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Address tfjs-automl typos in documentation strings (#8219)
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tfjs-automl/README.md

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@@ -48,10 +48,10 @@ const modelUrl = 'model.json'; // URL to the model.json file.
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const model = await automl.loadImageClassification(modelUrl);
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```
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If you do not want (or cannot) load the model over HTTP you can also load the model separately and directly use the constuctor.
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If you do not want (or cannot) load the model over HTTP you can also load the model separately and directly use the constructor.
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This is particularly relevant for __non-browser__ platforms.
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The following psuedocode demonstrates this approach:
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The following pseudocode demonstrates this approach:
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```js
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import * as automl from '@tensorflow/tfjs-automl';
@@ -138,10 +138,10 @@ const modelUrl = 'model.json'; // URL to the model.json file.
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const model = await automl.loadObjectDetection(modelUrl);
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```
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If you do not want (or cannot) load the model over HTTP you can also load the model separately and directly use the constuctor.
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If you do not want (or cannot) load the model over HTTP you can also load the model separately and directly use the constructor.
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This is particularly relevant for __non-browser__ platforms.
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The following psuedocode demonstrates this approach:
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The following pseudocode demonstrates this approach:
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```js
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import * as automl from '@tensorflow/tfjs-automl';

tfjs-automl/src/test_browser.ts

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@@ -39,7 +39,7 @@ const testEnv = parseTestEnvFromKarmaFlags(__karma__.config.args, TEST_ENVS);
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if (testEnv != null) {
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setTestEnvs([testEnv]);
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} else {
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// Run browser tests againts both the webgl backends.
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// Run browser tests against both the webgl backends.
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setTestEnvs([
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// WebGL.
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{

tfjs-automl/src/test_node.ts

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@@ -28,7 +28,7 @@ process.on('unhandledRejection', e => {
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throw e;
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});
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// Run node tests againts the cpu backend.
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// Run node tests against the cpu backend.
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setTestEnvs([{name: 'node', backendName: 'cpu'}]);
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const runner = new jasmine();

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