fix lint

Author: alicialics

tensorboard/plugins/projector/vz_projector/knn.ts

@@ -57,20 +57,18 @@ export function findKNNGPUCosDistNorm<T>(
           const typedArray = vector.toTypedArray(dataPoints, accessor);
           const bigMatrix = tf.tensor(typedArray, [N, dim]);
           const bigMatrixTransposed = tf.transpose(bigMatrix);
-          // 1 - A * A^T.
-          const bigMatrixSquared = tf.matMul(bigMatrix, bigMatrixTransposed);
-          const cosDistMatrix = tf.sub(1, bigMatrixSquared);
+          // A * A^T.
+          const cosSimilarityMatrix = tf.matMul(bigMatrix, bigMatrixTransposed);
+          bigMatrix.dispose();
+          bigMatrixTransposed.dispose();
           // `.data()` returns flattened Float32Array of B * N dimension.
           // For matrix of
           // [ 1  2 ]
           // [ 3  4 ],
           // `.data()` returns [1, 2, 3, 4].
-          const partial = await cosDistMatrix.data();
+          const partial = await cosSimilarityMatrix.data();
           // Discard all tensors and free up the memory.
-          bigMatrix.dispose();
-          bigMatrixTransposed.dispose();
-          bigMatrixSquared.dispose();
-          cosDistMatrix.dispose();
+          cosSimilarityMatrix.dispose();
           for (let i = 0; i < N; i++) {
             let kMin = new KMin<NearestEntry>(k);
             for (let j = 0; j < N; j++) {
@@ -81,15 +79,15 @@ export function findKNNGPUCosDistNorm<T>(
               // Access i * N's row at `j` column.
               // Reach row has N entries and j-th index has cosine distance
               // between i-th vs. j-th vectors.
-              const cosDist = partial[i * N + j];
+              const cosDist = 1 - partial[i * N + j];
               if (cosDist >= 0) {
                 kMin.add(cosDist, {index: j, dist: cosDist});
               }
             }
             nearest[i] = kMin.getMinKItems();
           }
         },
-        KNN_MSG_ID,
+        KNN_MSG_ID
       )
       .then(
         () => {
@@ -163,7 +161,7 @@ export function findKNN<T>(
       logging.setModalMessage(null!, KNN_MSG_ID);
       return nearest;
     },
-    KNN_MSG_ID,
+    KNN_MSG_ID
   );
 }
 /**
@@ -194,4 +192,3 @@ export function findKNNofPoint<T>(
   }
   return kMin.getMinKItems();
 }
-