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// META: title=validation tests for WebNN API instanceNormalization operation
// META: global=window,dedicatedworker
// META: script=../resources/utils_validation.js
'use strict';
const kExampleInputDescriptor = {
dataType: 'float32',
dimensions: [2, 2, 2, 2]
};
// 1D tensor descriptor which may be used for `scale`, or `bias` inputs.
const kExample1DTensorDescriptor = {
dataType: 'float32',
dimensions: [2]
};
multi_builder_test(async (t, builder, otherBuilder) => {
const inputFromOtherBuilder =
otherBuilder.input('input', kExampleInputDescriptor);
assert_throws_js(
TypeError, () => builder.instanceNormalization(inputFromOtherBuilder));
}, '[instanceNormalization] throw if input is from another builder');
multi_builder_test(async (t, builder, otherBuilder) => {
const scaleFromOtherBuilder =
otherBuilder.input('scale', kExample1DTensorDescriptor);
const options = {scale: scaleFromOtherBuilder};
const input = builder.input('input', kExampleInputDescriptor);
assert_throws_js(
TypeError, () => builder.instanceNormalization(input, options));
}, '[instanceNormalization] throw if scale option is from another builder');
multi_builder_test(async (t, builder, otherBuilder) => {
const biasFromOtherBuilder =
otherBuilder.input('bias', kExample1DTensorDescriptor);
const options = {bias: biasFromOtherBuilder};
const input = builder.input('input', kExampleInputDescriptor);
assert_throws_js(
TypeError, () => builder.instanceNormalization(input, options));
}, '[instanceNormalization] throw if bias option is from another builder');
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