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LRN.ts
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LRN.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 {KernelConfig, KernelFunc, LRN, LRNAttrs, LRNInputs, TensorInfo, TypedArray, util} from '@tensorflow/tfjs-core';
import {MathBackendCPU} from '../backend_cpu';
import {assertNotComplex} from '../cpu_util';
export function lRN(
args: {inputs: LRNInputs, backend: MathBackendCPU, attrs: LRNAttrs}):
TensorInfo {
const {inputs, backend, attrs} = args;
const {x} = inputs;
const {depthRadius, bias, alpha, beta} = attrs;
assertNotComplex(x, 'LRN');
const channels = x.shape[3];
const maxD = channels - 1;
const xValues = backend.data.get(x.dataId).values as TypedArray;
const size = util.sizeFromShape(x.shape);
const result = new Float32Array(size);
function sumAcrossChannels(offset: number) {
const currentChannel = offset % channels;
let beginSumOffset =
offset - currentChannel + Math.max(0, currentChannel - depthRadius);
const endSumOffset =
offset - currentChannel + Math.min(currentChannel + depthRadius, maxD);
let sum = 0.0;
for (; beginSumOffset <= endSumOffset; beginSumOffset++) {
const z = xValues[beginSumOffset];
sum += z * z;
}
return sum;
}
for (let offset = 0; offset < size; offset++) {
const sum = sumAcrossChannels(offset);
const val = xValues[offset] * Math.pow(bias + alpha * sum, -beta);
result[offset] = val;
}
return backend.makeTensorInfo(x.shape, x.dtype, result);
}
// tslint:disable-next-line: variable-name
export const LRNConfig: KernelConfig = {
kernelName: LRN,
backendName: 'cpu',
kernelFunc: lRN as unknown as KernelFunc
};