Function createSimpleBinaryKernelImpl

tfjs-backend-cpu/src/utils/binary_impl.ts:25–69

(op: SimpleBinaryOperation)

 * Template that creates implementation for binary ops. Supports broadcast.
 */
export function createSimpleBinaryKernelImpl(op: SimpleBinaryOperation):
    SimpleBinaryKernelImpl {
  return (aShape: number[], bShape: number[], aVals: DataValues,
          bVals: DataValues, dtype: DataType): [TypedArray, number[]] => {
    const newShape = backend_util.assertAndGetBroadcastShape(aShape, bShape);

    const resultRank = newShape.length;
    const resultStrides = util.computeStrides(newShape);
    const resultSize = util.sizeFromShape(newShape);

    const result =
        util.getTypedArrayFromDType(dtype as NumericDataType, resultSize);

    const aRank = aShape.length;
    const bRank = bShape.length;

    const aStrides = util.computeStrides(aShape);
    const bStrides = util.computeStrides(bShape);

    const aBroadcastDims = backend_util.getBroadcastDims(aShape, newShape);
    const bBroadcastDims = backend_util.getBroadcastDims(bShape, newShape);

    if (aBroadcastDims.length + bBroadcastDims.length === 0) {
      for (let i = 0; i < result.length; ++i) {
        result[i] = op(aVals[i % aVals.length], bVals[i % bVals.length]);
      }
    } else {
      for (let i = 0; i < result.length; ++i) {
        const loc = util.indexToLoc(i, resultRank, resultStrides);

        const aLoc = loc.slice(-aRank);
        aBroadcastDims.forEach(d => aLoc[d] = 0);
        const aIndex = util.locToIndex(aLoc, aRank, aStrides);

        const bLoc = loc.slice(-bRank);
        bBroadcastDims.forEach(d => bLoc[d] = 0);
        const bIndex = util.locToIndex(bLoc, bRank, bStrides);

        result[i] = op(aVals[aIndex], bVals[bIndex]);
      }
    }

    return [result, newShape];
  };
}