Fix build failures

backends/apple/coreml/runtime/delegate/backend_delegate.h

@@ -6,6 +6,7 @@
 // Please refer to the license found in the LICENSE file in the root directory of the source tree.
 
 #include <system_error>
+#include <unordered_map>
 #include <vector>
 
 namespace executorchcoreml {

backends/apple/coreml/runtime/kvstore/database.hpp

@@ -8,6 +8,7 @@
 #pragma once
 
 #include <bitset>
+#include <functional>
 #include <memory>
 #include <string>
 #include <system_error>

backends/apple/coreml/runtime/kvstore/key_value_store.hpp

@@ -7,6 +7,7 @@
 
 #pragma once
 
+#import <functional>
 #include <optional>
 #include <memory>
 #include <string>

backends/apple/coreml/runtime/test/CoreMLBackendDelegateTests.mm

@@ -14,7 +14,6 @@
 #import <executorch/runtime/executor/method.h>
 #import <executorch/runtime/executor/program.h>
 #import <executorch/runtime/platform/runtime.h>
-#import <executorch/util/util.h>
 
 static constexpr size_t kRuntimeMemorySize = 10 * 1024U * 1024U; // 10 MB
 
@@ -95,6 +94,33 @@
 
     return result;
 }
+
+Result<std::vector<Buffer>> prepare_input_tensors(Method& method) {
+    MethodMeta method_meta = method.method_meta();
+    size_t num_inputs = method_meta.num_inputs();
+    std::vector<std::vector<uint8_t>> buffers;
+    for (size_t i = 0; i < num_inputs; i++) {
+        Result<TensorInfo> tensor_meta = method_meta.input_tensor_meta(i);
+        if (!tensor_meta.ok()) {
+            ET_LOG(Info, "Skipping non-tensor input %zu", i);
+            continue;
+        }
+        Buffer buffer(tensor_meta->nbytes(), 1);
+        auto sizes = tensor_meta->sizes();
+        exec_aten::TensorImpl tensor_impl(tensor_meta->scalar_type(), std::size(sizes), const_cast<int *>(sizes.data()), buffer.data());
+        exec_aten::Tensor tensor(&tensor_impl);
+        EValue input_value(std::move(tensor));
+        Error err = method.set_input(input_value, i);
+        if (err != Error::Ok) {
+            ET_LOG(Error, "Failed to prepare input %zu: 0x%" PRIx32, i, (uint32_t)err);
+            return err;
+        }
+        buffers.emplace_back(std::move(buffer));
+    }
+
+    return buffers;
+}
+
 }
 
 @interface CoreMLBackendDelegateTests : XCTestCase
@@ -145,15 +171,12 @@ - (void)executeModelAtURL:(NSURL *)modelURL nTimes:(NSUInteger)nTimes {
         MemoryManager memoryManger(&methodAllocator, &plannedAllocator);
         auto method = program->load_method(methodName.get().c_str(), &memoryManger);
         XCTAssert(method.ok());
-        auto inputs = util::PrepareInputTensors(method.get());
-
+        auto inputBuffers = prepare_input_tensors(method.get());
         auto status = method->execute();
         XCTAssertEqual(status, Error::Ok);
         auto outputs = methodAllocator.allocateList<EValue>(method->outputs_size());
         status = method->get_outputs(outputs, method->outputs_size());
         XCTAssertEqual(status, Error::Ok);
-
-        util::FreeInputs(inputs);
     }
 }
 

examples/apple/coreml/executor_runner/main.mm

@@ -211,6 +211,32 @@ Args parse_command_line_args(NSArray<NSString *> *args) {
     return result;
 }
 
+Result<std::vector<Buffer>> prepare_input_tensors(Method& method) {
+    MethodMeta method_meta = method.method_meta();
+    size_t num_inputs = method_meta.num_inputs();
+    std::vector<std::vector<uint8_t>> buffers;
+    for (size_t i = 0; i < num_inputs; i++) {
+        Result<TensorInfo> tensor_meta = method_meta.input_tensor_meta(i);
+        if (!tensor_meta.ok()) {
+            ET_LOG(Info, "Skipping non-tensor input %zu", i);
+            continue;
+        }
+        Buffer buffer(tensor_meta->nbytes(), 1);
+        auto sizes = tensor_meta->sizes();
+        exec_aten::TensorImpl tensor_impl(tensor_meta->scalar_type(), std::size(sizes), const_cast<int *>(sizes.data()), buffer.data());
+        exec_aten::Tensor tensor(&tensor_impl);
+        EValue input_value(std::move(tensor));
+        Error err = method.set_input(input_value, i);
+        if (err != Error::Ok) {
+            ET_LOG(Error, "Failed to prepare input %zu: 0x%" PRIx32, i, (uint32_t)err);
+            return err;
+        }
+        buffers.emplace_back(std::move(buffer));
+    }
+
+    return buffers;
+}
+
 double calculate_mean(const std::vector<double>& durations) {
     if (durations.size() == 0) {
         return 0.0;
@@ -293,7 +319,7 @@ int main(int argc, char * argv[]) {
         ET_CHECK_MSG(method_name.ok(), "Failed to load method with name=%s from program=%p", method_name.get().c_str(), program.get());
         ET_LOG(Info, "Running method = %s", method_name.get().c_str());
 
-        auto inputs = util::PrepareInputTensors(*method);
+        auto inputs = prepare_input_tensors(*method);
         ET_LOG(Info, "Inputs prepared.");
 
         // Run the model.
@@ -322,7 +348,6 @@ int main(int argc, char * argv[]) {
             }
         }
 
-        util::FreeInputs(inputs);
-        return 0;
+        return EXIT_SUCCESS;
     }
 }