coreml : attempt to fix ANE-optimized models

coreml/whisper-decoder-impl.h

@@ -31,10 +31,10 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
 API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((visibility("hidden")))
 @interface whisper_decoder_implOutput : NSObject<MLFeatureProvider>
 
-/// var_1346 as multidimensional array of floats
+/// var_1195 as multidimensional array of floats
-@property (readwrite, nonatomic, strong) MLMultiArray * var_1346;
+@property (readwrite, nonatomic, strong) MLMultiArray * var_1195;
 - (instancetype)init NS_UNAVAILABLE;
-- (instancetype)initWithVar_1346:(MLMultiArray *)var_1346 NS_DESIGNATED_INITIALIZER;
+- (instancetype)initWithVar_1195:(MLMultiArray *)var_1195 NS_DESIGNATED_INITIALIZER;
 
 @end
 

coreml/whisper-decoder-impl.m

@@ -39,21 +39,21 @@
 
 @implementation whisper_decoder_implOutput
 
-- (instancetype)initWithVar_1346:(MLMultiArray *)var_1346 {
+- (instancetype)initWithVar_1195:(MLMultiArray *)var_1195 {
     self = [super init];
     if (self) {
-        _var_1346 = var_1346;
+        _var_1195 = var_1195;
     }
     return self;
 }
 
 - (NSSet<NSString *> *)featureNames {
-    return [NSSet setWithArray:@[@"var_1346"]];
+    return [NSSet setWithArray:@[@"var_1195"]];
 }
 
 - (nullable MLFeatureValue *)featureValueForName:(NSString *)featureName {
-    if ([featureName isEqualToString:@"var_1346"]) {
+    if ([featureName isEqualToString:@"var_1195"]) {
-        return [MLFeatureValue featureValueWithMultiArray:self.var_1346];
+        return [MLFeatureValue featureValueWithMultiArray:self.var_1195];
     }
     return nil;
 }
@@ -177,7 +177,7 @@
 - (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] initWithVar_1195:(MLMultiArray *)[outFeatures featureValueForName:@"var_1195"].multiArrayValue];
 }
 
 - (nullable whisper_decoder_implOutput *)predictionFromToken_data:(MLMultiArray *)token_data audio_data:(MLMultiArray *)audio_data error:(NSError * _Nullable __autoreleasing * _Nullable)error {
@@ -192,7 +192,7 @@
     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] initWithVar_1195:(MLMultiArray *)[resultProvider featureValueForName:@"var_1195"].multiArrayValue];
         [results addObject:result];
     }
     return results;

models/convert-whisper-to-coreml.py

@@ -7,7 +7,6 @@ from torch import Tensor
 from torch import nn
 from typing import Dict
 from typing import Optional
-from ane_transformers.reference.layer_norm import LayerNormANE as LayerNormANEBase
 from coremltools.models.neural_network.quantization_utils import quantize_weights
 from whisper.model import Whisper, AudioEncoder, TextDecoder, ResidualAttentionBlock, MultiHeadAttention, ModelDimensions
 from whisper import load_model
@@ -32,12 +31,12 @@ def correct_for_bias_scale_order_inversion(state_dict, prefix, local_metadata,
     state_dict[prefix + 'bias'] = state_dict[prefix + 'bias'] / state_dict[prefix + 'weight']
     return state_dict
 
-class LayerNormANE(LayerNormANEBase):
+class LayerNorm(nn.LayerNorm):
-
+    def forward(self, x: Tensor) -> Tensor:
-    def __init__(self, *args, **kwargs):
+        x = x.transpose(1,3)
-        super().__init__(*args, **kwargs)
+        x = super().forward(x)
-        self._register_load_state_dict_pre_hook(
+        x = x.transpose(1,3)
-            correct_for_bias_scale_order_inversion)
+        return x
 
 class MultiHeadAttentionANE(MultiHeadAttention):
     def __init__(self, n_state: int, n_head: int):
@@ -104,9 +103,9 @@ class ResidualAttentionBlockANE(ResidualAttentionBlock):
     def __init__(self, n_state: int, n_head: int, cross_attention: bool = False):
         super().__init__(n_state, n_head, cross_attention)
         self.attn =  MultiHeadAttentionANE(n_state, n_head)
-        self.attn_ln = LayerNormANE(n_state)
+        self.attn_ln = LayerNorm(n_state)
         self.cross_attn =  MultiHeadAttentionANE(n_state, n_head) if cross_attention else None
-        self.cross_attn_ln =  LayerNormANE(n_state) if cross_attention else None
+        self.cross_attn_ln =  LayerNorm(n_state) if cross_attention else None
 
         n_mlp = n_state * 4
         self.mlp =  nn.Sequential(
@@ -114,7 +113,7 @@ class ResidualAttentionBlockANE(ResidualAttentionBlock):
             nn.GELU(),
             nn.Conv2d(n_mlp, n_state, kernel_size=1)
         )
-        self.mlp_ln = LayerNormANE(n_state)
+        self.mlp_ln = LayerNorm(n_state)
 
 
 class AudioEncoderANE(AudioEncoder):
@@ -124,7 +123,7 @@ class AudioEncoderANE(AudioEncoder):
         self.blocks = nn.ModuleList(
             [ResidualAttentionBlockANE(n_state, n_head) for _ in range(n_layer)]
         )
-        self.ln_post = LayerNormANE(n_state)
+        self.ln_post = LayerNorm(n_state)
 
     def forward(self, x: Tensor):
         """
@@ -168,7 +167,7 @@ class TextDecoderANE(TextDecoder):
         self.blocks= nn.ModuleList(
             [ResidualAttentionBlockANE(n_state, n_head, cross_attention=True) for _ in range(n_layer)]
         )
-        self.ln= LayerNormANE(n_state)
+        self.ln= LayerNorm(n_state)
 
     def forward(self, x: Tensor, xa: Tensor, kv_cache: Optional[dict] = None):
         """

models/generate-coreml-interface.sh

@@ -8,7 +8,7 @@
 wd=$(dirname "$0")
 cd "$wd/../"
 
-python3 models/convert-whisper-to-coreml.py --model tiny.en
+python3 models/convert-whisper-to-coreml.py --model tiny.en --optimize-ane True
 
 mv -v models/coreml-encoder-tiny.en.mlpackage models/whisper-encoder-impl.mlpackage
 xcrun coremlc generate models/whisper-encoder-impl.mlpackage coreml/

models/generate-coreml-model.sh

@@ -13,7 +13,7 @@ mname="$1"
 wd=$(dirname "$0")
 cd "$wd/../"
 
-python3 models/convert-whisper-to-coreml.py --model $mname --encoder-only True
+python3 models/convert-whisper-to-coreml.py --model $mname --encoder-only True --optimize-ane True
 
 xcrun coremlc compile models/coreml-encoder-${mname}.mlpackage models/
 rm -rf models/ggml-${mname}-encoder.mlmodelc