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keras-js

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Run Keras models in the browser, with GPU support using WebGL

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"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); exports.default = void 0; var _Layer = _interopRequireDefault(require("../../Layer")); var _Tensor = _interopRequireDefault(require("../../Tensor")); var _WebGL = require("../../WebGL2"); var _ndarrayOps = _interopRequireDefault(require("ndarray-ops")); function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } const mapInputProgramSource = "#version 300 es\nprecision highp float;\nprecision highp isampler2D;\n\nin vec2 outTex;\nuniform sampler2D x;\nuniform isampler2D indexMap;\nuniform int inputCols;\nout vec4 outColor;\n\nvoid main() {\n ivec2 size = textureSize(indexMap, 0);\n int out_x = int(float(size[0]) * outTex.x);\n int out_y = int(float(size[1]) * outTex.y);\n\n int index = texelFetch(indexMap, ivec2(out_x, out_y), 0).r;\n\n if (index != -1) {\n int rowIndex = int(floor(float(index) / float(inputCols)));\n int colIndex = int(mod(float(index), float(inputCols)));\n float val = texelFetch(x, ivec2(colIndex, rowIndex), 0).r;\n outColor = vec4(val);\n } else {\n outColor = vec4(0.0);\n }\n}\n"; class UpSampling1D extends _Layer.default { constructor(attrs = {}) { super(attrs); this.layerClass = 'UpSampling1D'; const { size = 2 } = attrs; this.size = size; this.description = `size ${size}`; if (this.gpu) { this.mapInputProgram = _WebGL.webgl2.compileProgram(mapInputProgramSource); } } call(x) { if (this.gpu) { this._callGPU(x); } else { this._callCPU(x); } return this.output; } _callCPU(x) { this.inputShape = x.tensor.shape; this.outputShape = [this.inputShape[0] * this.size, this.inputShape[1]]; this.output = new _Tensor.default([], this.outputShape); for (let i = 0; i < this.size; i++) { _ndarrayOps.default.assign(this.output.tensor.lo(i, 0).step(this.size, 1), x.tensor); } } _createIndexMap() { if (this.indexMap) { return; } const indices = new _Tensor.default([], this.inputShape, { type: Int32Array }); const indicesRow = new _Tensor.default([], this.inputShape, { type: Int32Array }); const indicesCol = new _Tensor.default([], this.inputShape, { type: Int32Array }); for (let i = 0; i < this.inputShape[0]; i++) { _ndarrayOps.default.assigns(indicesRow.tensor.pick(i, null), i); } for (let j = 0; j < this.inputShape[1]; j++) { _ndarrayOps.default.assigns(indicesCol.tensor.pick(null, j), j); } _ndarrayOps.default.muls(indices.tensor, indicesRow.tensor, this.inputShape[1]); _ndarrayOps.default.addeq(indices.tensor, indicesCol.tensor); this.indexMap = new _Tensor.default([], this.outputShape, { type: Int32Array }); for (let i = 0; i < this.size; i++) { _ndarrayOps.default.assign(this.indexMap.tensor.lo(i, 0).step(this.size, 1), indices.tensor); } this.indexMap.createGLTexture({ type: '2d', format: 'int' }); } _callGPU(x) { if (!x.glTexture) { x.createGLTexture({ type: '2d', format: 'float' }); } this.inputShape = x.tensor.shape; this.outputShape = [this.inputShape[0] * this.size, this.inputShape[1]]; this._createIndexMap(); if (!this.output) { this.output = new _Tensor.default([], this.outputShape); this.output.createGLTexture({ type: '2d', format: 'float' }); } _WebGL.webgl2.runProgram({ program: this.mapInputProgram, output: this.output, inputs: [{ input: x, name: 'x' }, { input: this.indexMap, name: 'indexMap' }], uniforms: [{ value: x.glTextureShape[1], type: 'int', name: 'inputCols' }] }); if (this.outbound.length === 0) { this.output.transferFromGLTexture(); } } } exports.default = UpSampling1D;