refactor(embeddings): pre-allocate static tensors via as const array

Align the text/image embeddings tasks with the add-task-pipeline skill (and
every other task): allocate the static output tensor in a `[...] as const`
array, destructure it, and dispose via `tensors.forEach`.

Author: msluszniak

packages/react-native-executorch/src/extensions/cv/tasks/imageEmbeddings.ts

@@ -65,12 +65,13 @@ export async function createImageEmbeddings(
   const inpShape = meta.inputTensorMeta[0]!.shape;
   const outShape = meta.outputTensorMeta[0]!.shape;
 
-  const tEmbedding = tensor('float32', outShape);
+  const tensors = [tensor('float32', outShape)] as const;
+  const [tEmbedding] = tensors;
   const preprocessor = createImagePreprocessor(opts, inpShape);
 
   const dispose = () => {
     preprocessor.dispose();
-    tEmbedding.dispose();
+    tensors.forEach((t) => t.dispose());
     model.dispose();
   };
 

packages/react-native-executorch/src/extensions/nlp/tasks/textEmbeddings.ts

@@ -74,10 +74,11 @@ export async function createTextEmbeddings(
   const maxSeqLen = meta.inputTensorMeta[0]!.shape[1]!;
   const outShape = meta.outputTensorMeta[0]!.shape;
 
-  const tEmbedding = tensor('float32', outShape);
+  const tensors = [tensor('float32', outShape)] as const;
+  const [tEmbedding] = tensors;
 
   const dispose = () => {
-    tEmbedding.dispose();
+    tensors.forEach((t) => t.dispose());
     tokenizer.dispose();
     model.dispose();
   };