Function validateInput

tfjs-core/src/ops/sparse_to_dense_util.ts:32–66

(
    sparseIndices: Tensor, sparseValues: Tensor, outputShape: number[],
    defaultValues: Tensor)

 * will be thrown if it is set.
 */
export function validateInput(
    sparseIndices: Tensor, sparseValues: Tensor, outputShape: number[],
    defaultValues: Tensor) {
  if (sparseIndices.dtype !== 'int32') {
    throw new Error(
        'tf.sparseToDense() expects the indices to be int32 type,' +
        ` but the dtype was ${sparseIndices.dtype}.`);
  }
  if (sparseIndices.rank > 2) {
    throw new Error(
        'sparseIndices should be a scalar, vector, or matrix,' +
        ` but got shape ${sparseIndices.shape}.`);
  }

  const numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;
  const numDims = sparseIndices.rank > 1 ? sparseIndices.shape[1] : 1;

  if (outputShape.length !== numDims) {
    throw new Error(
        'outputShape has incorrect number of elements:,' +
        ` ${outputShape.length}, should be: ${numDims}.`);
  }

  const numValues = sparseValues.size;
  if (!(sparseValues.rank === 0 ||
        sparseValues.rank === 1 && numValues === numElems)) {
    throw new Error(
        'sparseValues has incorrect shape ' +
        `${sparseValues.shape}, should be [] or [${numElems}]`);
  }

  if (sparseValues.dtype !== defaultValues.dtype) {
    throw new Error('sparseValues.dtype must match defaultValues.dtype');
  }
}