@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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text/typescript
/**
* @license
* Copyright 2017 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import {GPGPUContext} from './gpgpu_context';
import {GPGPUProgram} from './gpgpu_math';
export class MultinomialProgram implements GPGPUProgram {
variableNames = ['probs'];
outputShape: number[];
userCode: string;
// Caching uniform location for speed.
seedLoc: WebGLUniformLocation;
constructor(batchSize: number, numOutcomes: number, numSamples: number) {
this.outputShape = [batchSize, numSamples];
this.userCode = `
uniform float seed;
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
float r = random(seed);
float cdf = 0.0;
for (int i = 0; i < ${numOutcomes - 1}; i++) {
cdf += getProbs(batch, i);
if (r < cdf) {
setOutput(float(i));
return;
}
}
// If no other event happened, last event happened.
setOutput(float(${numOutcomes - 1}));
}
`;
}
getCustomSetupFunc(seed: number) {
return (gpgpu: GPGPUContext, webGLProgram: WebGLProgram) => {
if (this.seedLoc == null) {
this.seedLoc = gpgpu.getUniformLocation(webGLProgram, 'seed');
}
gpgpu.gl.uniform1f(this.seedLoc, seed);
};
}
}