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CodeDecoder.mlmodelc/analytics/coremldata.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f73b5cb1ea58da1354e9693a58de02d8313261cd34868b6b5bac0cf4830f091c
+oid sha256:d52078ac1b879b055032ae3266b7cbd6a48a969c875c0f9835318feec20c18f4
 size 243

CodeDecoder.mlmodelc/coremldata.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ae57abaa76c7566ec6ec30e316d1408fa75e1af208d630a552d0d66b4a260f68
+oid sha256:83a6da5ed37a7b16fd371db634a76997e0320764acd1d748c5acf11f62211751
 size 642

CodeDecoder.mlmodelc/metadata.json

@@ -88,7 +88,7 @@
       "name" : "MLModelType_mlProgram"
     },
     "userDefinedMetadata" : {
-      "com.github.apple.coremltools.conversion_date" : "2026-03-30",
+      "com.github.apple.coremltools.conversion_date" : "2026-04-03",
       "com.github.apple.coremltools.source" : "torch==2.10.0",
       "com.github.apple.coremltools.version" : "9.0",
       "com.github.apple.coremltools.source_dialect" : "TorchScript"
@@ -155,7 +155,7 @@
         "type" : "MultiArray"
       }
     ],
-    "generatedClassName" : "CodeDecoder",
+    "generatedClassName" : "CodeDecoder_fixed",
     "method" : "predict"
   }
 ]

CodeDecoder.mlmodelc/model.mil

@@ -5236,23 +5236,23 @@ program(1.3)
             tensor<fp16, [1, 1, 1024]> input_cast_fp16 = mul(x = var_11363_cast_fp16, y = var_11366_cast_fp16)[name = string("input_cast_fp16")];
             tensor<fp16, [3072, 1024]> codec_head_weight_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor<uint8, [3072, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(440678400))), lut = tensor<fp16, [1, 1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(443824192))))[name = string("codec_head_weight_to_fp16_palettized")];
             tensor<fp16, [1, 1, 3072]> logits = linear(bias = linear_4_bias_0_to_fp16, weight = codec_head_weight_to_fp16_palettized, x = input_cast_fp16)[name = string("linear_196_cast_fp16")];
-            tensor<int32, [1]> var_11372_axes_0 = const()[name = string("op_11372_axes_0"), val = tensor<int32, [1]>([0])];
-            tensor<fp16, [1, 1024]> var_11372_cast_fp16 = squeeze(axes = var_11372_axes_0, x = input_cast_fp16)[name = string("op_11372_cast_fp16")];
-            tensor<int32, [1]> var_11374_axes_0 = const()[name = string("op_11374_axes_0"), val = tensor<int32, [1]>([-1])];
-            tensor<fp16, [1, 1024, 1]> var_11374_cast_fp16 = expand_dims(axes = var_11374_axes_0, x = var_11372_cast_fp16)[name = string("op_11374_cast_fp16")];
-            tensor<int32, [1]> var_11376_axes_0 = const()[name = string("op_11376_axes_0"), val = tensor<int32, [1]>([-1])];
-            tensor<fp16, [1, 1024, 1, 1]> hidden_states = expand_dims(axes = var_11376_axes_0, x = var_11374_cast_fp16)[name = string("op_11376_cast_fp16")];
-            int32 var_11378 = const()[name = string("op_11378"), val = int32(1)];
-            bool new_kv_k_interleave_0 = const()[name = string("new_kv_k_interleave_0"), val = bool(false)];
-            tensor<fp16, [1, 28672, 1, 1]> new_kv_k_cast_fp16 = concat(axis = var_11378, interleave = new_kv_k_interleave_0, values = (nk_1_cast_fp16, nk_3_cast_fp16, nk_5_cast_fp16, nk_7_cast_fp16, nk_9_cast_fp16, nk_11_cast_fp16, nk_13_cast_fp16, nk_15_cast_fp16, nk_17_cast_fp16, nk_19_cast_fp16, nk_21_cast_fp16, nk_23_cast_fp16, nk_25_cast_fp16, nk_27_cast_fp16, nk_29_cast_fp16, nk_31_cast_fp16, nk_33_cast_fp16, nk_35_cast_fp16, nk_37_cast_fp16, nk_39_cast_fp16, nk_41_cast_fp16, nk_43_cast_fp16, nk_45_cast_fp16, nk_47_cast_fp16, nk_49_cast_fp16, nk_51_cast_fp16, nk_53_cast_fp16, nk_cast_fp16))[name = string("new_kv_k_cast_fp16")];
+            tensor<int32, [1]> var_11375_axes_0 = const()[name = string("op_11375_axes_0"), val = tensor<int32, [1]>([0])];
+            tensor<fp16, [1, 1024]> var_11375_cast_fp16 = squeeze(axes = var_11375_axes_0, x = hidden_states_449_cast_fp16)[name = string("op_11375_cast_fp16")];
+            tensor<int32, [1]> var_11377_axes_0 = const()[name = string("op_11377_axes_0"), val = tensor<int32, [1]>([-1])];
+            tensor<fp16, [1, 1024, 1]> var_11377_cast_fp16 = expand_dims(axes = var_11377_axes_0, x = var_11375_cast_fp16)[name = string("op_11377_cast_fp16")];
+            tensor<int32, [1]> var_11379_axes_0 = const()[name = string("op_11379_axes_0"), val = tensor<int32, [1]>([-1])];
+            tensor<fp16, [1, 1024, 1, 1]> hidden_states = expand_dims(axes = var_11379_axes_0, x = var_11377_cast_fp16)[name = string("op_11379_cast_fp16")];
             int32 var_11381 = const()[name = string("op_11381"), val = int32(1)];
+            bool new_kv_k_interleave_0 = const()[name = string("new_kv_k_interleave_0"), val = bool(false)];
+            tensor<fp16, [1, 28672, 1, 1]> new_kv_k_cast_fp16 = concat(axis = var_11381, interleave = new_kv_k_interleave_0, values = (nk_1_cast_fp16, nk_3_cast_fp16, nk_5_cast_fp16, nk_7_cast_fp16, nk_9_cast_fp16, nk_11_cast_fp16, nk_13_cast_fp16, nk_15_cast_fp16, nk_17_cast_fp16, nk_19_cast_fp16, nk_21_cast_fp16, nk_23_cast_fp16, nk_25_cast_fp16, nk_27_cast_fp16, nk_29_cast_fp16, nk_31_cast_fp16, nk_33_cast_fp16, nk_35_cast_fp16, nk_37_cast_fp16, nk_39_cast_fp16, nk_41_cast_fp16, nk_43_cast_fp16, nk_45_cast_fp16, nk_47_cast_fp16, nk_49_cast_fp16, nk_51_cast_fp16, nk_53_cast_fp16, nk_cast_fp16))[name = string("new_kv_k_cast_fp16")];
+            int32 var_11384 = const()[name = string("op_11384"), val = int32(1)];
             bool new_kv_v_interleave_0 = const()[name = string("new_kv_v_interleave_0"), val = bool(false)];
-            tensor<fp16, [1, 28672, 1, 1]> new_kv_v_cast_fp16 = concat(axis = var_11381, interleave = new_kv_v_interleave_0, values = (nv_1_cast_fp16, nv_3_cast_fp16, nv_5_cast_fp16, nv_7_cast_fp16, nv_9_cast_fp16, nv_11_cast_fp16, nv_13_cast_fp16, nv_15_cast_fp16, nv_17_cast_fp16, nv_19_cast_fp16, nv_21_cast_fp16, nv_23_cast_fp16, nv_25_cast_fp16, nv_27_cast_fp16, nv_29_cast_fp16, nv_31_cast_fp16, nv_33_cast_fp16, nv_35_cast_fp16, nv_37_cast_fp16, nv_39_cast_fp16, nv_41_cast_fp16, nv_43_cast_fp16, nv_45_cast_fp16, nv_47_cast_fp16, nv_49_cast_fp16, nv_51_cast_fp16, nv_53_cast_fp16, nv_cast_fp16))[name = string("new_kv_v_cast_fp16")];
-            tensor<fp16, [1, 28672, 1, 256]> var_11386_cast_fp16 = mul(x = key_cache, y = var_1203_cast_fp16)[name = string("op_11386_cast_fp16")];
-            tensor<fp16, [1, 28672, 1, 256]> var_11387_cast_fp16 = mul(x = new_kv_k_cast_fp16, y = update_mask_cast_fp16)[name = string("op_11387_cast_fp16")];
-            tensor<fp16, [1, 28672, 1, 256]> new_key_cache = add(x = var_11386_cast_fp16, y = var_11387_cast_fp16)[name = string("op_11389_cast_fp16")];
-            tensor<fp16, [1, 28672, 1, 256]> var_11393_cast_fp16 = mul(x = value_cache, y = var_1203_cast_fp16)[name = string("op_11393_cast_fp16")];
-            tensor<fp16, [1, 28672, 1, 256]> var_11394_cast_fp16 = mul(x = new_kv_v_cast_fp16, y = update_mask_cast_fp16)[name = string("op_11394_cast_fp16")];
-            tensor<fp16, [1, 28672, 1, 256]> new_value_cache = add(x = var_11393_cast_fp16, y = var_11394_cast_fp16)[name = string("op_11396_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 1]> new_kv_v_cast_fp16 = concat(axis = var_11384, interleave = new_kv_v_interleave_0, values = (nv_1_cast_fp16, nv_3_cast_fp16, nv_5_cast_fp16, nv_7_cast_fp16, nv_9_cast_fp16, nv_11_cast_fp16, nv_13_cast_fp16, nv_15_cast_fp16, nv_17_cast_fp16, nv_19_cast_fp16, nv_21_cast_fp16, nv_23_cast_fp16, nv_25_cast_fp16, nv_27_cast_fp16, nv_29_cast_fp16, nv_31_cast_fp16, nv_33_cast_fp16, nv_35_cast_fp16, nv_37_cast_fp16, nv_39_cast_fp16, nv_41_cast_fp16, nv_43_cast_fp16, nv_45_cast_fp16, nv_47_cast_fp16, nv_49_cast_fp16, nv_51_cast_fp16, nv_53_cast_fp16, nv_cast_fp16))[name = string("new_kv_v_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 256]> var_11389_cast_fp16 = mul(x = key_cache, y = var_1203_cast_fp16)[name = string("op_11389_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 256]> var_11390_cast_fp16 = mul(x = new_kv_k_cast_fp16, y = update_mask_cast_fp16)[name = string("op_11390_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 256]> new_key_cache = add(x = var_11389_cast_fp16, y = var_11390_cast_fp16)[name = string("op_11392_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 256]> var_11396_cast_fp16 = mul(x = value_cache, y = var_1203_cast_fp16)[name = string("op_11396_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 256]> var_11397_cast_fp16 = mul(x = new_kv_v_cast_fp16, y = update_mask_cast_fp16)[name = string("op_11397_cast_fp16")];
+            tensor<fp16, [1, 28672, 1, 256]> new_value_cache = add(x = var_11396_cast_fp16, y = var_11397_cast_fp16)[name = string("op_11399_cast_fp16")];
         } -> (logits, hidden_states, new_key_cache, new_value_cache);
 }