Function any

tfjs-backend-cpu/src/kernels/Any.ts:25–77

(
    args: {inputs: AnyInputs, backend: MathBackendCPU, attrs: AnyAttrs})

import {transpose} from './Transpose';

export function any(
    args: {inputs: AnyInputs, backend: MathBackendCPU, attrs: AnyAttrs}):
    TensorInfo {
  const {inputs, backend, attrs} = args;
  const {x} = inputs;
  const {axis, keepDims} = attrs;

  assertNotComplex(x, 'any');

  const origAxes = util.parseAxisParam(axis, x.shape);
  let axes = origAxes;
  const permutedAxes = backend_util.getAxesPermutation(axes, x.shape.length);
  let $x = x;
  if (permutedAxes != null) {
    $x = transpose({inputs: {x}, backend, attrs: {perm: permutedAxes}});
    axes = backend_util.getInnerMostAxes(axes.length, x.shape.length);
  }

  backend_util.assertAxesAreInnerMostDims('any', axes, $x.shape.length);
  const [outShape, reduceShape] =
      backend_util.computeOutAndReduceShapes($x.shape, axes);
  const reduceSize = util.sizeFromShape(reduceShape);
  const vals = util.makeZerosTypedArray(util.sizeFromShape(outShape), $x.dtype);

  const aVals = backend.data.get($x.dataId).values as TypedArray;
  for (let i = 0; i < vals.length; ++i) {
    const offset = i * reduceSize;
    let anyVal = aVals[offset];
    for (let j = 0; j < reduceSize; ++j) {
      const value = aVals[offset + j];
      anyVal = anyVal || value;
    }
    vals[i] = anyVal;
  }

  if (permutedAxes != null) {
    backend.disposeIntermediateTensorInfo($x);
  }

  const result = backend.makeTensorInfo(outShape, $x.dtype, vals);

  if (keepDims) {
    const expandedShape = backend_util.expandShapeToKeepDim(outShape, origAxes);
    const reshapedResult =
        reshape({inputs: {x: result}, backend, attrs: {shape: expandedShape}});

    backend.disposeIntermediateTensorInfo(result);

    return reshapedResult;
  }

  return result;
}

export const anyConfig: KernelConfig = {
  kernelName: Any,