diff --git a/include/tvm/relay/transform.h b/include/tvm/relay/transform.h
index cbd6a88e584e..ce8b592a0f6d 100644
--- a/include/tvm/relay/transform.h
+++ b/include/tvm/relay/transform.h
@@ -377,7 +377,7 @@ TVM_DLL Pass EtaExpand(bool expand_constructor, bool expand_global_var);
  *
  * \return The pass.
  */
-TVM_DLL Pass PartitionGraph();
+TVM_DLL Pass PartitionGraph(runtime::PackedFunc foptimize = nullptr);
 
 /*!
  * \brief Inline the global functions marked as `inline` in a given Relay
diff --git a/python/tvm/relay/op/contrib/arm_compute_lib.py b/python/tvm/relay/op/contrib/arm_compute_lib.py
index 8dfb3b7e0bf4..b42ca9faaefc 100644
--- a/python/tvm/relay/op/contrib/arm_compute_lib.py
+++ b/python/tvm/relay/op/contrib/arm_compute_lib.py
@@ -54,6 +54,16 @@ def partition_for_arm_compute_lib(mod, params=None):
     -------
     ret : annotated and partitioned module.
     """
+
+    def optimize(mod):
+        foptimize = tvm._ffi.get_global_func("relay.ext.arm_compute_lib.optimize")
+        if foptimize is None:
+            raise RuntimeError(
+                "Failed to get the Arm compute library optimization pass. "
+                "Did you build with USE_ARM_COMPUTE_LIB=ON?"
+            )
+        return foptimize(mod)
+
     if params:
         mod["main"] = bind_params_by_name(mod["main"], params)
 
@@ -62,7 +72,7 @@ def partition_for_arm_compute_lib(mod, params=None):
             transform.InferType(),
             transform.MergeComposite(arm_compute_lib_pattern_table()),
             transform.AnnotateTarget("arm_compute_lib"),
-            transform.PartitionGraph(),
+            transform.PartitionGraph(optimize),
         ]
     )
 
diff --git a/python/tvm/relay/transform/transform.py b/python/tvm/relay/transform/transform.py
index 060547e4c4d7..f1bcfd467cae 100644
--- a/python/tvm/relay/transform/transform.py
+++ b/python/tvm/relay/transform/transform.py
@@ -627,7 +627,7 @@ def EliminateCommonSubexpr(fskip=None):
 
     Parameters
     ----------
-    fskip: Callable
+    fskip: Optional[Callable]
         The callback function that decides whether an expression should be
         skipped.
 
@@ -681,16 +681,21 @@ def LambdaLift():
     return _ffi_api.LambdaLift()
 
 
-def PartitionGraph():
+def PartitionGraph(foptimize=None):
     """Partition a Relay program into regions that can be executed on different
     backends.
 
+    Parameters
+    ----------
+    foptimize: Optional[Callable]
+        The callback function that optimizes the partitioned Relay functions.
+
     Returns
     -------
     ret: tvm.transform.Pass
         The registered pass that partitions the Relay program.
     """
-    return _ffi_api.PartitionGraph()
+    return _ffi_api.PartitionGraph(foptimize)
 
 
 def AnnotateTarget(targets):
diff --git a/src/relay/transforms/partition_graph.cc b/src/relay/transforms/partition_graph.cc
index 75bc46387cc6..ccf0fdb7e204 100644
--- a/src/relay/transforms/partition_graph.cc
+++ b/src/relay/transforms/partition_graph.cc
@@ -113,7 +113,8 @@ struct RegionFuncMetadata {
 
 class Partitioner : public MixedModeMutator {
  public:
-  explicit Partitioner(const IRModule& module) : module_(module) {
+  explicit Partitioner(const IRModule& module, runtime::PackedFunc foptimize)
+      : module_(module), foptimize_(foptimize) {
     for (auto f : module->functions) {
       GlobalVar f_var = f.first;
       BaseFunc f_func = f.second;
@@ -308,12 +309,12 @@ class Partitioner : public MixedModeMutator {
     if (!params_bind.empty()) {
       global_region_func = Downcast<Function>(relay::Bind(global_region_func, params_bind));
     }
-    std::string ext_opt = "relay.ext." + target + ".optimize";
-    auto pf = tvm::runtime::Registry::Get(ext_opt);
-    if (pf != nullptr) {
+
+    // Optimize the partitioned function using user-specified optimization pass.
+    if (foptimize_ != nullptr) {
       auto mod = IRModule::FromExpr(global_region_func);
       mod = transform::InferType()(mod);
-      mod = (*pf)(mod);
+      mod = foptimize_(mod);
       global_region_func = Downcast<Function>(mod->Lookup("main"));
     }
 
@@ -392,6 +393,8 @@ class Partitioner : public MixedModeMutator {
 
   /*!\brief The IRModule used for partitioning. */
   IRModule module_;
+  /*!\brief The optimize pass for the partitioned functions. */
+  const PackedFunc foptimize_;
 };
 
 IRModule RemoveDefaultAnnotations(IRModule module) {
@@ -484,7 +487,7 @@ IRModule FlattenTupleOutputs(IRModule module) {
 
 namespace transform {
 
-Pass PartitionGraph() {
+Pass PartitionGraph(const PackedFunc foptimize) {
   runtime::TypedPackedFunc<IRModule(IRModule, PassContext)> flatten_tuples = [=](IRModule m,
                                                                                  PassContext pc) {
     // There could be compiler_end annotations on tuples
@@ -503,8 +506,10 @@ Pass PartitionGraph() {
     return partitioning::RemoveDefaultAnnotations(m);
   };
 
-  runtime::TypedPackedFunc<IRModule(IRModule, PassContext)> part_func =
-      [=](IRModule m, PassContext pc) { return partitioning::Partitioner(m).Partition(); };
+  runtime::TypedPackedFunc<IRModule(IRModule, PassContext)> part_func = [=](IRModule m,
+                                                                            PassContext pc) {
+    return partitioning::Partitioner(m, foptimize).Partition();
+  };
 
   auto flatten_tuples_pass = CreateModulePass(flatten_tuples, 0, "FlattenNestedTuples", {});
   auto remove_default_pass = CreateModulePass(remove_defaults, 0, "RemoveDefaultAnnotations", {});
diff --git a/tests/python/relay/test_pass_partition_graph.py b/tests/python/relay/test_pass_partition_graph.py
index 2fd440e1c2c9..1e5fe133aca7 100644
--- a/tests/python/relay/test_pass_partition_graph.py
+++ b/tests/python/relay/test_pass_partition_graph.py
@@ -1327,8 +1327,6 @@ def test_extern_opt():
     def Optimize(mod):
         return relay.transform.FoldConstant()(mod)
 
-    tvm.register_func("relay.ext.test_target.optimize", Optimize)
-
     x = relay.var("x", shape=(2, 2))
     y0 = relay.var("y0", shape=(2, 2))
     y1 = relay.var("y1", shape=(2, 2))
@@ -1342,7 +1340,7 @@ def Optimize(mod):
     mod = tvm.IRModule()
     mod["main"] = f
     mod = transform.InferType()(mod)
-    mod = transform.PartitionGraph()(mod)
+    mod = transform.PartitionGraph(Optimize)(mod)
 
     try:
         t0 = mod["test_target_0"]