74 lines
3.2 KiB
JavaScript
74 lines
3.2 KiB
JavaScript
"use strict";
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.parseImageScalerAttributes = exports.imageScaler = void 0;
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const attribute_with_cache_key_1 = require("../../../attribute-with-cache-key");
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const types_1 = require("../types");
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const imageScaler = (inferenceHandler, inputs, attributes) => {
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validateInputs(inputs);
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const output = inferenceHandler.run(createImageScalerProgramInfoLoader(inferenceHandler, inputs, attributes), inputs);
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return [output];
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};
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exports.imageScaler = imageScaler;
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const parseImageScalerAttributes = (node) => {
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const scale = node.attributes.getFloat('scale');
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const bias = node.attributes.getFloats('bias');
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return (0, attribute_with_cache_key_1.createAttributeWithCacheKey)({ scale, bias });
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};
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exports.parseImageScalerAttributes = parseImageScalerAttributes;
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const imageScalerProgramMetadata = {
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name: 'ImageScaler',
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inputNames: ['X'],
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inputTypes: [types_1.TextureType.unpacked],
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};
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const createImageScalerProgramInfo = (handler, metadata, inputs, attributes) => {
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const outputShape = inputs[0].dims.slice();
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const rank = outputShape.length;
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const getBiasMethod = createGetBiasMethod(attributes.bias.length);
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const shaderSource = `
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${getBiasMethod}
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float process(int indices[${rank}]) {
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return _X(indices) * scale + getBias(bias, indices[1]);
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}`;
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return Object.assign(Object.assign({}, metadata), { output: { dims: outputShape, type: inputs[0].type, textureType: types_1.TextureType.unpacked }, variables: [
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{ name: 'bias', type: 'float', arrayLength: attributes.bias.length, data: attributes.bias },
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{ name: 'scale', type: 'float', data: attributes.scale }
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], shaderSource });
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};
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const createImageScalerProgramInfoLoader = (handler, inputs, attributes) => {
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const metadata = Object.assign(Object.assign({}, imageScalerProgramMetadata), { cacheHint: attributes.cacheKey });
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return Object.assign(Object.assign({}, metadata), { get: () => createImageScalerProgramInfo(handler, metadata, inputs, attributes) });
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};
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const createGetBiasMethod = (numChannels) => {
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const codeLines = [`float getBias(float bias[${numChannels}], int channel) {`];
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for (let i = 0; i < numChannels; ++i) {
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if (i === 0) {
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codeLines.push('\t' +
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`if (channel == ${i}) { return bias[${i}]; }`);
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}
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else if (i === numChannels - 1) {
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codeLines.push('\t' +
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`else { return bias[${i}]; }`);
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}
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else {
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codeLines.push('\t' +
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`else if (channel == ${i}) { return bias[${i}]; }`);
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}
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}
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codeLines.push('\t' +
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'}');
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return codeLines.join('\n');
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};
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const validateInputs = (inputs) => {
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if (!inputs || inputs.length !== 1) {
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throw new Error('ImageScaler requires 1 input.');
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}
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if (inputs[0].dims.length !== 4) {
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throw new Error('Invalid input shape.');
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}
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if (inputs[0].type !== 'float32' && inputs[0].type !== 'float64') {
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throw new Error('Invalid input type.');
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}
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};
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//# sourceMappingURL=image-scaler.js.map
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