Improve model recompilation logic in CoreMLBackend

Changed the `model` property in `CoreMLBackend` from a constant to a variable to allow reassignment when recompiling the model.

- Updated the `safelyPredict` function to handle prediction failures more gracefully:
  - Reorganized the logic to include a loop that attempts compilation and prediction with both cached and recompilation strategies.
  - Introduced a new private method `compileAndPredict` to encapsulate the model compilation and prediction logic, improving code readability and maintainability.

- Enhanced the `KataGoModel` class by modifying the `compileBundleMLModel` and `compileMLModel` methods to accept a `mustCompile` parameter, allowing conditional recompilation of the model based on input flags.

- This change addresses issues where the model fails to produce valid predictions by ensuring a fresh compilation under specific circumstances, improving overall reliability in predicting with CoreML models.

cpp/neuralnet/coremlbackend.swift

@@ -32,7 +32,7 @@ public class CoreMLBackend {
         return "KataGoModel\(xLen)x\(yLen)fp\(precision)\(encoder)"
     }
 
-    let model: KataGoModel
+    var model: KataGoModel
     let xLen: Int
     let yLen: Int
     public let version: Int32
@@ -117,8 +117,8 @@ public class CoreMLBackend {
 
             let inputBatch = KataGoModelInputBatch(inputArray: inputArray)
             let options = MLPredictionOptions()
-            let outputBatch = safelyPredict(from: inputBatch, options: options)
 
+            let outputBatch = safelyPredict(from: inputBatch, options: options)!
             assert(outputBatch.count == batchSize)
 
             outputBatch.outputArray.enumerated().forEach { index, output in
@@ -152,17 +152,34 @@ public class CoreMLBackend {
     }
 
     func safelyPredict(from inputBatch: KataGoModelInputBatch,
-                       options: MLPredictionOptions) -> KataGoModelOutputBatch {
-        if let firstTry = try? model.prediction(from: inputBatch, options: options) {
-            return firstTry
-        } else if let secondTry = try? model.prediction(from: inputBatch, options: options) {
-            return secondTry
-        } else {
-            let mlmodel = KataGoModel.compileBundleMLModel(modelName: modelName, computeUnits: .cpuOnly)!
-            let model = KataGoModel(model: mlmodel)
-            let cpuTry = try! model.prediction(from: inputBatch, options: options)
-            return cpuTry
+                       options: MLPredictionOptions) -> KataGoModelOutputBatch? {
+        if let prediction = try? model.prediction(from: inputBatch, options: options) {
+            return prediction
         }
+
+        let computeUnits = model.model.configuration.computeUnits
+
+        for mustCompile in [false, true] {
+            if let prediction = compileAndPredict(with: computeUnits, from: inputBatch, options: options, mustCompile: mustCompile) {
+                return prediction
+            }
+        }
+
+        return nil
+    }
+
+    private func compileAndPredict(with computeUnits: MLComputeUnits,
+                                   from inputBatch: KataGoModelInputBatch,
+                                   options: MLPredictionOptions,
+                                   mustCompile: Bool) -> KataGoModelOutputBatch? {
+        if let mlmodel = KataGoModel.compileBundleMLModel(modelName: modelName, computeUnits: computeUnits, mustCompile: mustCompile) {
+            model = KataGoModel(model: mlmodel)
+            if let outputBatch = try? model.prediction(from: inputBatch, options: options) {
+                return outputBatch
+            }
+        }
+
+        return nil
     }
 }
 

cpp/neuralnet/coremlmodel.swift

@@ -104,7 +104,7 @@ class KataGoModel {
         return bundleModelURL
     }
 
-    class func compileBundleMLModel(modelName: String, computeUnits: MLComputeUnits) -> MLModel? {
+    class func compileBundleMLModel(modelName: String, computeUnits: MLComputeUnits, mustCompile: Bool = false) -> MLModel? {
         var mlmodel: MLModel?
 
         do {
@@ -114,7 +114,8 @@ class KataGoModel {
             // Compile MLModel
             mlmodel = try compileMLModel(modelName: modelName,
                                          modelURL: bundleModelURL,
-                                         computeUnits: computeUnits)
+                                         computeUnits: computeUnits,
+                                         mustCompile: mustCompile)
         } catch {
             printError("An error occurred: \(error)")
         }
@@ -247,14 +248,14 @@ class KataGoModel {
         return savedDigestURL
     }
 
-    class func compileMLModel(modelName: String, modelURL: URL, computeUnits: MLComputeUnits) throws -> MLModel {
+    class func compileMLModel(modelName: String, modelURL: URL, computeUnits: MLComputeUnits, mustCompile: Bool) throws -> MLModel {
         let permanentURL = try getMLModelCPermanentURL(modelName: modelName)
         let savedDigestURL = try getSavedDigestURL(modelName: modelName)
         let digest = try getDigest(modelURL: modelURL)
 
-        let shouldCompileModel = checkShouldCompileModel(permanentURL: permanentURL,
-                                                         savedDigestURL: savedDigestURL,
-                                                         digest: digest)
+        let shouldCompileModel = mustCompile || checkShouldCompileModel(permanentURL: permanentURL,
+                                                                        savedDigestURL: savedDigestURL,
+                                                                        digest: digest)
 
         if shouldCompileModel {
             try compileAndSaveModel(permanentURL: permanentURL,