Function configureCallbacks

tfjs-layers/src/base_callbacks.ts:579–609

(
    callbacks: BaseCallback[], verbose: ModelLoggingVerbosity, epochs: number,
    initialEpoch: number, numTrainSamples: number, stepsPerEpoch: number,
    batchSize: number, doValidation: boolean,
    callbackMetrics: string[])

}

export function configureCallbacks(
    callbacks: BaseCallback[], verbose: ModelLoggingVerbosity, epochs: number,
    initialEpoch: number, numTrainSamples: number, stepsPerEpoch: number,
    batchSize: number, doValidation: boolean,
    callbackMetrics: string[]): {callbackList: CallbackList, history: History} {
  const history = new History();
  const actualCallbacks: BaseCallback[] = [
    new BaseLogger(), ...CallbackConstructorRegistry.createCallbacks(verbose)
  ];
  if (callbacks != null) {
    actualCallbacks.push(...callbacks);
  }
  actualCallbacks.push(history);
  const callbackList = new CallbackList(actualCallbacks);

  // TODO(cais): Figure out when this LayersModel instance can have a
  // dynamically
  //   set property called 'callback_model' as in PyKeras.

  callbackList.setParams({
    epochs,
    initialEpoch,
    samples: numTrainSamples,
    steps: stepsPerEpoch,
    batchSize,
    verbose,
    doValidation,
    metrics: callbackMetrics,
  });
  return {callbackList, history};
}