docs: public INDArray loadSingleSentence(String sentence) {
          List<String> tokens = tokenizeSentence(sentence);
          if(format == Format.CNN1D || format == Format.RNN){
              int[] featuresShape = new int[] {1, wordVectorSize, Math.min(maxSentenceLength, tokens.size())};
              INDArray features = Nd4j.create(featuresShape, (format == Format.CNN1D ? 'c' : 'f'));
              INDArrayIndex[] indices = new INDArrayIndex[3];
              indices[0] = NDArrayIndex.point(0);
              for (int i = 0; i < featuresShape[2]; i++) {
                  INDArray vector = getVector(tokens.get(i));
                  indices[1] = NDArrayIndex.all();
                  indices[2] = NDArrayIndex.point(i);
                  features.put(indices, vector);
              }
              return features;
          } else {
              int[] featuresShape = new int[] {1, 1, 0, 0};
              if (sentencesAlongHeight) {
                  featuresShape[2] = Math.min(maxSentenceLength, tokens.size());
                  featuresShape[3] = wordVectorSize;
              } else {
                  featuresShape[2] = wordVectorSize;
                  featuresShape[3] = Math.min(maxSentenceLength, tokens.size());
              }
  
              INDArray features = Nd4j.create(featuresShape);
              int length = (sentencesAlongHeight ? featuresShape[2] : featuresShape[3]);
              INDArrayIndex[] indices = new INDArrayIndex[4];
              indices[0] = NDArrayIndex.point(0);
              indices[1] = NDArrayIndex.point(0);
              for (int i = 0; i < length; i++) {
                  INDArray vector = getVector(tokens.get(i));
  
                  if (sentencesAlongHeight) {
                      indices[2] = NDArrayIndex.point(i);
                      indices[3] = NDArrayIndex.all();
                  } else {
                      indices[2] = NDArrayIndex.all();
                      indices[3] = NDArrayIndex.point(i);
                  }
  
                  features.put(indices, vector);
              }
  
              return features;
          }
      }