Enable quantized models by default on iOS APIs. Also makes related changes to docs.

PiperOrigin-RevId: 337876402
Change-Id: I7abb19894297cfe2781997b3e3e3ba4074fbf7e4

tensorflow/lite/delegates/gpu/metal_delegate.h

@@ -47,10 +47,15 @@ typedef struct {
   bool allow_precision_loss;
   TFLGpuDelegateWaitType wait_type;
   // Allows execution of integer quantized models
-  // TODO(b/169350710): Enable by default.
   bool enable_quantization;
 } TFLGpuDelegateOptions;
 
+// Populates TFLGpuDelegateOptions as follows:
+//   allow_precision_loss = false;
+//   wait_type = TFLGpuDelegateWaitType::TFLGpuDelegateWaitTypePassive;
+//   enable_quantization = true;
+TFL_CAPI_EXPORT extern TFLGpuDelegateOptions TFLGpuDelegateOptionsDefault(void);
+
 // Creates a new delegate instance that need to be destroyed with
 // `TFLDeleteTfLiteGpuDelegate` when delegate is no longer used by TFLite.
 // When `options` is set to `nullptr`, the following default values are used:

tensorflow/lite/delegates/gpu/metal_delegate.mm

@@ -177,10 +177,7 @@ class Delegate {
     if (options) {
       options_ = *options;
     } else {
-      // Default options.
+      options_ = TFLGpuDelegateOptionsDefault();
-      options_.allow_precision_loss = false;
-      options_.enable_quantization = false;
-      options_.wait_type = TFLGpuDelegateWaitType::TFLGpuDelegateWaitTypePassive;
     }
     metal_device_ = MTLCreateSystemDefaultDevice();
     command_queue_ = [metal_device_ newCommandQueue];
@@ -732,3 +729,12 @@ bool TFLGpuDelegateSetCommandEncoder(
   metal_delegate->SetCommandEncoder(encoder, control_encoder);
   return true;
 }
+
+TFLGpuDelegateOptions TFLGpuDelegateOptionsDefault() {
+  TFLGpuDelegateOptions options = {
+      .allow_precision_loss = false,
+      .wait_type = TFLGpuDelegateWaitType::TFLGpuDelegateWaitTypePassive,
+      .enable_quantization = true,
+  };
+  return options;
+}

tensorflow/lite/experimental/objc/apis/TFLMetalDelegate.h

@@ -57,7 +57,7 @@ typedef NS_ENUM(NSUInteger, TFLMetalDelegateThreadWaitType) {
 
 /**
  * Indicates whether the GPU delegate allows execution of an 8-bit quantized model. The default is
- * `false`.
+ * `true`.
  */
 @property(nonatomic, getter=isQuantizationEnabled) BOOL quantizationEnabled;
 

tensorflow/lite/experimental/objc/sources/TFLMetalDelegate.m

@@ -29,6 +29,7 @@ NS_ASSUME_NONNULL_BEGIN
 - (instancetype)init {
   self = [super init];
   if (self != nil) {
+    _quantizationEnabled = true;
     _waitType = TFLMetalDelegateThreadWaitTypePassive;
   }
   return self;

tensorflow/lite/experimental/swift/Sources/MetalDelegate.swift

@@ -62,8 +62,8 @@ extension MetalDelegate {
     public var waitType: ThreadWaitType = .passive
 
     /// Indicates whether the GPU delegate allows execution of an 8-bit quantized model. The default
-    /// is `false`.
+    /// is `true`.
-    public var isQuantizationEnabled = false
+    public var isQuantizationEnabled = true
 
     /// Creates a new instance with the default values.
     public init() {}

tensorflow/lite/experimental/swift/TensorFlowLiteSwift.podspec.template

@@ -52,8 +52,7 @@ Pod::Spec.new do |s|
     metal.test_spec 'Tests' do |ts|
       ts.source_files = swift_dir + 'Tests/{Interpreter,MetalDelegate}Tests.swift'
       ts.resources = [
-        tfl_dir + 'testdata/add.bin',
+        tfl_dir + 'testdata/multi_add.bin',
-        tfl_dir + 'testdata/add_quantized.bin',
       ]
     end
   end

tensorflow/lite/experimental/swift/Tests/MetalDelegateTests.swift

@@ -34,18 +34,26 @@ class MetalDelegateTests: XCTestCase {
   }
 
   func testInitInterpreterWithDelegate() throws {
+    // If metal device is not available, skip.
+    if MTLCreateSystemDefaultDevice() == nil {
+      return
+    }
     let metalDelegate = MetalDelegate()
-    let interpreter = try Interpreter(modelPath: AddQuantizedModel.path, delegates: [metalDelegate])
+    let interpreter = try Interpreter(modelPath: MultiAddModel.path, delegates: [metalDelegate])
     XCTAssertEqual(interpreter.delegates?.count, 1)
     XCTAssertNil(interpreter.options)
   }
 
   func testInitInterpreterWithOptionsAndDelegate() throws {
+    // If metal device is not available, skip.
+    if MTLCreateSystemDefaultDevice() == nil {
+      return
+    }
     var options = Interpreter.Options()
     options.threadCount = 1
     let metalDelegate = MetalDelegate()
     let interpreter = try Interpreter(
-      modelPath: AddQuantizedModel.path,
+      modelPath: MultiAddModel.path,
       options: options,
       delegates: [metalDelegate]
     )
@@ -91,3 +99,16 @@ class MetalDelegateOptionsTests: XCTestCase {
     XCTAssertNotEqual(options1, options2)
   }
 }
+
+
+/// Values for the `multi_add.bin` model.
+enum MultiAddModel {
+  static let info = (name: "multi_add", extension: "bin")
+
+  static var path: String = {
+    let bundle = Bundle(for: MetalDelegateTests.self)
+    guard let path = bundle.path(forResource: info.name, ofType: info.extension) else { return "" }
+    return path
+  }()
+}
+

tensorflow/lite/g3doc/performance/gpu.md

@@ -12,11 +12,9 @@ resulting in lower latency. In the best scenario, inference on the GPU may now
 run fast enough for previously not available real-time applications.
 
 Unlike CPUs, GPUs compute with 16-bit or 32-bit floating point numbers and do
-not require quantization for optimal performance.
+not require quantization for optimal performance. The delegate does accept 8-bit
-
+quantized models, but the calculation will be performed in floating point
-**NOTE:** The delegate does accept 8-bit quantized models on Android. Support on
+numbers. Refer to the [advanced documentation](gpu_advanced.md) for details.
-iOS is experimental. Refer to the [advanced documentation](gpu_advanced.md) for
-details.
 
 Another benefit with GPU inference is its power efficiency. GPUs carry out the
 computations in a very efficient and optimized manner, so that they consume less

tensorflow/lite/g3doc/performance/gpu_advanced.md

@@ -325,7 +325,6 @@ Android APIs support quantized models by default. To disable, do the following:
 **C++ API**
 
 ```c++
-// NEW: Prepare custom options with feature enabled.
 TfLiteGpuDelegateOptionsV2 options = TfLiteGpuDelegateOptionsV2Default();
 options.experimental_flags = TFLITE_GPU_EXPERIMENTAL_FLAGS_NONE;
 
@@ -336,7 +335,6 @@ if (interpreter->ModifyGraphWithDelegate(delegate) != kTfLiteOk) return false;
 **Java API**
 
 ```java
-// NEW: Prepare GPU delegate with feature turned on.
 GpuDelegate delegate = new GpuDelegate(new GpuDelegate.Options().setQuantizedModelsAllowed(false));
 
 Interpreter.Options options = (new Interpreter.Options()).addDelegate(delegate);
@@ -344,27 +342,21 @@ Interpreter.Options options = (new Interpreter.Options()).addDelegate(delegate);
 
 #### iOS
 
-Support for quantized models on iOS APIs is experimental. To enable, do the
+iOD APIs support quantized models by default. To disable, do the following:
-following:
 
 **Swift API**
 
 ```swift
-// NEW: Prepare custom options with feature enabled.
 var options = MetalDelegate.Options()
-options.isQuantizationEnabled = true
+options.isQuantizationEnabled = false
 let delegate = MetalDelegate(options: options)
 ```
 
 **C API (also used for Objective-C)**
 
 ```c
-
+TFLGpuDelegateOptions options = TFLGpuDelegateOptionsDefault();
-// THIS:
+options.enable_quantization = false;
-// NEW: Prepare custom options with feature enabled.
-const TFLGpuDelegateOptions options = {
-  .enable_quantization = true,
-};
 
 auto* delegate = TFLGpuDelegateCreate(options);
 ```