From c30ae8c28c3f9ad7356b252a2d07537f966db703 Mon Sep 17 00:00:00 2001
From: Shushi Hong <820958424@qq.com>
Date: Sat, 13 Jun 2026 21:30:10 -0400
Subject: [PATCH] [Runtime][CoreML] Fix FFI casts in CoreML runtime

The CoreML runtime still used legacy packed argument conversions, including direct AnyView-to-string conversion, type_code checks, and old tensor handle constants. After the FFI update, enabling USE_COREML failed to compile and the runtime create function was not registered.

Update the runtime to use current PackedArgs cast helpers for strings, indices, and DLTensor arguments, and use the Objective-C NSArray type for CoreML metadata inputs. This restores the CoreML runtime registration when USE_COREML is enabled.
---
 .../extra/contrib/coreml/coreml_runtime.mm    | 30 ++++++-------------
 1 file changed, 9 insertions(+), 21 deletions(-)

diff --git a/src/runtime/extra/contrib/coreml/coreml_runtime.mm b/src/runtime/extra/contrib/coreml/coreml_runtime.mm
index 82f7c51c9ea7..a72948b250a7 100644
--- a/src/runtime/extra/contrib/coreml/coreml_runtime.mm
+++ b/src/runtime/extra/contrib/coreml/coreml_runtime.mm
@@ -22,6 +22,7 @@
  */
 #include <tvm/ffi/function.h>
 #include <tvm/ffi/reflection/registry.h>
+#include <tvm/runtime/logging.h>
 
 #include "../../../../support/bytes_io.h"
 #include "coreml_runtime.h"
@@ -136,12 +137,12 @@
     return ffi::Function([this](ffi::PackedArgs args, ffi::Any* rv) { model_->Invoke(); });
   } else if (name == "set_input") {
     return ffi::Function([this](ffi::PackedArgs args, ffi::Any* rv) {
-      const auto& input_name = args[0].operator std::string();
-      model_->SetInput(input_name, args[1]);
+      model_->SetInput(args[0].cast<std::string>(), args[1].cast<DLTensor*>());
     });
   } else if (name == "get_output") {
-    return ffi::Function(
-        [this](ffi::PackedArgs args, ffi::Any* rv) { *rv = model_->GetOutput(args[0]); });
+    return ffi::Function([this](ffi::PackedArgs args, ffi::Any* rv) {
+      *rv = model_->GetOutput(args[0].cast<int>());
+    });
   } else if (name == "get_num_outputs") {
     return ffi::Function(
         [this](ffi::PackedArgs args, ffi::Any* rv) { *rv = model_->GetNumOutputs(); });
@@ -154,18 +155,11 @@
       NSDictionary* json = [NSJSONSerialization JSONObjectWithData:data
                                                            options:NSJSONReadingAllowFragments
                                                              error:nil];
-      NSffi::Array<NSString*>* input_names = json[@"inputs"];
+      NSArray<NSString*>* input_names = json[@"inputs"];
 
       // Copy input tensors to corresponding data entries.
       for (auto i = 0; i < args.size() - 1; ++i) {
-        TVM_FFI_ICHECK(args[i].type_code() == kTVMDLTensorHandle ||
-                       args[i].type_code() == kTVMTensorHandle)
-            << "Expect Tensor or DLTensor as inputs\n";
-        if (args[i].type_code() == kTVMDLTensorHandle || args[i].type_code() == kTVMTensorHandle) {
-          model_->SetInput([input_names[i] UTF8String], args[i]);
-        } else {
-          LOG(FATAL) << "Not implemented";
-        }
+        model_->SetInput([input_names[i] UTF8String], args[i].cast<DLTensor*>());
       }
 
       // Execute the subgraph.
@@ -173,13 +167,7 @@
 
       // TODO: Support multiple outputs.
       Tensor out = model_->GetOutput(0);
-      if (args[args.size() - 1].type_code() == kTVMDLTensorHandle) {
-        DLTensor* arg = args[args.size() - 1];
-        out.CopyTo(arg);
-      } else {
-        Tensor arg = args[args.size() - 1];
-        out.CopyTo(arg);
-      }
+      out.CopyTo(args[args.size() - 1].cast<DLTensor*>());
       *rv = out;
     });
   } else {
@@ -196,7 +184,7 @@
 TVM_FFI_STATIC_INIT_BLOCK() {
   namespace refl = tvm::ffi::reflection;
   refl::GlobalDef().def_packed("tvm.coreml_runtime.create", [](ffi::PackedArgs args, ffi::Any* rv) {
-    *rv = CoreMLRuntimeCreate(args[0], args[1]);
+    *rv = CoreMLRuntimeCreate(args[0].cast<std::string>(), args[1].cast<std::string>());
   });
 }