Merge branch 'main' into jz/qwen3-benchmark

Author: jackzhxng

examples/demo-apps/apple_ios/LLaMA/README.md

@@ -37,7 +37,7 @@ Download already exported LLaMA/LLaVA models along with tokenizers from [Hugging
 
 4. To run on a device, ensure you have it set up for development and a provisioning profile with the `increased-memory-limit` entitlement. Update the app's bundle identifier to match your provisioning profile with the required capability.
 
-5. After successfully launching the app, copy the exported ExecuTorch model (`.pte`) and tokenizer (`.model`) files to the iLLaMA folder.
+5. After successfully launching the app, copy the exported ExecuTorch model (`.pte`) and tokenizer (`.model`) files to the iLLaMA folder. Three models are currently supported at the moment - Llama, Qwen3, and Llava multimodal. Please ensure that your model `.pte` file starts with `llama`, `qwen3`, or `llava` so that the app selects the correct model type.
 
     - **For the Simulator:** Drag and drop both files onto the Simulator window and save them in the `On My iPhone > iLLaMA` folder.
     - **For a Device:** Open a separate Finder window, navigate to the Files tab, drag and drop both files into the iLLaMA folder, and wait for the copying to finish.

extension/apple/ExecuTorch/Exported/ExecuTorchTensor.h

@@ -670,4 +670,82 @@ __attribute__((deprecated("This API is experimental.")))
 
 @end
 
+#pragma mark - Empty Category
+
+@interface ExecuTorchTensor (Empty)
+
+/**
+ * Creates an empty tensor with the specified shape, strides, data type, and shape dynamism.
+ *
+ * @param shape An NSArray of NSNumber objects representing the desired shape.
+ * @param strides An NSArray of NSNumber objects representing the desired strides.
+ * @param dataType An ExecuTorchDataType value specifying the element type.
+ * @param shapeDynamism An ExecuTorchShapeDynamism value specifying whether the shape is static or dynamic.
+ * @return A new, empty ExecuTorchTensor instance.
+ */
++ (instancetype)emptyTensorWithShape:(NSArray<NSNumber *> *)shape
+                             strides:(NSArray<NSNumber *> *)strides
+                            dataType:(ExecuTorchDataType)dataType
+                       shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism
+    NS_SWIFT_NAME(empty(shape:strides:dataType:shapeDynamism:));
+
+/**
+ * Creates an empty tensor with the specified shape, data type, and shape dynamism.
+ *
+ * @param shape An NSArray of NSNumber objects representing the desired shape.
+ * @param dataType An ExecuTorchDataType value specifying the element type.
+ * @param shapeDynamism An ExecuTorchShapeDynamism value specifying whether the shape is static or dynamic.
+ * @return A new, empty ExecuTorchTensor instance.
+ */
++ (instancetype)emptyTensorWithShape:(NSArray<NSNumber *> *)shape
+                            dataType:(ExecuTorchDataType)dataType
+                       shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism
+    NS_SWIFT_NAME(empty(shape:dataType:shapeDynamism:));
+
+/**
+ * Creates an empty tensor with the specified shape and data type, using dynamic bound shape.
+ *
+ * @param shape An NSArray of NSNumber objects representing the desired shape.
+ * @param dataType An ExecuTorchDataType value specifying the element type.
+ * @return A new, empty ExecuTorchTensor instance.
+ */
++ (instancetype)emptyTensorWithShape:(NSArray<NSNumber *> *)shape
+                            dataType:(ExecuTorchDataType)dataType
+    NS_SWIFT_NAME(empty(shape:dataType:));
+
+/**
+ * Creates an empty tensor similar to the given tensor, with the specified data type and shape dynamism.
+ *
+ * @param tensor An existing ExecuTorchTensor instance whose shape and strides are used.
+ * @param dataType An ExecuTorchDataType value specifying the desired element type.
+ * @param shapeDynamism An ExecuTorchShapeDynamism value specifying whether the shape is static or dynamic.
+ * @return A new, empty ExecuTorchTensor instance with the same shape as the provided tensor.
+ */
++ (instancetype)emptyTensorLikeTensor:(ExecuTorchTensor *)tensor
+                             dataType:(ExecuTorchDataType)dataType
+                        shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism
+    NS_SWIFT_NAME(empty(like:dataType:shapeDynamism:));
+
+/**
+ * Creates an empty tensor similar to the given tensor, with the specified data type.
+ *
+ * @param tensor An existing ExecuTorchTensor instance whose shape and strides are used.
+ * @param dataType An ExecuTorchDataType value specifying the desired element type.
+ * @return A new, empty ExecuTorchTensor instance with the same shape as the provided tensor.
+ */
++ (instancetype)emptyTensorLikeTensor:(ExecuTorchTensor *)tensor
+                             dataType:(ExecuTorchDataType)dataType
+    NS_SWIFT_NAME(empty(like:dataType:));
+
+/**
+ * Creates an empty tensor similar to the given tensor.
+ *
+ * @param tensor An existing ExecuTorchTensor instance.
+ * @return A new, empty ExecuTorchTensor instance with the same properties as the provided tensor.
+ */
++ (instancetype)emptyTensorLikeTensor:(ExecuTorchTensor *)tensor
+    NS_SWIFT_NAME(empty(like:));
+
+@end
+
 NS_ASSUME_NONNULL_END

extension/apple/ExecuTorch/Exported/ExecuTorchTensor.mm

@@ -591,3 +591,61 @@ - (instancetype)initWithUnsignedInteger:(NSUInteger)scalar {
 }
 
 @end
+
+@implementation ExecuTorchTensor (Empty)
+
++ (instancetype)emptyTensorWithShape:(NSArray<NSNumber *> *)shape
+                             strides:(NSArray<NSNumber *> *)strides
+                            dataType:(ExecuTorchDataType)dataType
+                       shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism {
+  auto tensor = empty_strided(
+    utils::toVector<SizesType>(shape),
+    utils::toVector<StridesType>(strides),
+    static_cast<ScalarType>(dataType),
+    static_cast<TensorShapeDynamism>(shapeDynamism)
+  );
+  return [[self alloc] initWithNativeInstance:&tensor];
+}
+
++ (instancetype)emptyTensorWithShape:(NSArray<NSNumber *> *)shape
+                            dataType:(ExecuTorchDataType)dataType
+                       shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism {
+  return [self emptyTensorWithShape:shape
+                            strides:@[]
+                           dataType:dataType
+                      shapeDynamism:shapeDynamism];
+}
+
++ (instancetype)emptyTensorWithShape:(NSArray<NSNumber *> *)shape
+                            dataType:(ExecuTorchDataType)dataType {
+  return [self emptyTensorWithShape:shape
+                            strides:@[]
+                           dataType:dataType
+                      shapeDynamism:ExecuTorchShapeDynamismDynamicBound];
+}
+
++ (instancetype)emptyTensorLikeTensor:(ExecuTorchTensor *)tensor
+                             dataType:(ExecuTorchDataType)dataType
+                        shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism {
+  return [self emptyTensorWithShape:tensor.shape
+                            strides:tensor.strides
+                           dataType:dataType
+                      shapeDynamism:shapeDynamism];
+}
+
++ (instancetype)emptyTensorLikeTensor:(ExecuTorchTensor *)tensor
+                             dataType:(ExecuTorchDataType)dataType {
+  return [self emptyTensorWithShape:tensor.shape
+                            strides:tensor.strides
+                           dataType:dataType
+                      shapeDynamism:tensor.shapeDynamism];
+}
+
++ (instancetype)emptyTensorLikeTensor:(ExecuTorchTensor *)tensor {
+  return [self emptyTensorWithShape:tensor.shape
+                            strides:tensor.strides
+                           dataType:tensor.dataType
+                      shapeDynamism:tensor.shapeDynamism];
+}
+
+@end

extension/apple/ExecuTorch/__tests__/TensorTest.swift

@@ -548,4 +548,24 @@ class TensorTest: XCTestCase {
       XCTAssertEqual(UnsafeBufferPointer(start: pointer.assumingMemoryBound(to: UInt.self), count: count).first, 42)
     }
   }
+
+  func testEmpty() {
+    let tensor = Tensor.empty(shape: [3, 4], dataType: .float)
+    XCTAssertEqual(tensor.shape, [3, 4])
+    XCTAssertEqual(tensor.count, 12)
+    tensor.bytes { pointer, count, dataType in
+      XCTAssertNotNil(pointer)
+      XCTAssertEqual(count, 12)
+      XCTAssertEqual(dataType, .float)
+    }
+  }
+
+  func testEmptyLike() {
+    let other = Tensor.empty(shape: [2, 2], dataType: .int)
+    let tensor = Tensor.empty(like: other)
+    XCTAssertEqual(tensor.shape, other.shape)
+    XCTAssertEqual(tensor.strides, other.strides)
+    XCTAssertEqual(tensor.dimensionOrder, other.dimensionOrder)
+    XCTAssertEqual(tensor.dataType, other.dataType)
+  }
 }