coreml : update generated encoder/decoder interfaces

This commit updates the generated encoder/decoder interfaces for the
whisper model which is the result of running the
generate-coreml-interface.sh script.

Author: danbev

src/coreml/whisper-decoder-impl.h

@@ -11,36 +11,33 @@
 
 NS_ASSUME_NONNULL_BEGIN
 
-
 /// Model Prediction Input Type
-API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
+API_AVAILABLE(macos(10.15), ios(13.0), watchos(6.0), tvos(13.0)) __attribute__((visibility("hidden")))
 @interface whisper_decoder_implInput : NSObject<MLFeatureProvider>
 
-/// token_data as 1 by 1 matrix of 32-bit integers
+/// token_data as 1 by 1 matrix of floats
 @property (readwrite, nonatomic, strong) MLMultiArray * token_data;
 
-/// audio_data as 1 × 384 × 1 × 1500 4-dimensional array of floats
+/// audio_data as 1 × 1500 × 384 3-dimensional array of floats
 @property (readwrite, nonatomic, strong) MLMultiArray * audio_data;
 - (instancetype)init NS_UNAVAILABLE;
 - (instancetype)initWithToken_data:(MLMultiArray *)token_data audio_data:(MLMultiArray *)audio_data NS_DESIGNATED_INITIALIZER;
 
 @end
 
-
 /// Model Prediction Output Type
-API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
+API_AVAILABLE(macos(10.15), ios(13.0), watchos(6.0), tvos(13.0)) __attribute__((visibility("hidden")))
 @interface whisper_decoder_implOutput : NSObject<MLFeatureProvider>
 
-/// var_1346 as multidimensional array of floats
-@property (readwrite, nonatomic, strong) MLMultiArray * var_1346;
+/// cast_76 as multidimensional array of floats
+@property (readwrite, nonatomic, strong) MLMultiArray * cast_76;
 - (instancetype)init NS_UNAVAILABLE;
-- (instancetype)initWithVar_1346:(MLMultiArray *)var_1346 NS_DESIGNATED_INITIALIZER;
+- (instancetype)initWithCast_76:(MLMultiArray *)cast_76 NS_DESIGNATED_INITIALIZER;
 
 @end
 
-
 /// Class for model loading and prediction
-API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
+API_AVAILABLE(macos(10.15), ios(13.0), watchos(6.0), tvos(13.0)) __attribute__((visibility("hidden")))
 @interface whisper_decoder_impl : NSObject
 @property (readonly, nonatomic, nullable) MLModel * model;
 
@@ -94,7 +91,7 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
     @param configuration The model configuration
     @param handler When the model load completes successfully or unsuccessfully, the completion handler is invoked with a valid whisper_decoder_impl instance or NSError object.
 */
-+ (void)loadWithConfiguration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_decoder_impl * _Nullable model, NSError * _Nullable error))handler;
++ (void)loadWithConfiguration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_decoder_impl * _Nullable model, NSError * _Nullable error))handler API_AVAILABLE(macos(11.0), ios(14.0), watchos(7.0), tvos(14.0)) __attribute__((visibility("hidden")));
 
 /**
     Construct whisper_decoder_impl instance asynchronously with URL of .mlmodelc directory and optional configuration.
@@ -105,7 +102,7 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
     @param configuration The model configuration
     @param handler When the model load completes successfully or unsuccessfully, the completion handler is invoked with a valid whisper_decoder_impl instance or NSError object.
 */
-+ (void)loadContentsOfURL:(NSURL *)modelURL configuration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_decoder_impl * _Nullable model, NSError * _Nullable error))handler;
++ (void)loadContentsOfURL:(NSURL *)modelURL configuration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_decoder_impl * _Nullable model, NSError * _Nullable error))handler API_AVAILABLE(macos(11.0), ios(14.0), watchos(7.0), tvos(14.0)) __attribute__((visibility("hidden")));
 
 /**
     Make a prediction using the standard interface
@@ -124,10 +121,25 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
 */
 - (nullable whisper_decoder_implOutput *)predictionFromFeatures:(whisper_decoder_implInput *)input options:(MLPredictionOptions *)options error:(NSError * _Nullable __autoreleasing * _Nullable)error;
 
+/**
+    Make an asynchronous prediction using the standard interface
+    @param input an instance of whisper_decoder_implInput to predict from
+    @param completionHandler a block that will be called upon completion of the prediction. error will be nil if no error occurred.
+*/
+- (void)predictionFromFeatures:(whisper_decoder_implInput *)input completionHandler:(void (^)(whisper_decoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler API_AVAILABLE(macos(14.0), ios(17.0), watchos(10.0), tvos(17.0)) __attribute__((visibility("hidden")));
+
+/**
+    Make an asynchronous prediction using the standard interface
+    @param input an instance of whisper_decoder_implInput to predict from
+    @param options prediction options
+    @param completionHandler a block that will be called upon completion of the prediction. error will be nil if no error occurred.
+*/
+- (void)predictionFromFeatures:(whisper_decoder_implInput *)input options:(MLPredictionOptions *)options completionHandler:(void (^)(whisper_decoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler API_AVAILABLE(macos(14.0), ios(17.0), watchos(10.0), tvos(17.0)) __attribute__((visibility("hidden")));
+
 /**
     Make a prediction using the convenience interface
-    @param token_data as 1 by 1 matrix of 32-bit integers:
-    @param audio_data as 1 × 384 × 1 × 1500 4-dimensional array of floats:
+    @param token_data 1 by 1 matrix of floats
+    @param audio_data 1 × 1500 × 384 3-dimensional array of floats
     @param error If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, pass in NULL.
     @return the prediction as whisper_decoder_implOutput
 */

src/coreml/whisper-decoder-impl.m

@@ -39,21 +39,21 @@ - (nullable MLFeatureValue *)featureValueForName:(NSString *)featureName {
 
 @implementation whisper_decoder_implOutput
 
-- (instancetype)initWithVar_1346:(MLMultiArray *)var_1346 {
+- (instancetype)initWithCast_76:(MLMultiArray *)cast_76 {
     self = [super init];
     if (self) {
-        _var_1346 = var_1346;
+        _cast_76 = cast_76;
     }
     return self;
 }
 
 - (NSSet<NSString *> *)featureNames {
-    return [NSSet setWithArray:@[@"var_1346"]];
+    return [NSSet setWithArray:@[@"cast_76"]];
 }
 
 - (nullable MLFeatureValue *)featureValueForName:(NSString *)featureName {
-    if ([featureName isEqualToString:@"var_1346"]) {
-        return [MLFeatureValue featureValueWithMultiArray:self.var_1346];
+    if ([featureName isEqualToString:@"cast_76"]) {
+        return [MLFeatureValue featureValueWithMultiArray:self.cast_76];
     }
     return nil;
 }
@@ -80,10 +80,13 @@ + (nullable NSURL *)URLOfModelInThisBundle {
     Such application may want to use `-[MLModel initWithContentsOfURL:configuration:error:]` and `+URLOfModelInThisBundle` to create a MLModel object to pass-in.
 */
 - (instancetype)initWithMLModel:(MLModel *)model {
+    if (model == nil) {
+        return nil;
+    }
     self = [super init];
-    if (!self) { return nil; }
-    _model = model;
-    if (_model == nil) { return nil; }
+    if (self != nil) {
+        _model = model;
+    }
     return self;
 }
 
@@ -177,7 +180,29 @@ - (nullable whisper_decoder_implOutput *)predictionFromFeatures:(whisper_decoder
 - (nullable whisper_decoder_implOutput *)predictionFromFeatures:(whisper_decoder_implInput *)input options:(MLPredictionOptions *)options error:(NSError * _Nullable __autoreleasing * _Nullable)error {
     id<MLFeatureProvider> outFeatures = [self.model predictionFromFeatures:input options:options error:error];
     if (!outFeatures) { return nil; }
-    return [[whisper_decoder_implOutput alloc] initWithVar_1346:(MLMultiArray *)[outFeatures featureValueForName:@"var_1346"].multiArrayValue];
+    return [[whisper_decoder_implOutput alloc] initWithCast_76:(MLMultiArray *)[outFeatures featureValueForName:@"cast_76"].multiArrayValue];
+}
+
+- (void)predictionFromFeatures:(whisper_decoder_implInput *)input completionHandler:(void (^)(whisper_decoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler {
+    [self.model predictionFromFeatures:input completionHandler:^(id<MLFeatureProvider> prediction, NSError *predictionError) {
+        if (prediction != nil) {
+            whisper_decoder_implOutput *output = [[whisper_decoder_implOutput alloc] initWithCast_76:(MLMultiArray *)[prediction featureValueForName:@"cast_76"].multiArrayValue];
+            completionHandler(output, predictionError);
+        } else {
+            completionHandler(nil, predictionError);
+        }
+    }];
+}
+
+- (void)predictionFromFeatures:(whisper_decoder_implInput *)input options:(MLPredictionOptions *)options completionHandler:(void (^)(whisper_decoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler {
+    [self.model predictionFromFeatures:input options:options completionHandler:^(id<MLFeatureProvider> prediction, NSError *predictionError) {
+        if (prediction != nil) {
+            whisper_decoder_implOutput *output = [[whisper_decoder_implOutput alloc] initWithCast_76:(MLMultiArray *)[prediction featureValueForName:@"cast_76"].multiArrayValue];
+            completionHandler(output, predictionError);
+        } else {
+            completionHandler(nil, predictionError);
+        }
+    }];
 }
 
 - (nullable whisper_decoder_implOutput *)predictionFromToken_data:(MLMultiArray *)token_data audio_data:(MLMultiArray *)audio_data error:(NSError * _Nullable __autoreleasing * _Nullable)error {
@@ -192,7 +217,7 @@ - (nullable whisper_decoder_implOutput *)predictionFromToken_data:(MLMultiArray
     NSMutableArray<whisper_decoder_implOutput*> *results = [NSMutableArray arrayWithCapacity:(NSUInteger)outBatch.count];
     for (NSInteger i = 0; i < outBatch.count; i++) {
         id<MLFeatureProvider> resultProvider = [outBatch featuresAtIndex:i];
-        whisper_decoder_implOutput * result = [[whisper_decoder_implOutput alloc] initWithVar_1346:(MLMultiArray *)[resultProvider featureValueForName:@"var_1346"].multiArrayValue];
+        whisper_decoder_implOutput * result = [[whisper_decoder_implOutput alloc] initWithCast_76:(MLMultiArray *)[resultProvider featureValueForName:@"cast_76"].multiArrayValue];
         [results addObject:result];
     }
     return results;

src/coreml/whisper-encoder-impl.h

@@ -11,9 +11,8 @@
 
 NS_ASSUME_NONNULL_BEGIN
 
-
 /// Model Prediction Input Type
-API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
+API_AVAILABLE(macos(10.15), ios(13.0), watchos(6.0), tvos(13.0)) __attribute__((visibility("hidden")))
 @interface whisper_encoder_implInput : NSObject<MLFeatureProvider>
 
 /// logmel_data as 1 × 80 × 3000 3-dimensional array of floats
@@ -23,9 +22,8 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
 
 @end
 
-
 /// Model Prediction Output Type
-API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
+API_AVAILABLE(macos(10.15), ios(13.0), watchos(6.0), tvos(13.0)) __attribute__((visibility("hidden")))
 @interface whisper_encoder_implOutput : NSObject<MLFeatureProvider>
 
 /// output as multidimensional array of floats
@@ -35,9 +33,8 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
 
 @end
 
-
 /// Class for model loading and prediction
-API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
+API_AVAILABLE(macos(10.15), ios(13.0), watchos(6.0), tvos(13.0)) __attribute__((visibility("hidden")))
 @interface whisper_encoder_impl : NSObject
 @property (readonly, nonatomic, nullable) MLModel * model;
 
@@ -91,7 +88,7 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
     @param configuration The model configuration
     @param handler When the model load completes successfully or unsuccessfully, the completion handler is invoked with a valid whisper_encoder_impl instance or NSError object.
 */
-+ (void)loadWithConfiguration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_encoder_impl * _Nullable model, NSError * _Nullable error))handler;
++ (void)loadWithConfiguration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_encoder_impl * _Nullable model, NSError * _Nullable error))handler API_AVAILABLE(macos(11.0), ios(14.0), watchos(7.0), tvos(14.0)) __attribute__((visibility("hidden")));
 
 /**
     Construct whisper_encoder_impl instance asynchronously with URL of .mlmodelc directory and optional configuration.
@@ -102,7 +99,7 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
     @param configuration The model configuration
     @param handler When the model load completes successfully or unsuccessfully, the completion handler is invoked with a valid whisper_encoder_impl instance or NSError object.
 */
-+ (void)loadContentsOfURL:(NSURL *)modelURL configuration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_encoder_impl * _Nullable model, NSError * _Nullable error))handler;
++ (void)loadContentsOfURL:(NSURL *)modelURL configuration:(MLModelConfiguration *)configuration completionHandler:(void (^)(whisper_encoder_impl * _Nullable model, NSError * _Nullable error))handler API_AVAILABLE(macos(11.0), ios(14.0), watchos(7.0), tvos(14.0)) __attribute__((visibility("hidden")));
 
 /**
     Make a prediction using the standard interface
@@ -121,9 +118,24 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
 */
 - (nullable whisper_encoder_implOutput *)predictionFromFeatures:(whisper_encoder_implInput *)input options:(MLPredictionOptions *)options error:(NSError * _Nullable __autoreleasing * _Nullable)error;
 
+/**
+    Make an asynchronous prediction using the standard interface
+    @param input an instance of whisper_encoder_implInput to predict from
+    @param completionHandler a block that will be called upon completion of the prediction. error will be nil if no error occurred.
+*/
+- (void)predictionFromFeatures:(whisper_encoder_implInput *)input completionHandler:(void (^)(whisper_encoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler API_AVAILABLE(macos(14.0), ios(17.0), watchos(10.0), tvos(17.0)) __attribute__((visibility("hidden")));
+
+/**
+    Make an asynchronous prediction using the standard interface
+    @param input an instance of whisper_encoder_implInput to predict from
+    @param options prediction options
+    @param completionHandler a block that will be called upon completion of the prediction. error will be nil if no error occurred.
+*/
+- (void)predictionFromFeatures:(whisper_encoder_implInput *)input options:(MLPredictionOptions *)options completionHandler:(void (^)(whisper_encoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler API_AVAILABLE(macos(14.0), ios(17.0), watchos(10.0), tvos(17.0)) __attribute__((visibility("hidden")));
+
 /**
     Make a prediction using the convenience interface
-    @param logmel_data as 1 × n_mel × 3000 3-dimensional array of floats:
+    @param logmel_data 1 × 80 × 3000 3-dimensional array of floats
     @param error If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, pass in NULL.
     @return the prediction as whisper_encoder_implOutput
 */

src/coreml/whisper-encoder-impl.m

@@ -76,10 +76,13 @@ + (nullable NSURL *)URLOfModelInThisBundle {
     Such application may want to use `-[MLModel initWithContentsOfURL:configuration:error:]` and `+URLOfModelInThisBundle` to create a MLModel object to pass-in.
 */
 - (instancetype)initWithMLModel:(MLModel *)model {
+    if (model == nil) {
+        return nil;
+    }
     self = [super init];
-    if (!self) { return nil; }
-    _model = model;
-    if (_model == nil) { return nil; }
+    if (self != nil) {
+        _model = model;
+    }
     return self;
 }
 
@@ -176,6 +179,28 @@ - (nullable whisper_encoder_implOutput *)predictionFromFeatures:(whisper_encoder
     return [[whisper_encoder_implOutput alloc] initWithOutput:(MLMultiArray *)[outFeatures featureValueForName:@"output"].multiArrayValue];
 }
 
+- (void)predictionFromFeatures:(whisper_encoder_implInput *)input completionHandler:(void (^)(whisper_encoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler {
+    [self.model predictionFromFeatures:input completionHandler:^(id<MLFeatureProvider> prediction, NSError *predictionError) {
+        if (prediction != nil) {
+            whisper_encoder_implOutput *output = [[whisper_encoder_implOutput alloc] initWithOutput:(MLMultiArray *)[prediction featureValueForName:@"output"].multiArrayValue];
+            completionHandler(output, predictionError);
+        } else {
+            completionHandler(nil, predictionError);
+        }
+    }];
+}
+
+- (void)predictionFromFeatures:(whisper_encoder_implInput *)input options:(MLPredictionOptions *)options completionHandler:(void (^)(whisper_encoder_implOutput * _Nullable output, NSError * _Nullable error))completionHandler {
+    [self.model predictionFromFeatures:input options:options completionHandler:^(id<MLFeatureProvider> prediction, NSError *predictionError) {
+        if (prediction != nil) {
+            whisper_encoder_implOutput *output = [[whisper_encoder_implOutput alloc] initWithOutput:(MLMultiArray *)[prediction featureValueForName:@"output"].multiArrayValue];
+            completionHandler(output, predictionError);
+        } else {
+            completionHandler(nil, predictionError);
+        }
+    }];
+}
+
 - (nullable whisper_encoder_implOutput *)predictionFromLogmel_data:(MLMultiArray *)logmel_data error:(NSError * _Nullable __autoreleasing * _Nullable)error {
     whisper_encoder_implInput *input_ = [[whisper_encoder_implInput alloc] initWithLogmel_data:logmel_data];
     return [self predictionFromFeatures:input_ error:error];