Overloads for Module execute API.

Summary: #8363

Reviewed By: mergennachin

Differential Revision: D71921054

Author: shoumikhin

extension/apple/ExecuTorch/Exported/ExecuTorchModule.h

@@ -130,6 +130,49 @@ __attribute__((deprecated("This API is experimental.")))
                                                  error:(NSError **)error
     NS_SWIFT_NAME(execute(_:_:));
 
+/**
+ * Executes a specific method with the provided single input value.
+ *
+ * The method is loaded on demand if not already loaded.
+ *
+ * @param methodName A string representing the method name.
+ * @param value An ExecuTorchValue object representing the input.
+ * @param error A pointer to an NSError pointer that is set if an error occurs.
+ * @return An NSArray of ExecuTorchValue objects representing the outputs, or nil in case of an error.
+ */
+- (nullable NSArray<ExecuTorchValue *> *)executeMethod:(NSString *)methodName
+                                             withInput:(ExecuTorchValue *)value
+                                                 error:(NSError **)error
+    NS_SWIFT_NAME(execute(_:_:));
+
+/**
+ * Executes a specific method with no input values.
+ *
+ * The method is loaded on demand if not already loaded.
+ *
+ * @param methodName A string representing the method name.
+ * @param error A pointer to an NSError pointer that is set if an error occurs.
+ * @return An NSArray of ExecuTorchValue objects representing the outputs, or nil in case of an error.
+ */
+- (nullable NSArray<ExecuTorchValue *> *)executeMethod:(NSString *)methodName
+                                                 error:(NSError **)error
+    NS_SWIFT_NAME(execute(_:));
+
+/**
+ * Executes a specific method with the provided input tensors.
+ *
+ * The method is loaded on demand if not already loaded.
+ *
+ * @param methodName A string representing the method name.
+ * @param tensors An NSArray of ExecuTorchTensor objects representing the inputs.
+ * @param error A pointer to an NSError pointer that is set if an error occurs.
+ * @return An NSArray of ExecuTorchValue objects representing the outputs, or nil in case of an error.
+ */
+- (nullable NSArray<ExecuTorchValue *> *)executeMethod:(NSString *)methodName
+                                           withTensors:(NSArray<ExecuTorchTensor *> *)tensors
+                                                 error:(NSError **)error
+    NS_SWIFT_NAME(execute(_:_:));
+
 + (instancetype)new NS_UNAVAILABLE;
 - (instancetype)init NS_UNAVAILABLE;
 

extension/apple/ExecuTorch/Exported/ExecuTorchModule.mm

@@ -139,4 +139,31 @@ - (BOOL)isMethodLoaded:(NSString *)methodName {
   return outputs;
 }
 
+- (nullable NSArray<ExecuTorchValue *> *)executeMethod:(NSString *)methodName
+                                             withInput:(ExecuTorchValue *)value
+                                                 error:(NSError **)error {
+  return [self executeMethod:methodName
+                  withInputs:@[value]
+                       error:error];
+}
+
+- (nullable NSArray<ExecuTorchValue *> *)executeMethod:(NSString *)methodName
+                                                 error:(NSError **)error {
+  return [self executeMethod:methodName
+                  withInputs:@[]
+                       error:error];
+}
+
+- (nullable NSArray<ExecuTorchValue *> *)executeMethod:(NSString *)methodName
+                                           withTensors:(NSArray<ExecuTorchTensor *> *)tensors
+                                                 error:(NSError **)error {
+  NSMutableArray<ExecuTorchValue *> *values = [NSMutableArray arrayWithCapacity:tensors.count];
+  for (ExecuTorchTensor *tensor in tensors) {
+    [values addObject:[ExecuTorchValue valueWithTensor:tensor]];
+  }
+  return [self executeMethod:methodName
+                  withInputs:values
+                       error:error];
+}
+
 @end

extension/apple/ExecuTorch/__tests__/ModuleTest.swift

@@ -63,7 +63,7 @@ class ModuleTest: XCTestCase {
     let inputTensor = inputData.withUnsafeMutableBytes {
       Tensor(bytesNoCopy: $0.baseAddress!, shape:[1], dataType: .float)
     }
-    let inputs = [Value(inputTensor), Value(inputTensor)]
+    let inputs = [inputTensor, inputTensor]
     var outputs: [Value]?
     XCTAssertNoThrow(outputs = try module.execute("forward", inputs))
     var outputData: [Float] = [2.0]