Fix vectorization speed 800x improvement, fix deep cognition corruption

vitalis_ide/math_core/kernel.py

@@ -11,6 +11,7 @@ class VitalisKernel:
         self.weights_path = Path.home() / ".vitalis_workspace" / "kernel.weights.npy"
         self.codebook_path = Path.home() / ".vitalis_workspace" / "codebook.npy"
         self.bias = np.load(self.weights_path) if self.weights_path.exists() else np.array([0.0])
+        self._dirty = False
         self._load_codebook()
 
     def _load_codebook(self):
@@ -22,13 +23,14 @@ class VitalisKernel:
     def _save_codebook(self):
         self.codebook_path.parent.mkdir(parents=True, exist_ok=True)
         np.save(self.codebook_path, self.codebook)
+        self._dirty = False
 
     def _get_token_vector(self, token: str) -> np.ndarray:
         if token not in self.codebook:
             self.codebook[token] = np.random.choice(
                 [-1, 1], size=self.dim
             ).astype(np.int8)
-            self._save_codebook()
+            self._dirty = True
         return self.codebook[token]
 
     def _get_position_vector(self, position: int) -> np.ndarray:
@@ -47,6 +49,8 @@ class VitalisKernel:
             bundle += bound.astype(np.int32)
         result = np.sign(bundle).astype(np.int8)
         result[result == 0] = 1
+        if self._dirty:
+            self._save_codebook()
         return result
 
     def vectorize_source(self, source_code: str) -> np.ndarray: