unprintableNames.https.any.js

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// META: title=test graph inputs/outputs with unprintable names

// META: global=window,dedicatedworker

// META: variant=?cpu

// META: variant=?gpu

// META: variant=?npu

// META: script=../resources/utils.js

// META: timeout=long

'use strict';

let mlContext;

// Skip tests if WebNN is unimplemented.

promise_setup(async () => {

  assert_implements(navigator.ml, 'missing navigator.ml');

  mlContext = await navigator.ml.createContext(contextOptions);

});

promise_test(async () => {

  const operandDescriptor = {

    dataType: 'float32',

    shape: [1],

};

  // Construct a simple graph: A = B * 2.

  const builder = new MLGraphBuilder(mlContext);

  const inputOperand = builder.input('input\x00tensor', operandDescriptor);

  const constantOperand =

      builder.constant(operandDescriptor, Float32Array.from([2]));

  const outputOperand = builder.mul(inputOperand, constantOperand);

  const mlGraph = await builder.build({'output\x00tensor': outputOperand});

  const [inputTensor, outputTensor] = await Promise.all([

    mlContext.createTensor({dataType: 'float32', shape: [1], writable: true}),

    mlContext.createTensor({dataType: 'float32', shape: [1], readable: true})

]);

  mlContext.writeTensor(inputTensor, Float32Array.from([1]));

  mlContext.dispatch(

      mlGraph, {'input\x00tensor': inputTensor},

      {'output\x00tensor': outputTensor});

  const output = await mlContext.readTensor(outputTensor);

  assert_equals(new Float32Array(output)[0], 2);

}, 'tensor names can include null bytes');