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ArgMax.ts
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ArgMax.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 {ArgMax, ArgMaxAttrs, ArgMaxInputs, backend_util, KernelConfig, KernelFunc, TensorInfo, TypedArray, util} from '@tensorflow/tfjs-core';
import {MathBackendCPU} from '../backend_cpu';
import {assertNotComplex} from '../cpu_util';
import {transpose} from './Transpose';
export function argMax(
args: {inputs: ArgMaxInputs, backend: MathBackendCPU, attrs: ArgMaxAttrs}):
TensorInfo {
const {inputs, backend, attrs} = args;
const {x} = inputs;
const {axis} = attrs;
assertNotComplex(x, 'argMax');
let axes = util.parseAxisParam(axis, x.shape);
const permutedAxes = backend_util.getAxesPermutation(axes, x.shape.length);
let $x = x;
const intermediateTensorInfos = [];
if (permutedAxes != null) {
$x = transpose({inputs: {x}, backend, attrs: {perm: permutedAxes}});
intermediateTensorInfos.push($x);
axes = backend_util.getInnerMostAxes(axes.length, $x.shape.length);
}
axes = [axes[0]];
backend_util.assertAxesAreInnerMostDims('argMax', axes, $x.shape.length);
const [outShape, reduceShape] =
backend_util.computeOutAndReduceShapes($x.shape, axes);
const outSize = util.sizeFromShape(outShape);
const vals = util.makeZerosTypedArray(outSize, 'int32');
const reduceSize = util.sizeFromShape(reduceShape);
const aVals = backend.data.get($x.dataId).values as TypedArray;
for (let i = 0; i < vals.length; ++i) {
const offset = i * reduceSize;
let max = aVals[offset];
let maxIndex = 0;
for (let j = 0; j < reduceSize; ++j) {
const value = aVals[offset + j];
if (value > max) {
max = value;
maxIndex = j;
}
}
vals[i] = maxIndex;
}
intermediateTensorInfos.forEach(
t => backend.disposeIntermediateTensorInfo(t));
return backend.makeTensorInfo(outShape, 'int32', vals);
}
export const argMaxConfig: KernelConfig = {
kernelName: ArgMax,
backendName: 'cpu',
kernelFunc: argMax as unknown as KernelFunc
};