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All.ts
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All.ts
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/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import {All, AllAttrs, AllInputs, backend_util, KernelConfig, KernelFunc, TensorInfo, TypedArray, util} from '@tensorflow/tfjs-core';
import {MathBackendCPU} from '../backend_cpu';
import {assertNotComplex} from '../cpu_util';
import {reshape} from './Reshape';
import {transpose} from './Transpose';
export function all(
args: {inputs: AllInputs, backend: MathBackendCPU, attrs: AllAttrs}):
TensorInfo {
const {inputs, backend, attrs} = args;
const {x} = inputs;
const {axis, keepDims} = attrs;
assertNotComplex(x, 'all');
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('all', 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 all = aVals[offset];
for (let j = 0; j < reduceSize; ++j) {
const value = aVals[offset + j];
all = all && value;
}
vals[i] = all;
}
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 allConfig: KernelConfig = {
kernelName: All,
backendName: 'cpu',
kernelFunc: all as unknown as KernelFunc
};