Address typos in tfjs-core documentation strings

tfjs-core/src/backends/einsum_util.ts

@@ -167,7 +167,7 @@ export function checkEinsumDimSizes(
  *
  * @param summedDims indices to the dimensions being summed over.
  * @param idDims A look up table for the dimensions present in each input
- *     tensor. Each consituent array contains indices for the dimensions in the
+ *     tensor. Each constituent array contains indices for the dimensions in the
  *     corresponding input tensor.
  *
  * @return A map with two fields:

tfjs-core/src/backends/non_max_suppression_impl.ts

@@ -188,7 +188,7 @@ function intersectionOverUnion(boxes: TypedArray, i: number, j: number) {
 
 // A Gaussian penalty function, this method always returns values in [0, 1].
 // The weight is a function of similarity, the more overlap two boxes are, the
-// smaller the weight is, meaning highly overlapping boxe will be significantly
+// smaller the weight is, meaning highly overlapping boxes will be significantly
 // penalized. On the other hand, a non-overlapping box will not be penalized.
 function suppressWeight(iouThreshold: number, scale: number, iou: number) {
   const weight = Math.exp(scale * iou * iou);

tfjs-core/src/engine.ts

@@ -313,7 +313,7 @@ export class Engine implements TensorTracker, DataMover {
   /**
    * Initializes a backend by looking up the backend name in the factory
    * registry and calling the factory method. Returns a boolean representing
-   * whether the initialization of the backend suceeded. Throws an error if
+   * whether the initialization of the backend succeeded. Throws an error if
    * there is no backend in the factory registry.
    */
   private initializeBackend(backendName: string):

tfjs-core/src/engine_test.ts

@@ -243,7 +243,7 @@ describe('Backend registration', () => {
          throw new Error('failed to create async2');
        }, 101 /* priority */);
 
-       // Await for the library to find the best backend that succesfully
+       // Await for the library to find the best backend that successfully
        // initializes.
        await tf.ready();
        expect(tf.backend()).toEqual(testBackend);

tfjs-core/src/io/browser_files_test.ts

@@ -259,7 +259,7 @@ describeWithFlags('browserDownloads', BROWSER_ENVS, () => {
     // Verify that the default file names are used.
     expect(jsonAnchor.download).toEqual('model.json');
     expect(jsonAnchor.clicked).toEqual(1);
-    // The weight file should not have been downoaded.
+    // The weight file should not have been downloaded.
     expect(weightDataAnchor.download).toEqual(undefined);
     expect(weightDataAnchor.clicked).toEqual(0);
 

tfjs-core/src/io/composite_array_buffer.ts

@@ -91,7 +91,7 @@ export class CompositeArrayBuffer {
       start = end;
     }
 
-    // Set the byteLenghth
+    // Set the byteLength
     if (this.shards.length === 0) {
       this.byteLength = 0;
     }

tfjs-core/src/io/http.ts

@@ -324,7 +324,7 @@ IORouterRegistry.registerLoadRouter(httpRouter);
  * The following GitHub Gist
  * https://gist.github.com/dsmilkov/1b6046fd6132d7408d5257b0976f7864
  * implements a server based on [flask](https://github.com/pallets/flask) that
- * can receive the request. Upon receiving the model artifacts via the requst,
+ * can receive the request. Upon receiving the model artifacts via the request,
  * this particular server reconstitutes instances of [Keras
  * Models](https://keras.io/models/model/) in memory.
  *

tfjs-core/src/io/http_test.ts

@@ -446,7 +446,7 @@ describeWithFlags('parseUrl', BROWSER_ENVS, () => {
     expect(prefix).toEqual('http://google.com/');
     expect(suffix).toEqual('?param=1');
   });
-  it('should parse url with multiple serach params', () => {
+  it('should parse url with multiple search params', () => {
     const url = 'http://google.com/a?x=1/file?param=1';
     const [prefix, suffix] = parseUrl(url);
     expect(prefix).toEqual('http://google.com/a?x=1/');

tfjs-core/src/io/indexed_db.ts

@@ -255,7 +255,7 @@ IORouterRegistry.registerLoadRouter(indexedDBRouter);
  *
  * @param modelPath A unique identifier for the model to be saved. Must be a
  *   non-empty string.
- * @returns An instance of `BrowserIndexedDB` (sublcass of `IOHandler`),
+ * @returns An instance of `BrowserIndexedDB` (subclass of `IOHandler`),
  *   which can be used with, e.g., `tf.Model.save`.
  */
 export function browserIndexedDB(modelPath: string): IOHandler {

tfjs-core/src/io/indexed_db_test.ts

@@ -172,7 +172,7 @@ describeWithFlags('IndexedDB', BROWSER_ENVS, () => {
 
        try {
          await handler.load();
-         fail('Loading nonexistent model from IndexedDB succeeded unexpectly');
+         fail('Loading nonexistent model from IndexedDB succeeded unexpectedly');
        } catch (err) {
          expect(err.message)
              .toEqual(

tfjs-core/src/io/weights_loader_test.ts

@@ -332,7 +332,7 @@ describeWithFlags('loadWeights', BROWSER_ENVS, () => {
     expect(weight2.dtype).toEqual('float32');
   });
 
-  it('2 group, 4 weights, dont specify weights fetchs all', async () => {
+  it('2 group, 4 weights, dont specify weights fetches all', async () => {
     setupFakeWeightFiles({
       './weightfile0': new Float32Array([1, 2, 3, 4, 5]),
       './weightfile1': new Float32Array([6, 7, 8, 9])

tfjs-core/src/jasmine_util.ts

@@ -105,7 +105,7 @@ export interface TestFilter {
  *     Tests that have the substrings specified by the include or startsWith
  *     will be included in the test run, unless one of the substrings specified
  *     by `excludes` appears in the name.
- * @param customInclude Function to programatically include a test.
+ * @param customInclude Function to programmatically include a test.
  *     If this function returns true, a test will immediately run. Otherwise,
  *     `testFilters` is used for fine-grained filtering.
  *
@@ -124,7 +124,7 @@ export function setupTestFilters(
    * Filter method that returns boolean, if a given test should run or be
    * ignored based on its name. The exclude list has priority over the
    * include list. Thus, if a test matches both the exclude and the include
-   * list, it will be exluded.
+   * list, it will be excluded.
    */
   // tslint:disable-next-line: no-any
   const specFilter = (spec: any) => {

tfjs-core/src/ops/browser.ts

@@ -254,7 +254,7 @@ export async function fromPixelsAsync(
     // In some cases, the input will have larger size than its content.
     // E.g. new Image(10, 10) but with 1 x 1 content. Using
     // createImageBitmap will clip the size from 10 x 10 to 1 x 1, which
-    // is not correct. We should avoid wrapping such resouce to
+    // is not correct. We should avoid wrapping such resource to
     // imageBitmap.
     if (imageBitmap != null && imageBitmap.width === pixels.width &&
         imageBitmap.height === pixels.height) {
@@ -292,7 +292,7 @@ function validateImgTensor(img: Tensor2D|Tensor3D) {
 function validateImageOptions(imageOptions: ImageOptions) {
   const alpha = imageOptions ?.alpha || 1;
   if (alpha > 1 || alpha < 0) {
-    throw new Error(`Alpha value ${alpha} is suppoed to be in range [0 - 1].`);
+    throw new Error(`Alpha value ${alpha} is supposed to be in range [0 - 1].`);
   }
 }
 

tfjs-core/src/ops/ensure_shape.ts

@@ -23,7 +23,7 @@ import {arraysEqualWithNull} from '../util_base';
 import {op} from './operation';
 
 /**
- * Checks the input tensor mathes the given shape.
+ * Checks the input tensor matches the given shape.
  *
  * Given an input tensor, returns a new tensor with the same values as the
  * input tensor with shape `shape`.

tfjs-core/src/ops/image/crop_and_resize.ts

@@ -39,7 +39,7 @@ import {op} from '../operation';
  *     coordinates of the box in the `boxInd[i]`th image in the batch
  * @param boxInd 1d int32 tensor of shape `[numBoxes]` with values in range
  *     `[0, batch)` that specifies the image that the `i`-th box refers to.
- * @param cropSize 1d int32 tensor of 2 elements `[cropHeigh, cropWidth]`
+ * @param cropSize 1d int32 tensor of 2 elements `[cropHeight, cropWidth]`
  *     specifying the size to which all crops are resized to.
  * @param method Optional string from `'bilinear' | 'nearest'`,
  *     defaults to bilinear, which specifies the sampling method for resizing

tfjs-core/src/ops/linalg/qr_test.ts

@@ -135,7 +135,7 @@ describeWithFlags('qr', ALL_ENVS, () => {
     expect(tf.memory().numTensors).toEqual(numTensors + 2);
   });
 
-  it('Insuffient input tensor rank leads to error', () => {
+  it('Insufficient input tensor rank leads to error', () => {
     const x1 = scalar(12);
     expect(() => tf.linalg.qr(x1)).toThrowError(/rank >= 2.*got rank 0/);
     const x2 = tensor1d([12]);

tfjs-core/src/ops/ragged_tensor_to_tensor.ts

@@ -70,7 +70,7 @@ import {op} from './operation';
  *     "ROW_SPLITS": the row_splits tensor from the ragged tensor.
  *     "VALUE_ROWIDS": the value_rowids tensor from the ragged tensor.
  *     "FIRST_DIM_SIZE": if value_rowids is used for the first dimension, then
- *         it is preceeded by "FIRST_DIM_SIZE". The tensors are in the order of
+ *         it is preceded by "FIRST_DIM_SIZE". The tensors are in the order of
  *         the dimensions.
  * @return A Tensor. Has the same type as values.
  * @doc {heading: 'Operations', subheading: 'Ragged'}

tfjs-core/src/ops/rand_util.ts

@@ -222,7 +222,7 @@ export function jarqueBeraNormalityTest(values: TypedArray|number[]) {
   const s = skewness(values);
   const k = kurtosis(values);
   const jb = n / 6 * (Math.pow(s, 2) + 0.25 * Math.pow(k - 3, 2));
-  // JB test requires 2-degress of freedom from Chi-Square @ 0.95:
+  // JB test requires 2-degrees of freedom from Chi-Square @ 0.95:
   // http://www.itl.nist.gov/div898/handbook/eda/section3/eda3674.htm
   const CHI_SQUARE_2DEG = 5.991;
   if (jb > CHI_SQUARE_2DEG) {

tfjs-core/src/ops/tensor.ts

@@ -160,7 +160,7 @@ import {makeTensor} from './tensor_ops_util';
  * const aBuffer = createGPUBufferFromData(device, aData, dtype);
  * const shape = [aData.length];
  * // To use zeroCopy, use {buffer: aBuffer, zeroCopy: true} instead and destroy
- * // aBuffer untill all access is done.
+ * // aBuffer until all access is done.
  * const a = tf.tensor({buffer: aBuffer}, shape, dtype);
  * const b = tf.tensor(bData, shape, dtype);
  * const result = tf.add(a, b);

tfjs-core/src/serialization.ts

@@ -225,7 +225,7 @@ export class SerializationMap {
  *
  * @param cls The class to be registered. It must have a public static member
  *   called `className` defined and the value must be a non-empty string.
- * @param pkg The pakcage name that this class belongs to. This used to define
+ * @param pkg The package name that this class belongs to. This used to define
  *     the key in GlobalCustomObject. If not defined, it defaults to `Custom`.
  * @param name The name that user specified. It defaults to the actual name of
  *     the class as specified by its static `className` property.

tfjs-core/src/tensor.ts

@@ -518,7 +518,7 @@ Object.defineProperty(Tensor, Symbol.hasInstance, {
 
 export function getGlobalTensorClass() {
   // Use getGlobal so that we can augment the Tensor class across package
-  // boundaries becase the node resolution alg may result in different modules
+  // boundaries because the node resolution alg may result in different modules
   // being returned for this file depending on the path they are loaded from.
   return getGlobal('Tensor', () => {
     return Tensor;