Method decodeSequence

translation/index.js:131–174

(inputSeq)

  }

  decodeSequence(inputSeq) {
    // Encode the inputs state vectors.
    let statesValue = this.encoderModel.predict(inputSeq);

    // Generate empty target sequence of length 1.
    let targetSeq = tf.buffer([1, 1, this.numDecoderTokens]);
    // Populate the first character of the target sequence with the start
    // character.
    targetSeq.set(1, 0, 0, this.targetTokenIndex['\t']);

    // Sample loop for a batch of sequences.
    // (to simplify, here we assume that a batch of size 1).
    let stopCondition = false;
    let decodedSentence = '';
    while (!stopCondition) {
      const predictOutputs =
          this.decoderModel.predict([targetSeq.toTensor()].concat(statesValue));
      const outputTokens = predictOutputs[0];
      const h = predictOutputs[1];
      const c = predictOutputs[2];

      // Sample a token.
      // We know that outputTokens.shape is [1, 1, n], so no need for slicing.
      const logits = outputTokens.reshape([outputTokens.shape[2]]);
      const sampledTokenIndex = logits.argMax().dataSync()[0];
      const sampledChar = this.reverseTargetCharIndex[sampledTokenIndex];
      decodedSentence += sampledChar;

      // Exit condition: either hit max length or find stop character.
      if (sampledChar === '\n' ||
          decodedSentence.length > this.maxDecoderSeqLength) {
        stopCondition = true;
      }

      // Update the target sequence (of length 1).
      targetSeq = tf.buffer([1, 1, this.numDecoderTokens]);
      targetSeq.set(1, 0, 0, sampledTokenIndex);

      // Update states.
      statesValue = [h, c];
    }

    return decodedSentence;
  }

  /** Translate the given English sentence into French. */
  translate(inputSentence) {