Method call

custom-layer/custom_layer.js:65–79

* Centers the input and applies the following function to every element of * the input. * * x => [max(x, 0), max(-x, 0)] * * The theory being that there may be signal in the both negative and positive * portions of the input. Note that this will double the number of channels.

(inputs, kwargs)

   *   example code.
   */
  call(inputs, kwargs) {
    let input = inputs;
    if (Array.isArray(input)) {
      input = input[0];
    }
    this.invokeCallHook(inputs, kwargs);
    const origShape = input.shape;
    const flatShape =
        [origShape[0], origShape[1] * origShape[2] * origShape[3]];
    const flattened = input.reshape(flatShape);
    const centered = tf.sub(flattened, flattened.mean(1).expandDims(1));
    const pos = centered.relu().reshape(origShape);
    const neg = centered.neg().relu().reshape(origShape);
    return tf.concat([pos, neg], 3);
  }

  /**
   * If a custom layer class is to support serialization, it must implement