dgkris

const fetchToken = () => {
  return new Promise((resolve) => {
    chrome.storage.sync.get(["userToken"], (obj) => {
      resolve(obj["userToken"] ? obj["userToken"] : "");
    });
  });
};

const fetchRefreshToken = () => {
  return new Promise((resolve) => {

dgkris

https://www.buycott.com/campaign/browse
https://www.buycott.com/campaign/browse#campaign_trending
https://www.buycott.com/campaign/browse#campaign_popular
https://www.buycott.com/campaign/1317/boycott-trump-products
https://www.buycott.com/campaign/1177/save-and-support-the-bees-as-much-as-you-can
https://www.buycott.com/campaign/1193/stop-buying-products-manufactured-using-prison-slave-labor
https://www.buycott.com/campaign/613/boycott-russian-products-because-of-homophobic-lgbt-policies
https://www.buycott.com/campaign/412/reject-magic-hat-s-frivolous-lawsuit-against-west-sixth
https://www.buycott.com/campaign/211/pro-gmo-or-pro-right-to-know
https://www.buycott.com/campaign/354/say-no-to-palm-oil-products

dgkris

{
  "geocoding": {
    "version": "0.2",
    "attribution": "https://geocode.earth/guidelines",
    "query": {
      "parsed_text": {
        "postalcode": "87801"
      },
      "size": 10,
      "private": false,

dgkris

{
  "logger": {
    "level": "info",
    "timestamp": false
  },
  "esclient": {
    "hosts": [
      { "host": "0.0.0.0" }
    ]
  },

dgkris

for i in range(200):
  for j in range(300):
    print("hello")
    print("hello")
    
for i in range(200):
  for j in range(300):
    print("hello")
    print("hello")

dgkris

{
  "logger": {
    "level": "info",
    "timestamp": false
  },
  "esclient": {
    "hosts": [
      { "host": "elasticsearch" }
    ]
  },

dgkris

for i in range(100):
     for a in range(250):
          for b in range(200):
               print "abba"
     for j in range(300):
          print "hello"

dgkris

        MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
            .seed(12345)
            .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).iterations(1)
            .iterations(1)
            .activation(Activation.RELU)
            .weightInit(WeightInit.XAVIER)
            .learningRate(0.1)
            .list()
            .layer(0, new DenseLayer.Builder().nIn(402).nOut(1024).build())
            .layer(1, new DenseLayer.Builder().nIn(1024).nOut(2048).build())

dgkris

 public static void predict(SentimentExampleIterator iter,MultiLayerNetwork net,String sentence) {
        DataSet dataSet=iter.reviewEncode(sentence);
        INDArray features = dataSet.getFeatureMatrix();
        INDArray inMask = dataSet.getFeaturesMaskArray();
        INDArray outMask = dataSet.getLabelsMaskArray();
        INDArray predicted = net.output(features,false,inMask,outMask);
        INDArray output=predicted.get(NDArrayIndex.point(0), NDArrayIndex.all(), NDArrayIndex.point(predicted.shape()[2]-1));
        System.out.println(output);
    }
    

dgkris

//Prediction logic
    public void predict(MultiLayerNetwork net,String sentence) {
        SentimentExampleIterator iter = null;
        DataSet dataSet=iter.reviewEncode("hello world");
            INDArray features = dataSet.getFeatureMatrix();
            INDArray inMask = dataSet.getFeaturesMaskArray();
            INDArray outMask = dataSet.getLabelsMaskArray();
            INDArray predicted = net.output(features,false,inMask,outMask);
    }