variable().
+*@li beta1: A mutable tensor. Has the same type as "var". Should be
+*    from a Variable().
+*@li beta2: A mutable tensor. Has the same type as "var". Should be
+*    from a Variable().
+*@li epsilon: A mutable tensor. Has the same type as "var". Should be
+*    from a Variable().
+*@li grad: A tensor for the gradient. Has the same type as "var". Should be
+*    from a Variable().
+*
+*@par Attribute:
+*one attribute, including:
+*@li use_locking: An optional bool. Defaults to "False".
+*    If "True", updating of the "var" tensor is protected by a lock;
+*    otherwise the behavior is undefined, but may exhibit less contention.
+*
+*@par Outputs:
+*four outputs, including:
+*@li var: A mutable tensor. Has the same type as input "var".
+*@li m: A mutable tensor. Has the same type as input "var"
+*@li v: A mutable tensor. Has the same type as input "var"
+*@li vhat: A mutable tensor. Has the same type as input "var"
+*
+*@attention Constraints:
+* The input tensors must have the same shape.
+*
+*@par Third-party framework compatibility
+* Compatible with the TensorFlow operator ResourceApplyKerasMomentum.
+*
+*/
+REG_OP(ApplyAdamWithAmsgradV2)
+    .INPUT(var, TensorType({DT_FLOAT}))
+    .INPUT(m, TensorType({DT_FLOAT}))
+    .INPUT(v, TensorType({DT_FLOAT}))
+    .INPUT(vhat, TensorType({DT_FLOAT}))
+    .INPUT(beta1_power, TensorType({DT_FLOAT}))
+    .INPUT(beta2_power, TensorType({DT_FLOAT}))
+    .INPUT(lr, TensorType({DT_FLOAT}))
+    .INPUT(beta1, TensorType({DT_FLOAT}))
+    .INPUT(beta2, TensorType({DT_FLOAT}))
+    .INPUT(epsilon, TensorType({DT_FLOAT}))
+    .INPUT(grad, TensorType({DT_FLOAT}))
+    .OUTPUT(var, TensorType({DT_FLOAT}))
+    .OUTPUT(m, TensorType({DT_FLOAT}))
+    .OUTPUT(v, TensorType({DT_FLOAT}))
+    .OUTPUT(vhat, TensorType({DT_FLOAT}))
+    .ATTR(use_locking, Bool, false)
+    .OP_END_FACTORY_REG(ApplyAdamWithAmsgradV2)
+
 /**
 *@brief Updates "var" according to the AddSign update.
 *  t-1 mean previous period.
diff --git a/third_party/fwkacllib/inc/toolchain/prof_acl_api.h b/third_party/fwkacllib/inc/toolchain/prof_acl_api.h
index 718fc69d..2353d967 100644
--- a/third_party/fwkacllib/inc/toolchain/prof_acl_api.h
+++ b/third_party/fwkacllib/inc/toolchain/prof_acl_api.h
@@ -36,7 +36,7 @@
 #define PROF_SUBTASK_TIME           0x0000040000000ULL
 #define PROF_OP_DETAIL              0x0000080000000ULL
 
-#define PROF_AICPU_MODEL            0x4000000000000000ULL
+constexpr uint64_t PROF_AICPU_MODEL = 0x4000000000000000ULL;
 #define PROF_MODEL_LOAD             0x8000000000000000ULL
 
 #define PROF_TASK_TRACE             (PROF_MODEL_EXECUTE | PROF_RUNTIME_TRACE | PROF_TRAINING_TRACE | \
@@ -70,7 +70,7 @@
 #define PROF_SUBTASK_TIME_MASK           0x0000040000000ULL
 #define PROF_OP_DETAIL_MASK              0x0000080000000ULL
 
-#define PROF_AICPU_MODEL_MASK            0x4000000000000000ULL
+constexpr uint64_t PROF_AICPU_MODEL_MASK = 0x4000000000000000ULL;
 #define PROF_MODEL_LOAD_MASK             0x8000000000000000ULL
 
 #if (defined(_WIN32) || defined(_WIN64) || defined(_MSC_VER))
diff --git a/third_party/fwkacllib/inc/toolchain/prof_common.h b/third_party/fwkacllib/inc/toolchain/prof_common.h
index 411d7a29..37702c9b 100644
--- a/third_party/fwkacllib/inc/toolchain/prof_common.h
+++ b/third_party/fwkacllib/inc/toolchain/prof_common.h
@@ -152,7 +152,7 @@ struct MsprofGeProfInferData {
     uint8_t  reserve[MSPROF_GE_INFER_DATA_RESERVE_BYTES];
 };
 
-#define MSPROF_GE_TASK_DATA_RESERVE_BYTES 12
+constexpr int32_t MSPROF_GE_TASK_DATA_RESERVE_BYTES = 12;
 #define MSPROF_GE_OP_TYPE_LEN 56
 enum MsprofGeTaskType {
     MSPROF_GE_TASK_TYPE_AI_CORE = 0,