Function standardizeInputData

tfjs-layers/src/engine/training.ts:81–185

(
    data: Tensor|Tensor[]|{[inputName: string]: Tensor}, names: string[],
    shapes?: Shape[], checkBatchAxis = true, exceptionPrefix = '')

 * @throws ValueError: in case of improperly formatted user data.
 */
export function standardizeInputData(
    data: Tensor|Tensor[]|{[inputName: string]: Tensor}, names: string[],
    shapes?: Shape[], checkBatchAxis = true, exceptionPrefix = ''): Tensor[] {
  if (names == null || names.length === 0) {
    // Check for the case where the model expected no data, but some data got
    // sent.
    if (data != null) {
      let gotUnexpectedData = false;
      if (isDataArray(data) && (data as Tensor[]).length > 0) {
        gotUnexpectedData = true;
      } else if (isDataDict(data)) {
        for (const key in data) {
          if (data.hasOwnProperty(key)) {
            gotUnexpectedData = true;
            break;
          }
        }
      } else {
        // `data` is a singleton Tensor in this case.
        gotUnexpectedData = true;
      }
      if (gotUnexpectedData) {
        throw new ValueError(
            `Error when checking model ${exceptionPrefix} expected no data, ` +
            `but got ${data}`);
      }
    }
    return [];
  }
  if (data == null) {
    return names.map(name => null);
  }

  let arrays: Tensor[];
  if (isDataDict(data)) {
    data = data as {[inputName: string]: Tensor};
    arrays = [];
    for (const name of names) {
      if (data[name] == null) {
        throw new ValueError(
            `No data provided for "${name}". Need data for each key in: ` +
            `${names}`);
      }
      arrays.push(data[name]);
    }
  } else if (isDataArray(data)) {
    data = data as Tensor[];
    if (data.length !== names.length) {
      throw new ValueError(
          `Error when checking model ${exceptionPrefix}: the Array of ` +
          `Tensors that you are passing to your model is not the size the ` +
          `model expected. Expected to see ${names.length} Tensor(s), but ` +
          `instead got the following list of Tensor(s): ${data}`);
    }
    arrays = data;
  } else {
    data = data as Tensor;
    if (names.length > 1) {