Georgi Gerganov
2 years ago
parent
72af0f5697
commit
b0ac915265
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//
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// CoremlEncoder.m
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//
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// This file was automatically generated and should not be edited.
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//
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#if !__has_feature(objc_arc)
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#error This file must be compiled with automatic reference counting enabled (-fobjc-arc)
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#endif
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#import "whisper-encoder-impl.h"
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@implementation CoremlEncoderInput
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- (instancetype)initWithMelSegment:(MLMultiArray *)melSegment {
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self = [super init];
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if (self) {
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_melSegment = melSegment;
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}
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return self;
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}
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- (NSSet<NSString *> *)featureNames {
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return [NSSet setWithArray:@[@"melSegment"]];
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}
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- (nullable MLFeatureValue *)featureValueForName:(NSString *)featureName {
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if ([featureName isEqualToString:@"melSegment"]) {
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return [MLFeatureValue featureValueWithMultiArray:self.melSegment];
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}
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return nil;
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}
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@end
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@implementation CoremlEncoderOutput
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- (instancetype)initWithOutput:(MLMultiArray *)output {
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self = [super init];
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if (self) {
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_output = output;
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}
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return self;
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}
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- (NSSet<NSString *> *)featureNames {
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return [NSSet setWithArray:@[@"output"]];
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}
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- (nullable MLFeatureValue *)featureValueForName:(NSString *)featureName {
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if ([featureName isEqualToString:@"output"]) {
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return [MLFeatureValue featureValueWithMultiArray:self.output];
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}
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return nil;
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}
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@end
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@implementation CoremlEncoder
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/**
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URL of the underlying .mlmodelc directory.
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*/
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+ (nullable NSURL *)URLOfModelInThisBundle {
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NSString *assetPath = [[NSBundle bundleForClass:[self class]] pathForResource:@"CoremlEncoder" ofType:@"mlmodelc"];
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if (nil == assetPath) { os_log_error(OS_LOG_DEFAULT, "Could not load CoremlEncoder.mlmodelc in the bundle resource"); return nil; }
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return [NSURL fileURLWithPath:assetPath];
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}
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/**
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Initialize CoremlEncoder instance from an existing MLModel object.
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Usually the application does not use this initializer unless it makes a subclass of CoremlEncoder.
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Such application may want to use `-[MLModel initWithContentsOfURL:configuration:error:]` and `+URLOfModelInThisBundle` to create a MLModel object to pass-in.
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*/
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- (instancetype)initWithMLModel:(MLModel *)model {
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self = [super init];
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if (!self) { return nil; }
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_model = model;
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if (_model == nil) { return nil; }
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return self;
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}
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/**
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Initialize CoremlEncoder instance with the model in this bundle.
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*/
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- (nullable instancetype)init {
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return [self initWithContentsOfURL:(NSURL * _Nonnull)self.class.URLOfModelInThisBundle error:nil];
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}
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/**
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Initialize CoremlEncoder instance with the model in this bundle.
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@param configuration The model configuration object
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@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.
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*/
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- (nullable instancetype)initWithConfiguration:(MLModelConfiguration *)configuration error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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return [self initWithContentsOfURL:(NSURL * _Nonnull)self.class.URLOfModelInThisBundle configuration:configuration error:error];
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}
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/**
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Initialize CoremlEncoder instance from the model URL.
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@param modelURL URL to the .mlmodelc directory for CoremlEncoder.
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@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.
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*/
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- (nullable instancetype)initWithContentsOfURL:(NSURL *)modelURL error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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MLModel *model = [MLModel modelWithContentsOfURL:modelURL error:error];
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if (model == nil) { return nil; }
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return [self initWithMLModel:model];
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}
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/**
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Initialize CoremlEncoder instance from the model URL.
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@param modelURL URL to the .mlmodelc directory for CoremlEncoder.
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@param configuration The model configuration object
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@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.
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*/
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- (nullable instancetype)initWithContentsOfURL:(NSURL *)modelURL configuration:(MLModelConfiguration *)configuration error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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MLModel *model = [MLModel modelWithContentsOfURL:modelURL configuration:configuration error:error];
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if (model == nil) { return nil; }
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return [self initWithMLModel:model];
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}
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/**
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Construct CoremlEncoder instance asynchronously with configuration.
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Model loading may take time when the model content is not immediately available (e.g. encrypted model). Use this factory method especially when the caller is on the main thread.
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@param configuration The model configuration
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@param handler When the model load completes successfully or unsuccessfully, the completion handler is invoked with a valid CoremlEncoder instance or NSError object.
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*/
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+ (void)loadWithConfiguration:(MLModelConfiguration *)configuration completionHandler:(void (^)(CoremlEncoder * _Nullable model, NSError * _Nullable error))handler {
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[self loadContentsOfURL:(NSURL * _Nonnull)[self URLOfModelInThisBundle]
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configuration:configuration
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completionHandler:handler];
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}
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/**
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Construct CoremlEncoder instance asynchronously with URL of .mlmodelc directory and optional configuration.
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Model loading may take time when the model content is not immediately available (e.g. encrypted model). Use this factory method especially when the caller is on the main thread.
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@param modelURL The model URL.
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@param configuration The model configuration
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@param handler When the model load completes successfully or unsuccessfully, the completion handler is invoked with a valid CoremlEncoder instance or NSError object.
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*/
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+ (void)loadContentsOfURL:(NSURL *)modelURL configuration:(MLModelConfiguration *)configuration completionHandler:(void (^)(CoremlEncoder * _Nullable model, NSError * _Nullable error))handler {
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[MLModel loadContentsOfURL:modelURL
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configuration:configuration
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completionHandler:^(MLModel *model, NSError *error) {
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if (model != nil) {
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CoremlEncoder *typedModel = [[CoremlEncoder alloc] initWithMLModel:model];
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handler(typedModel, nil);
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} else {
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handler(nil, error);
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}
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}];
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}
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- (nullable CoremlEncoderOutput *)predictionFromFeatures:(CoremlEncoderInput *)input error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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return [self predictionFromFeatures:input options:[[MLPredictionOptions alloc] init] error:error];
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}
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- (nullable CoremlEncoderOutput *)predictionFromFeatures:(CoremlEncoderInput *)input options:(MLPredictionOptions *)options error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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id<MLFeatureProvider> outFeatures = [self.model predictionFromFeatures:input options:options error:error];
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if (!outFeatures) { return nil; }
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return [[CoremlEncoderOutput alloc] initWithOutput:(MLMultiArray *)[outFeatures featureValueForName:@"output"].multiArrayValue];
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}
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- (nullable CoremlEncoderOutput *)predictionFromMelSegment:(MLMultiArray *)melSegment error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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CoremlEncoderInput *input_ = [[CoremlEncoderInput alloc] initWithMelSegment:melSegment];
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return [self predictionFromFeatures:input_ error:error];
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}
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- (nullable NSArray<CoremlEncoderOutput *> *)predictionsFromInputs:(NSArray<CoremlEncoderInput*> *)inputArray options:(MLPredictionOptions *)options error:(NSError * _Nullable __autoreleasing * _Nullable)error {
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id<MLBatchProvider> inBatch = [[MLArrayBatchProvider alloc] initWithFeatureProviderArray:inputArray];
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id<MLBatchProvider> outBatch = [self.model predictionsFromBatch:inBatch options:options error:error];
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if (!outBatch) { return nil; }
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NSMutableArray<CoremlEncoderOutput*> *results = [NSMutableArray arrayWithCapacity:(NSUInteger)outBatch.count];
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for (NSInteger i = 0; i < outBatch.count; i++) {
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id<MLFeatureProvider> resultProvider = [outBatch featuresAtIndex:i];
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CoremlEncoderOutput * result = [[CoremlEncoderOutput alloc] initWithOutput:(MLMultiArray *)[resultProvider featureValueForName:@"output"].multiArrayValue];
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[results addObject:result];
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}
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return results;
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}
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@end
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@ -0,0 +1,22 @@
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// Wrapper of the Core ML Whisper Encoder model
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//
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// Code is derived from the work of Github user @wangchou
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// ref: https://github.com/wangchou/callCoreMLFromCpp
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#if __cplusplus
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extern "C" {
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#endif
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struct whisper_coreml_context;
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struct whisper_coreml_context * whisper_coreml_init(const char * path_model);
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void whisper_coreml_free(struct whisper_coreml_context * ctx);
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void whisper_coreml_encode(
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const whisper_coreml_context * ctx,
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float * mel,
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float * out);
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#if __cplusplus
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}
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#endif
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@ -0,0 +1,61 @@
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#import "coreml/whisper-encoder.h"
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#import "coreml/whisper-encoder-impl.h"
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#import <CoreML/CoreML.h>
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#include <stdlib.h>
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#if __cplusplus
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extern "C" {
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#endif
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struct whisper_coreml_context {
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const void * data;
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};
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struct whisper_coreml_context * whisper_coreml_init(const char * path_model) {
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NSString * path_model_str = [[NSString alloc] initWithUTF8String:path_model];
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NSURL * url_model = [NSURL fileURLWithPath: path_model_str];
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const void * data = CFBridgingRetain([[CoremlEncoder alloc] initWithContentsOfURL:url_model error:nil]);
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if (data == NULL) {
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return NULL;
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}
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whisper_coreml_context * ctx = new whisper_coreml_context;
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ctx->data = data;
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return ctx;
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}
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void whisper_coreml_free(struct whisper_coreml_context * ctx) {
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CFRelease(ctx->data);
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delete ctx;
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}
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void whisper_coreml_encode(
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const whisper_coreml_context * ctx,
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float * mel,
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float * out) {
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MLMultiArray * inMultiArray = [
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[MLMultiArray alloc] initWithDataPointer: mel
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shape: @[@1, @80, @3000]
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dataType: MLMultiArrayDataTypeFloat32
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strides: @[@(240000), @(3000), @1]
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deallocator: nil
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error: nil
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];
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CoremlEncoderOutput * outCoreML = [(__bridge id) ctx->data predictionFromMelSegment:inMultiArray error:nil];
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MLMultiArray * outMA = outCoreML.output;
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memcpy(out, outMA.dataPointer, outMA.count * sizeof(float));
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}
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#if __cplusplus
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}
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#endif
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@ -0,0 +1,82 @@
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#!/bin/bash
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# This script downloads Whisper model files that have already been converted to Core ML format.
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# This way you don't have to convert them yourself.
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src="https://huggingface.co/datasets/ggerganov/whisper.cpp-coreml"
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pfx="resolve/main/ggml"
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# get the path of this script
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function get_script_path() {
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if [ -x "$(command -v realpath)" ]; then
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echo "$(dirname $(realpath $0))"
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else
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local ret="$(cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P)"
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echo "$ret"
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fi
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}
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models_path="$(get_script_path)"
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# Whisper models
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models=( "tiny.en" "tiny" "base.en" "base" "small.en" "small" "medium.en" "medium" "large-v1" "large" )
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# list available models
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function list_models {
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printf "\n"
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printf " Available models:"
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for model in "${models[@]}"; do
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printf " $model"
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done
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printf "\n\n"
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}
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if [ "$#" -ne 1 ]; then
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printf "Usage: $0 <model>\n"
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list_models
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exit 1
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fi
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model=$1
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if [[ ! " ${models[@]} " =~ " ${model} " ]]; then
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printf "Invalid model: $model\n"
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list_models
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exit 1
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fi
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# download Core ML model
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printf "Downloading Core ML model $model from '$src' ...\n"
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cd $models_path
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if [ -f "ggml-$model.mlmodel" ]; then
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printf "Model $model already exists. Skipping download.\n"
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exit 0
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fi
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if [ -x "$(command -v wget)" ]; then
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wget --quiet --show-progress -O ggml-$model.mlmodel $src/$pfx-$model.mlmodel
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elif [ -x "$(command -v curl)" ]; then
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curl -L --output ggml-$model.mlmodel $src/$pfx-$model.mlmodel
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else
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printf "Either wget or curl is required to download models.\n"
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exit 1
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fi
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if [ $? -ne 0 ]; then
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printf "Failed to download Core ML model $model \n"
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printf "Please try again later or download the original Whisper model files and convert them yourself.\n"
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exit 1
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fi
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printf "Done! Model '$model' saved in 'models/ggml-$model.mlmodel'\n"
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printf "Run the following command to compile it:\n\n"
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printf " $ xcrun coremlc compile ./models/ggml-$model.mlmodel ./models\n\n"
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printf "You can now use it like this:\n\n"
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printf " $ ./main -m models/ggml-$model.bin -f samples/jfk.wav\n"
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printf "\n"
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