[iOS] EXC_BAD_ACCESS in bridgeless mode - runtime captured by reference in async lambda

Environment

• react-native-fast-tflite: 2.0.0
• React Native: 0.84 (bridgeless mode)
• iOS

Problem

TensorflowPlugin.cpp captures runtime by reference ([=, &runtime])
in async lambdas passed to callInvoker->invokeAsync. When the lambda
executes asynchronously, the runtime reference is dangling — causing
EXC_BAD_ACCESS.

Two occurrences:

1. callInvoker->invokeAsync([=, &runtime]() { ← loadTensorflowModel
2. this->_callInvoker->invokeAsync([=, &runtime]() { ← run()

Fix

Capture runtime by pointer instead:

// BEFORE
callInvoker->invokeAsync([=, &runtime]() {
  auto result = jsi::Object::createFromHostObject(runtime, plugin);
  promise->resolve(std::move(result));
});

// AFTER  
auto* runtimePtr = &runtime;
callInvoker->invokeAsync([=]() {
  auto result = jsi::Object::createFromHostObject(*runtimePtr, plugin);
  promise->resolve(std::move(result));
});

Same fix for the second occurrence in run().

Workaround

Use react-native-nitro-tflite (unofficial drop-in replacement).

Start in TensorflowPlugin.cpp and inspect the asynchronous callInvoker invocations in loadTensorflowModel and run(), focusing on how runtime is captured. Confirm both occurrences no longer rely on a dangling reference, then build or test the iOS bridgeless configuration and verify the EXC_BAD_ACCESS issue is resolved.